text:
Admission factors associated with hospital mortality in patients with haematological malignancy admitted to UK adult, general critical care units: a secondary analysis of the ICNARC Case Mix Programme Database
DOI: 10.1186/cc8016
© Hampshire et al.; licensee BioMed Central Ltd. 2009
Received: 12 May 2009
Accepted: 25 August 2009
Published: 25 August 2009
Patients with haematological malignancy admitted to intensive care have a high mortality. Adverse prognostic factors include the number of organ failures, invasive mechanical ventilation and previous bone marrow transplantation. Severity-of-illness scores may underestimate the mortality of critically ill patients with haematological malignancy. This study investigates the relationship between admission characteristics and outcome in patients with haematological malignancies admitted to intensive care units (ICUs) in England, Wales and Northern Ireland, and assesses the performance of three severity-of-illness scores in this population.
A secondary analysis of the Intensive Care National Audit and Research Centre (ICNARC) Case Mix Programme Database was conducted on admissions to 178 adult, general ICUs in England, Wales and Northern Ireland between 1995 and 2007. Multivariate logistic regression analysis was used to identify factors associated with hospital mortality. The Acute Physiology and Chronic Health Evaluation (APACHE) II score, Simplified Acute Physiology Score (SAPS) II and ICNARC score were evaluated for discrimination (the ability to distinguish survivors from nonsurvivors); and the APACHE II, SAPS II and ICNARC mortality probabilities were evaluated for calibration (the accuracy of the estimated probability of survival).
There were 7,689 eligible admissions. ICU mortality was 43.1% (3,312 deaths) and acute hospital mortality was 59.2% (4,239 deaths). ICU and hospital mortality increased with the number of organ failures on admission. Admission factors associated with an increased risk of death were bone marrow transplant, Hodgkin's lymphoma, severe sepsis, age, length of hospital stay prior to intensive care admission, tachycardia, low systolic blood pressure, tachypnoea, low Glasgow Coma Score, sedation, PaO2:FiO2, acidaemia, alkalaemia, oliguria, hyponatraemia, hypernatraemia, low haematocrit, and uraemia. The ICNARC model had the best discrimination of the three scores analysed, as assessed by the area under the receiver operating characteristic curve of 0.78, but all scores were poorly calibrated. APACHE II had the highest accuracy at predicting hospital mortality, with a standardised mortality ratio of 1.01. SAPS II and the ICNARC score both underestimated hospital mortality.
Increased hospital mortality is associated with the length of hospital stay prior to ICU admission and with severe sepsis, suggesting that, if appropriate, such patients should be treated aggressively with early ICU admission. A low haematocrit was associated with higher mortality and this relationship requires further investigation. The severity-of-illness scores assessed in this study had reasonable discriminative power, but none showed good calibration.
Patients with haematological malignancies can now expect a greater chance of curative treatment and longer survival times than ever before due to bone marrow (haemopoeitic stem cell) transplantation and chemotherapy. Yet these potentially life-saving treatments may also cause life-threatening complications [1–5]. Seven per cent of patients admitted to hospital with haematological malignancy become critically ill [6], and these patients have a higher mortality than the general intensive care population [7–10].
Factors found to influence survival of patients admitted to the intensive care unit (ICU) with a haematological malignancy include the severity of the acute illness [11–13], invasive mechanical ventilation (IMV) [5, 14, 15], and previous haemopoeitic stem cell transplant (HSCT) [11, 12]. Neutropaenia [12, 16] and the nature and progress of the haematological malignancy [9] may also predict a poor outcome. Probably due to the small number of patients included, however, not all of the factors mentioned above were predictive of adverse outcome in subsequent studies.
Models that incorporate the effect of chronic health and specific diagnoses on mortality, such as the Acute Physiology and Chronic Health Evaluation II (APACHE II) score and the Simplified Acute Physiology Score II (SAPS II), are able to discriminate survivors from nonsurvivors [12, 16, 17]. Despite this ability, severity-of-illness scores significantly underestimate actual mortality in this population of patients [6, 8, 11]. The Intensive Care National Audit and Research Centre (ICNARC) model was developed in 2007 using data from 216,626 admissions in the ICNARC database [18], and was shown to be superior to existing risk prediction models. The ICNARC model assesses acute physiology in addition to age, source of admission, diagnostic category and cardiopulmonary resuscitation before admission. Unlike the APACHE II and SAPS II models, the ICNARC model does not exclude patients with specific diagnoses, like burns. The model, however, has never been assessed for its accuracy in haematological malignancy patients. The accuracy of a severity-of-illness score can be assessed by the model's discrimination between survivors and nonsurvivors (how well the model predicts the correct outcome) and by assessing calibration (how well the model tracks outcomes across the range of possible scores).
The present study examines the outcomes of haematological malignancy patients admitted to general adult ICUs in England, Wales and Northern Ireland, identified using a high-quality clinical database. We used multivariable logistic regression analysis to identify factors on admission that are associated with acute hospital mortality. We evaluated the discrimination and calibration of the APACHE II, SAPS II and ICNARC models in these patients.
Materials and methods
Case Mix Programme Database
The Case Mix Programme is the national comparative audit of adult, general critical care units (ICUs and combined intensive care and high-dependency units) in England, Wales and Northern Ireland, coordinated by the ICNARC. The Case Mix Programme Database (CMPD) contains pooled case mix and outcome data on consecutive admissions to units participating in the Case Mix Programme, which have undergone extensive local and central validation. The data are collected to precise rules and definitions by trained data collectors. Details of the data collection and validation have been reported previously [19]. The CMPD has been independently assessed to be of high quality [20]. Support for the collection and use of patient-identifiable data without consent in the Case Mix Programme has to be obtained under Section 251 of the NHS Act 2006 (approval number PIAG 2–10(f)/2005), and therefore ethical approval was not required for the present study. Data were extracted from the CMPD for 514,918 admissions from 178 ICUs, covering the period December 1995 to March 2007.
Selection of cases
Admissions in the CMPD with haematological malignancy can be identified from the primary, secondary and ultimate primary reason for admission fields, from either of two other conditions relevant to the admission, and from the past medical history. The reasons for admission and other conditions relevant to the admission are coded using the ICNARC Coding Method [21], a hierarchical method specifically designed for coding reasons for admission to the ICU.
Admissions with any of the following ICNARC Coding Method conditions as the primary, secondary or ultimate primary reason for admission or other conditions relevant to the admission were included in the analysis: bone marrow transplant, graft versus host disease, acute lymphoblastic leukaemia, acute myeloblastic leukaemia, chronic lymphocytic leukaemia, chronic myelogenous leukaemia, Hodgkin's lymphoma, non-Hodgkin's lymphoma or myeloma. All admissions that do not satisfy these criteria but have any of the following conditions in their past medical history were also included in the analysis: acute myelogenous leukaemia or lymphocytic leukaemia or multiple myeloma; chronic myelogenous leukaemia or chronic lymphocytic leukaemia; or lymphoma. The conditions specified above must have been present in the 6 months prior to admission to the unit in order to be included in the CMPD.
An algorithm was derived to divide these admissions into categories based on their reason for admission. This algorithm was required because it is possible for each admission to have more than one condition coded. The following hierarchy of reason for admission was therefore used: acute lymphoblastic leukaemia or acute myeloblastic leukaemia or myeloma; chronic lymphocytic leukaemia or chronic myelogenous leukaemia; Hodgkin's lymphoma or non-Hodgkin's lymphoma; and bone marrow transplant or graft versus host disease.
Each of the reasons for admission or each of the conditions relevant to the admission was searched in turn for the conditions in the order defined above and the admission was allocated to the condition that was identified first. The primary reason for admission was searched first, followed by the secondary reason, the ultimate reason and finally the other conditions relevant to the patient's admission.
It is not possible to identify treatments received by the admitted patient using the ICNARC Coding Method, so admissions with the conditions bone marrow transplant or graft versus host disease were considered to have received HSCT.
Data were extracted on the case mix, on the outcome and on the activity as defined below.
Case mix
Organ system failures were identified from physiological data according to the definitions of Knaus and colleagues [22]. Severity of illness was measured by the APACHE II Acute Physiology Score, the APACHE II score [22], the ICNARC physiology score [18], the SAPS II score [23] and the number of organ system failures. Both the APACHE II Acute Physiology Score and the ICNARC physiology score encompass a weighting for acute physiology (defined by derangement from the normal range for 12 physiological variables in the first 24 hours following admission to the ICU). The APACHE II score and the SAPS II additionally encompass a weighting for age and for a past medical history of specified conditions.
Patients who were ventilated at any time during the first 24 hours in the ICU include both patients who were receiving mechanical ventilation on admission to the ICU and those for which ventilation was initiated at any time during the first 24 hours of their stay.
Patients were defined as having severe sepsis if they met at least three of the four systemic inflammatory response syndrome criteria, if they had evidence of infection, and by the presence of at least one organ dysfunction during the first 24 hours following admission to the ICU. Physiological definitions of the systemic inflammatory response syndrome criteria and organ dysfunctions were matched as closely as possible to those used in the PROWESS trial, as has been reported previously [24].
Survival data were extracted at discharge from the Case Mix Programme unit and at ultimate discharge from the acute hospital.
Readmissions to the unit within the same hospital stay were identified from the postcode, date of birth and sex of the patient, and were confirmed by the participating units.
A statistical analysis plan was agreed a priori. The analyses performed were as follows.
Descriptive statistics
The case mix, outcome and activity were described for all haematological malignancy admissions.
Prognostic modelling in haematological malignancies
The effect of case mix factors on acute hospital mortality was assessed by multivariable logistic regression modelling for the admissions that were identified as having a haematological malignancy. The past medical history as recorded in the CMPD does not distinguish between individual haematological diagnoses, but groups together the following diagnoses: acute myelogenous leukaemia or lymphocytic leukaemia or multiple myeloma; chronic lymphocytic leukaemia or chronic myelogenous leukaemia; and Hodgkin's lymphoma or non-Hodgkin's lymphoma. To assess the effect of specific haematological diagnoses on outcome, therefore, only admissions with a haematological diagnosis as the primary, secondary or ultimate reason for admission were included in the regression analysis of diagnosis on outcome.
For all physiology variables, all measurements were from the first 24 hours following ICU admission. The variables entered into the model, selected a priori, were as follows: age; sex; haematological diagnosis on admission (only admissions with a haematological diagnosis as the primary, secondary or ultimate reason for admission were included in this analysis); highest central temperature (or noncentral temperature + 1°C if no central temperature was recorded); lowest systolic blood pressure; highest heart rate; lowest respiratory rate; PaO2:FiO2 (with additional weightings for patients who were ventilated at any time during the first 24 hours of their admission to the unit); lowest arterial pH; serum sodium (most extreme value from the normal range); serum potassium (most extreme value from the normal range); serum urea (most extreme value from the normal range); serum creatinine (most extreme value from the normal range); urine output in the first 24 hours of admission to the unit (if the length of stay in the unit was less than 24 hours the urine output during their stay is scaled up to give the equivalent urine output in 24 hours); haematocrit (most extreme value from the normal range; if there were no haematocrit measurements available then three times the recorded haemoglobin values were used instead); lowest white blood cell count; lowest total Glasgow Coma Score (GCS); IMV; severe sepsis; cardiopulmonary resuscitation within 24 hours prior to admission; and acute hospital length of stay before ICU admission in days.
Continuous variables were divided into categories for modelling, except for age and hospital length of stay before ICU admission, which were assumed to have a linear effect on the log odds.
Evaluation of APACHE II, SAPS II and ICNARC models in haematological malignancy admissions
The SAPS II, the APACHE II score and the ICNARC physiology score were evaluated for discrimination (the ability of the model to distinguish survivors from nonsurvivors), and the APACHE II mortality probability (using coefficients from the model that has been calibrated using the CMPD [25]), the ICNARC model mortality probability and the SAPS II mortality probability were evaluated for discrimination and calibration (the accuracy of the estimated probability of survival). The APACHE II and ICNARC models are used to predict the probability of ultimate acute hospital mortality. The SAPS II model is used to predict the probability of mortality within the same hospital that houses the ICU where the admission occurred.
Discrimination was assessed by the area under the receiver operating characteristic curve (AUROC) [26]. Calibration was assessed by the standardised mortality ratio (SMR), the Hosmer–Lemeshow C statistic [27] and Cox's regression calibration [28].
The AUROC (also called the concordance statistic) measures the probability that a randomly selected nonsurvivor has a higher prediction than a randomly selected survivor. A value of 0.5 indicates no discrimination, and a value of 1 indicates perfect discrimination. Values higher than 0.8 are generally considered to demonstrate good discrimination, values between 0.6 and 0.8 are considered moderate, and values lower than 0.6 are considered poor.
The SMR can be used to compare the discrepancy between observed and expected deaths between groups. The ratio is calculated as the number of observed deaths divided by the number of deaths predicted by the model.
The Hosmer–Lemeshow test divides the data into 10 groups and compares the observed mortality in these groups with the expected mortality predicted by the model. The C statistic is a chi-squared statistic for testing the hypothesis of perfect calibration (observed mortality = expected mortality). A significant result indicates that calibration is not perfect [27].
If the model is perfectly calibrated then the slope will be 1 and the intercept will be 0; that is, true log odds = predicted log odds. This is tested with a likelihood ratio chi-squared test, with a significant result indicating lack of calibration.
Readmissions within the same acute hospital stay were excluded from all analyses of acute hospital mortality. Patients who stayed less than 8 hours in the ICU were excluded from the calculation of APACHE II scores and probabilities. In addition, patients transferred from another ICU and admissions following coronary artery bypass graft or for primary burns were excluded from the calculation of APACHE II and SAPS II probabilities. In addition, patients were excluded from the calculation of SAPS II probability if no respiratory rates were recorded or no measurements from blood gases were taken. There are no exclusions from the ICNARC model.
All analyses were performed using Stata 9.2 (Stata Corporation, College Station, TX, USA).
Case mix
Case mix for admissions with haematological malignancy
All admissions (n = 7,689)
Age, mean (SD)
57.5 (17.6)
Male, n (%)
4,638 (60.3)
APACHE II Acute Physiology Score, mean (SD)
17.1 (7.4)
APACHE II score, mean (SD)
24.4 (7.9)
ICNARC physiology score, mean (SD)
23.7 (11.4)
Number of organ system failures, mean (SD)
1.5 (1.2)
Ventilated at any time during the first 24 hours in the ICU, n (%)
4,244 (55.4)
Severe sepsis, n (%)
4,177 (54.3)
Lowest platelet count (× 109/l), median (IQR)
74 (31 to 162)
Lowest white blood cell count (× 109/l), median (IQR)
6.7 (2.1 to 14.0)
Mortality, n (%)
3,312 (43.1)
4,239 (59.2)
Unit length of stay (days), median (IQR)
2.5 (1.0 to 5.9)
2.2 (0.7 to 6.3)
2.3 (0.9 to 6.1)
Hospital length of stay (days)a, median (IQR)
27 (14 to 50)
14 (5 to 29)
19 (9 to 38)
Transferred in from another ICU, n (%)
166 (2.2)
Readmission within the same hospital stay, n (%)
449 (5.8)
Hospital mortality by number of organ system failures, mortality (95% CI)
0 organ failures
33.8 (31.4 to 36.2)
1 organ failure
50.3 (48.3 to 52.4)
2 organ failures
68.3 (66.1 to 70.4)
3 organ failures
83.9 (81.5 to 86.1)
4 organ failures
92.3 (89.3 to 94.6)
5 organ failures
98.8 (93.7 to 99.9)
Thrombocytopaenia was present in 4,745 (61.7%) patients, with a median lowest recorded platelet count of 74 × 109/l. Two thousand and twenty-nine (26.4%) patients were leukopaenic on admission.
Case mix for admissions with haematological malignancy by diagnostic category
AML (n = 622)
ALL (n = 272)
CMLL (n = 310)
Age, mean (SD)
49.8 (16.8)
33.5 (20.1)
61.7 (16.1)
Male, n (%)
331 (53.2)
143 (52.6)
205 (66.1)
APACHE II Acute Physiology Score, mean (SD)
20.1 (6.9)
18.6 (6.9)
17.2 (6.9)
APACHE II score, mean (SD)
26.3 (7.6)
23.8 (7.2)
24.9 (7.6)
ICNARC physiology score, mean (SD)
26.5 (11.1)
24.1 (11.2)
23.7 (11.4)
Number of organ system failures, mean (SD)
1.9 (1.2)
1.7 (1.1)
1.5 (1.1)
Mechanically ventilated at any time during first 24 hours in the ICU, n (%)
329 (53.1)
129 (47.6)
165 (53.4)
Severe sepsis, n (%)
284 (45.7)
121 (44.5)
137 (44.2)
Lowest platelet count (× 109/l), median (IQR)
26 (13 to 51)
34 (19 to 62)
61 (34 to 121)
Lowest white blood cell count (× 109/l), median (IQR)
2.3 (0.2 to 16.1)
1.9 (0.2 to 6.8)
10.3 (3.1 to 34.6)
Mortality, n (%)
341 (54.8)
116 (42.7)
126 (40.7)
Acute hospitala
398 (67.3)
141 (55.5)
165 (56.9)
Unit length of stay (days), median (IQR)
Unit survivor
2.8 (1.0 to 5.6)
2.2 (1.0 to 4.9)
2.2 (1.0 to 6.1)
Unit nonsurvivor
1.5 (0.6 to 4.4)
3.4 (1.0 to 10.2)
1.5 (0.4 to 6.3)
1.9 (0.8 to 5.3)
2.6 (1.0 to 6.7)
1.9 (0.8 to 6.1)
Acute hospital length of stay (days)a, median (IQR)
Hospital survivor
38 (27 to 62)
39 (21 to 61)
19 (11 to 41)
Hospital nonsurvivor
15 (3 to 27)
23 (8 to 45)
9 (3 to 24)
22 (8 to 39)
29 (13 to 51)
15 (7 to 33)
Readmission within the same acute hospital stay, n (%)
28 (4.5)
14 (5.2)
18 (5.8)
Acute hospital mortality by number of organ system failures, n (%)
0 organ failures
24 (47.1)
10 (27.8)
16 (29.6)
1 organ failure
99 (54.4)
39 (48.2)
51 (45.5)
2 organ failures
114 (65.9)
49 (60.5)
44 (67.7)
3 organ failures
105 (85.4)
31 (79.5)
38 (90.5)
4 organ failures
47 (88.7)
9 (64.3)
15 (93.8)
5 organ failures
9 (100.0)
3 (100.0)
1 (100.0)
Hodgkin's lymphoma (n = 216)
Non-Hodgkin's lymphoma (n = 1,007)
Bone marrow transplant (n = 156)
Myeloma (n = 397)
Age, mean (SD)
50.7 (17.9)
56.3 (15.8)
40.8 (14.7)
63.0 (11.2)
Male, n (%)
123 (56.9)
611 (60.7)
83 (53.2)
244 (61.5)
APACHE II Acute Physiology Score, mean (SD)
16.7 (7.0)
17.2 (7.4)
18.5 (8.6)
17.1 (7.5)
APACHE II score, mean (SD)
23.2 (7.5)
24.1 (8.0)
23.4 (9.5)
24.3 (7.9)
ICNARC physiology score, mean (SD)
23.2 (11.0)
24.0 (10.9)
24.0 (12.4)
24.2 (10.8)
Number of organ system failures, mean (SD)
1.5 (1.2)
1.5 (1.2)
1.7 (1.3)
1.7 (1.3)
Mechanically ventilated at any time during first 24 hours in the ICU, n (%)
115 (53.5)
528 (52.7)
69 (45.1)
209 (52.8)
Severe sepsis, n (%)
101 (46.8)
414 (41.1)
68 (43.6)
146 (36.8)
Lowest platelet count (× 109/l), median (IQR)
75 (29 to 188)
82 (33 to 184)
37 (19 to 62)
95 (47 to 161)
Lowest white blood cell count (× 109/l), median (IQR)
6.1 (2.1 to 10.5)
6.3 (1.8 to 13.6)
3.7 (0.6 to 8.2)
4.7 (1.9 to 8.8)
Mortality, n (%)
119 (55.1)
492 (48.9)
74 (47.4)
151 (38.0)
Acute hospitala
142 (71.0)
625 (66.2)
93 (65.0)
227 (60.1)
Unit length of stay (days), median (IQR)
Unit survivor
2.7 (1.2 to 5.4)
2.9 (1.3 to 6.7)
2.6 (1.1 to 8.3)
2.9 (1.2 to 8.1)
Unit nonsurvivor
4.5 (1.2 to 8.7)
2.7 (0.9 to 6.4)
3.9 (1.1 to 7.7)
2.8 (0.7 to 7.4)
3.4 (1.2 to 7.2)
2.7 (1.1 to 6.4)
3.0 (1.1 to 7.9)
2.9 (1.1 to 7.7)
Acute hospital length of stay (days)a, median (IQR)
Hospital survivor
24 (12 to 44)
29 (15 to 53)
32 (17 to 63)
34 (18 to 55)
Hospital nonsurvivor
15 (6 to 26)
15 (6 to 30)
28 (13 to 46)
14 (5 to 25)
17 (8 to 35)
19 (9 to 35)
29 (15 to 54)
20 (9 to 38)
Readmission within the same acute hospital stay, n (%)
16 (7.4)
59 (5.9)
11 (7.1)
10 (2.5)
Acute hospital mortality by number of organ system failures, n (%)
0 organ failures
26 (54.2)
90 (43.7)
6 (25.0)
24 (32.4)
1 organ failure
43 (71.7)
182 (60.3)
27 (62.8)
54 (49.1)
2 organ failures
38 (70.4)
197 (75.2)
28 (71.8)
70 (68.0)
3 organ failures
24 (88.9)
102 (87.9)
13 (72.2)
41 (77.4)
4 organ failures
10 (100.0)
41 (93.2)
17 (100.0)
27 (100.0)
5 organ failures
1 (100.0)
13 (92.9)
2 (100.0)
11 (100.0)
Outcome and activity
Overall 3,312 (43.1%) patients died in intensive care and 4,239 (59.2%) died during the hospital admission (Table 1). The median length of stay on the ICU was 2.3 days, survivors having a slightly longer median stay than nonsurvivors. Four hundred and forty-nine (5.8%) patients were readmitted to the ICU during the same hospital admission, and 166 (2.2%) were transferred from another ICU.
Effect of organ failure on survival
As the number of organ failures present on admission increased, there was an increase in hospital mortality (Table 1). If five organ failures were present, the hospital mortality was 98.8%.
Prognostic ability of the SAPS II, APACHE II and ICNARC models
Model fit – comparison of the SAPS II, APACHE II and ICNARC models
SAPS II model
APACHE II model
ICNARC model
Eligible admissions, n (%)
4,973 (64.6)
6,212 (80.7)
7,156 (93.1)
Observed deaths
Expected deaths
1.13 (1.11 to 1.16)
1.01 (0.99–1.03)
1.25 (1.22 to 1.27)
0.74 (0.73 to 0.75)
0.74 (0.73 to 0.76)
0.79 (0.78 to 0.80)
Hosmer–Lemeshow Ca statistic
P value
< 0.001
< 0.001
< 0.001
Cox's calibration regression
Intercept (95% CI)
0.44 (0.38 to 0.51)
0.08 (0.02 to 0.14)
0.62 (0.56 to 0.67)
Slope (95% CI)
0.59 (0.54 to 0.63)
0.80 (0.75 to 0.85)
0.77 (0.73 to 0.81)
P value
< 0.001
< 0.001
< 0.001
Factors associated with acute hospital mortality
Multivariate logistic regression analysis for admissions to critical care units with haematological malignancya
Number of admissions
Number of deaths
Percentage of deaths
Odds ratio (95% CI)
P value
< 0.001
<45 years
1.14 (1.09 to 1.20)
45 to 54 years
Per 10-year increase
55 to 64 years
65 to 74 years
75+ years
1.02 (0.89 to 1.18)
Diagnostic categoryb
< 0.001
Bone marrow transplant
1.88 (1.00 to 3.53)
1.37 (0.86 to 2.20)
1.02 (0.58 to 1.80)
Hodgkin's lymphoma
2.38 (1.30 to 4.36)
Non-Hodgkin's lymphoma
1.46 (0.92 to 2.31)
0.79 (0.47 to 1.35)
Highest central temperature
2.26 (0.97 to 5.29)
36.0 to 38.4°C
38.5 to 40.9°C
0.94 (0.81 to 1.09)
0.70 (0.41 to 1.20)
Lowest systolic blood pressure
< 0.001
<50 mmHg
3.66 (1.93 to 6.96)
50 to 59 mmHg
1.66 (1.09 to 2.54)
60 to 69 mmHg
1.55 (1.15 to 2.08)
70 to 79 mmHg
1.10 (0.88 to 1.37)
80 to 99 mmHg
1.14 (0.97 to 1.34)
100+ mmHg
Highest heart rate
< 0.001
<110 beats/min
110 to 119 beats/min
1.32 (1.06 to 1.64)
120 to 139 beats/min
1.57 (1.30 to 1.90)
140+ beats/min
2.07 (1.67 to 2.55)
Highest respiratory rate, ventilated or nonventilated
< 0.001
<6 breaths/min
1.03 (0.69 to 1.53)
6 to 11 breaths/min
12 to 13 breaths/min
1.36 (1.12 to 1.65)
14 to 24 breaths/min
1.57 (1.31 to 1.87)
25+ breaths/min
2.81 (2.00 to 3.95)
< 0.001
<100 mmHg
2.78 (2.11 to 3.66)
100 to 199 mmHg
1.34 (1.07 to 1.69)
200+ mmHg
<100 mmHg
2.71 (1.45 to 5.06)
100 to 199 mmHg
1.33 (0.72 to 2.45)
200+ mmHg
1.06 (0.58 to 1.95)
Lowest arterial pH
< 0.001
2.25 (1.71 to 2.96)
7.15 to 7.24
1.37 (1.11 to 1.70)
7.25 to 7.32
1.09 (0.91 to 1.30)
7.33 to 7.49
2.20 (1.24 to 3.92)
Serum sodium
<130 mmol/l
2.47 (1.70 to 3.60)
130 to 149 mmol/l
150 to 154 mmol/l
1.85 (1.25 to 2.73)
155 to 159 mmol/l
3.28 (1.45 to 7.40)
160+ mmol/l
1.34 (0.52 to 3.46)
Multivariate logistic regression analysis for admissions to critical care units with haematological malignancya
Number of admissions
Number of deaths
Percentage of deaths
Odds ratio (95% CI)
P value
Serum potassium
<3.0 mmol/l
2.40 (1.02 to 5.67)
3.0 to 3.4 mmol/l
1.29 (0.87 to 1.92)
3.5 to 5.4 mmol/l
5.5 to 5.9 mmol/l
0.93 (0.69 to 1.27)
6.0 to 6.9 mmol/l
1.12 (0.79 to 1.61)
7.0+ mmol/l
0.79 (0.40 to 1.53)
Serum urea
<6.2 mmol/l
1.05 (0.78 to 1.42)
6.2 to 7.1 mmol/l
7.2 to 14.3 mmol/l
1.45 (1.09 to 1.93)
14.4+ mmol/l
2.39 (1.74 to 3.28)
Serum creatinine
<0.6 μmol/l
1.41 (0.94 to 2.13)
0.6 to 1.4 μmol/l
1.5+ μmol/l
0.84 (0.70 to 1.02)
Urine output
< 0.001
<400 ml/day
2.91 (2.23 to 3.79)
400 to 599 ml/day
2.66 (1.76 to 4.00)
600 to 899 ml/day
2.05 (1.53 to 2.75)
900 to 1,499 ml/day
1.58 (1.30 to 1.91)
1,500 to 1,999 ml/day
1.37 (1.13 to 1.66)
2,000+ ml/day
3.22 (0.96 to 10.85)
20 to 29%
4.56 (1.51 to 13.80)
30 to 45%
3.69 (1.22 to 11.13)
46 to 49%
2.13 (0.58 to 7.82)
50 to 59%
1.24 (0.09 to 17.20)
Lowest white blood cell count
<1 × 109/l
1.17 (00.95 to 1.45)
1 to 2 × 109/l
1.15 (0.92 to 1.43)
3 to 14 × 109/l
15 to 39 × 109/l
0.98 (0.80 to 1.20)
40+ × 109/l
1.16 (0.86 to 1.56)
Glasgow Coma Score
< 0.001
3.32 (2.33 to 4.74)
1.58 (0.55 to 4.52)
2.20 (0.85 to 5.73)
1.47 (0.80 to 2.71)
7 to 13
1.80 (1.40 to 2.31)
1.48 (1.11 to 1.98)
1.85 (1.50 to 2.28)
Sedated and paralysed
2.40 (1.51 to 3.82)
Mechanical ventilation
1.53 (0.85 to 2.73)
Severe sepsis
1.29 (1.10 to 1.50)
CPR within 24 hours prior to admission
1.21 (0.84 to 1.74)
Hospital length of stay before ICU admission
< 0.001
0 days
1.02 (1.01 to 1.02)
1 day
(per day)
2 to 4 days
5 to 9 days
10 to 19 days
>20 days
Nineteen factors were found to be associated with acute hospital mortality. Patients with severe sepsis had a higher risk of acute hospital mortality (adjusted odds ratio (OR) = 1.29). There was also an increase in mortality with increasing age, with an adjusted OR of 1.14 for every 10-year increase in age. As the time interval between acute hospital admission and admission to intensive care increased, the acute hospital mortality also increased. Acute hospital mortality was 54.1% in patients immediately admitted to the ICU, compared with 70.8% if admission occurred after 20 days or more in hospital.
Other factors found to be associated with an increased risk of hospital mortality were haematocrit, systolic blood pressure, respiratory rate, heart rate, GCS, sedation, PaO2:, arterial pH, urine output, serum sodium, and serum urea. Of these factors, haematocrit from 20 to 29% (adjusted OR = 4.56), systolic hypotension <50 mmHg (adjusted OR = 3.66), and a GCS of 3 (adjusted OR = 3.32) conferred the highest odds for hospital mortality.
Although IMV within 24 hours of ICU admission was not associated with hospital mortality after adjustment for other prognostic factors, 70.2% of intubated patients died compared with 45.3% of nonintubated patients.
Two thousand eight hundred admissions were included in the subgroup analysis of the effect of diagnosis on outcome. Admission after HSCT (mortality 65%, adjusted OR = 1.88) or admission with a diagnosis of Hodgkin's lymphoma (mortality 71%, adjusted OR = 2.38) were both associated with higher hospital mortality.
The acute hospital mortality of patients with haematological malignancies admitted to adult, general ICUs in England, Wales and Northern Ireland between 1995 and 2007 was 59.2%. Factors present on admission associated with increasing acute hospital mortality included age, length of hospital stay prior to admission and the presence of severe sepsis. Patients with Hodgkin's lymphoma and those who had received HSCT had an increased risk of death.
We compared the performance of the SAPS II, APACHE II and ICNARC models in predicting mortality. The ICNARC model had the best discrimination as assessed by the AUROC, but significantly underestimates mortality; while the APACHE II model does not underestimate mortality for this group of patients, but has slightly less discriminative power than the ICNARC model. None of the models showed good calibration as assessed by the Hosmer–Lemeshow goodness-of-fit test or Cox's calibration regression.
Strengths of the study
The present trial is a large study assessing the outcome of admissions with haematological malignancies to the ICU, including data from 178 different units. The generalisability of our results to similar patient populations is enhanced by the number of units contributing data. The CMPD is recognised to be of high quality, meaning that the data used in this study are reliable.
Limitations of the study
The CMPD was not primarily designed to analyse the outcome of critically ill patients with haematological malignancies, imposing important limitations on the study. Only routinely collected admission data included in the CMPD were available for analysis. Therefore, it was not possible to analyse all of the prognostic factors in haematological malignancy patients, such as neutropaenia, or the type of HSCT received. We could not determine whether patients had received allogeneic or autologous HSCT, or peripheral blood stem cell transplants prior to ICU admission, where the mortality of patients receiving these treatments is known to differ. Although we analysed the effect of leukopaenia on outcome, this is not the same as neutropaenia. The analysis of the effect of haematological diagnosis on outcome was also limited by the grouping of different haematological conditions in the past medical history field of the CMPD. We therefore performed a subgroup analysis on 2,800 admissions where a precise haematological diagnosis could be extracted. We are also unable to analyse the effect of physiology on outcome beyond the first 24 hours of ICU stay, where deteriorating physiology may be useful in making decisions regarding withholding or withdrawing treatment. We are not able to report on long-term follow up for mortality in these admissions.
It is likely that this retrospective study was subject to inclusion bias. Differences in admission policies among the contributing units may have led to the inclusion of data from patients with incurable illness who were certain to die, and to the exclusion of critically ill patients with haematological malignancy who were managed on the ward, of whom there are a large number [6]. Eligible patients may have been omitted, or ineligible patients included. For example, HSCT may be used to treat some solid tumours and autoimmune disorders, as well as haematological malignancies. The proportion of HSCT patients, however, was small (143 out of 7,689 admissions) – the majority of whom would have had a haematological malignancy.
During the time period covered by the present study, several novel therapies for critically ill haematological malignancy patients have been introduced, such as noninvasive ventilation and recombinant colony-stimulating factors. The use of these therapies may have improved the survival of many patients included in this study [29]. In addition, the management of sepsis has been improved by the introduction of the Surviving Sepsis Campaign in 2002. It has been suggested that cancer patients with severe sepsis have a better chance of survival than in the past [30, 31]. Despite this, the unit and hospital mortality rates of patients in this study did not change significantly over time (data not shown). Finally, lead-time bias may have affected the results. Lead-time bias results from patients' physiology improving as they receive therapy usually provided in the ICU while awaiting ICU admission.
Predictive power of the APACHE II, SAPS II and ICNARC models
The SAPS II and APACHE II models have been assessed in small studies of critically ill haematological malignancy patients. The AUROC for SAPS II was found to be 0.765 [32] and 0.78 [12]. Benoit and colleagues found that the SAPS II model had better discrimination than the APACHE II model (AUROC = 0.712) [32]; however, both studies included only small numbers of patients. Both the ICNARC and SAPS II models underestimated actual mortality in this study. Underestimation of mortality in haematological malignancy patients by the SAPS II model has been previously described [6, 11]. The APACHE II model has also been found to underestimate mortality in these patients [8, 11], but we found that the APACHE II model gave the most accurate mortality prediction (Table 3) with an SMR of 1.01.
Effect of organ failure on survival
As the number of organ failures present on admission increased, the hospital mortality also increased; less than 10% of patients with four organ failures survived, and hospital mortality was 98.8% when there were five organ failures present on admission (Tables 1 and 2).
Risk factors for hospital mortality
Risk factors for mortality in patients admitted to intensive care with haematological malignancy
Factors identified that are associated with hospital mortality
Owzcuk and colleagues [16]
High SAPS II, SOFA score or APACHE II score, neutropaenia, hypotension, cardiovascular failure
Yau and colleagues [9]
Progression of underlying malignancy
Massion and colleagues [11]
Respiratory failure, fungal infection, number of organ failures, haemopoeitic stem cell transplant status
Benoit and colleagues [32]
Leukopaenia, use of vasopressors, urea >0.75 g/l
Gordon and colleagues [6]
Hepatic failure, central nervous system failure, SAPS II score >66
Lim and colleagues [39]
Raised bilirubin, inotropic support, more than three organ failures
Lloyd-Thomas and colleagues [8]
High APACHE II score, number of organ failures, mechanical ventilation
Brunet and colleagues [10]
SAPS II score, more than one organ failure
Kroschinsky and colleagues [14]
Haemofiltration, high SAPS II score
Silfvast and colleagues [50]
Maximal SOFA score on admission
Cornet and colleagues [17]
SAPS II and SOFA score over 96 hours
Lamia and colleagues [12]
Severe sepsis or septic shock, vasopressor use, invasive ventilation, neutropaenia, allogeneic haemopoeitic stem cell transplant, high SAPS II, SOFA score, ODIN score or LODS score
Bianchi and colleagues [41]
Mechanical ventilation, neutropaenia, renal failure
Haematological diagnosis
We found that patients diagnosed with Hodgkin's lymphoma had an increased risk of hospital mortality (adjusted OR = 2.38). This is an unexpected finding, since patients with Hodgkin's lymphoma have a relatively good long-term prognosis. Groeger and colleagues found in cancer patients receiving IMV that those with leukaemia had a higher mortality [33]. Massion and colleagues found that acute myeloid leukaemia and non-Hodgkin's lymphoma had a negative effect on 6-month survival [11]. In the present study, patients with acute myeloid leukaemia had a higher mortality than those with acute lymphocytic leukaemia, perhaps partially explained by the difference in mean age between these admissions (Table 2). Patients with chronic lymphocytic leukaemia had the best prognosis in the study by Peters and colleagues [7]. Other researchers, however, have found that the type of haematological malignancy was not predictive for mortality [13, 16].
Bone marrow transplant
Admission after bone marrow transplantation (HSCT) was a risk factor for acute hospital mortality in the present study. The hospital mortality in patients who become critically ill after HSCT is 54 to 67% [1, 34, 35], with higher mortality rates reported in intubated patients [3, 16, 36, 37]. Patients who receive autologous HSCT transplants undergo less intensive preparative regimens and faster marrow engraftment, so a lower mortality would be expected. Khassawneh and colleagues found that the hospital mortality rate in such patients who were intubated was 74% [38]. Indeed, allogeneic HSCT has been identified as a risk factor for mortality [33, 34]. Other studies, however, have found that the type of HSCT has no influence on mortality [3, 35, 39]. Dividing HSCT patients into those receiving autologous and allogeneic transplants is not possible in the present study, as the type of HSCT received is not recorded in the CMPD.
Admission physiology
Tachypnoea, a low PaO2:FiO2 and hypotension were associated with increased hospital mortality. The relationship between respiratory failure and increased risk of mortality has already been demonstrated [11]. Requirement for vasopressors has also been associated with a worse outcome in these patients [12, 32, 39].
In the present study oliguria, hyponatraemia and uraemia correlated with mortality. These abnormalities may result from acute kidney injury, which is strongly associated with mortality in haematological malignancy patients [14, 32].
Arterial pH
Acidaemia was associated with lower survival. Acute kidney injury or high serum lactate may cause acidosis, and both conditions predicted higher mortality in previous studies [1, 14, 32, 40, 41].
Invasive mechanical ventilation
Most studies report a strong relationship between IMV and increased mortality [8, 12, 41]. Using noninvasive ventilation rather than IMV reduces mortality in immunocompromised patients [42, 43]. IMV during the first 24 hours of admission was not associated with an increased risk of mortality in this study, although a large absolute difference in mortality exists between patients who received IMV and those who did not.
Depudyt and colleagues found that IMV within 24 hours of ICU admission was related to a lower mortality rate in haematological malignancy patients with respiratory failure [44]. Considering those patients who had PaO2:FiO2 lower than 200 mmHg in the present study, a similar conclusion may be drawn, as those who were invasively ventilated within 24 hours had lower mortality rates than those who were not. Indeed, we found that severe respiratory failure (PaO2:FiO2 < 100 mmHg) without IMV is associated with increased hospital mortality. This may reflect reluctance to use IMV in such patients, as less than one-third of patients who had a PaO2:FiO2 < 100 mmHg received IMV (Table 5).
We did not find an association between leukopaenia and mortality, although in previous studies leukopaenia was identified as a significant risk factor [8, 32] and leukopaenia is a component of the APACHE II score and the SAPS II. We were unable to assess the effect of neutropaenia on mortality, as this is not a recorded parameter in the CMPD.
Glasgow Coma Score
A low GCS was independently associated with mortality. Gordon and colleagues [6] found that central nervous system failure was associated with higher mortality.
The retrospective nature of the present study should lead to caution in interpreting the factors identified as being associated with mortality. Severe sepsis – together with cardiorespiratory and renal dysfunction – was associated with increased mortality, however, and this implies that early, aggressive treatment aimed at reversing organ dysfunction may improve survival, particularly in those patients with severe sepsis.
We also found that acute hospital mortality was associated with a longer stay in hospital prior to ICU admission. This is probably due to delayed recognition and suboptimal treatment of patients who have become acutely unwell on the ward, suggesting that earlier admission to the ICU may benefit some patients. Groeger and colleagues found a correlation between hospital length of stay prior to ICU admission and mortality in critically ill cancer patients [33, 45, 46], and this has also been found in critically ill patients as a whole [47].
A low haematocrit of between 20% and 45% was associated with higher mortality, compared with admissions with a haematocrit of between 50% and 59. Anaemia has not previously been associated with an increased risk of hospital mortality in critically ill patients with haematological malignancy. Current practice in intensive care patients is to tolerate a fall in haematocrit, excepting certain groups of patients, based on evidence that this practice is not harmful [48]. On the other hand, in the early phase of severe sepsis, targeting a haematocrit of at least 30% is associated with improved survival [49]. In patients with a haematological malignancy a low haematocrit is common, and its causes are multifactorial. The low haematocrit may be chronic (resulting from bone marrow suppression or more aggressive chemotherapy) or acute (secondary to haemorrhage). One interpretation of our results would suggest that if haematology malignancy patients were managed with a higher haematocrit, at least initially, then their mortality may be reduced.
The association between hospital mortality and sedation may be partially explained by confounding with the adverse effect on mortality of mechanical ventilation. The relationship between hospital mortality and anaemia on admission in these patients is surprising given previous evidence of safety in tolerating a low haematocrit in intensive care patients. Further studies should be conducted to refute or confirm this relationship.
The ICU mortality for haematological malignancy patients in this study was 43.1% and the hospital mortality was 59.2%. Admission factors associated with an increased risk of death were severe sepsis, age, bone marrow transplant, Hodgkin's lymphoma, length of hospital stay prior to intensive care admission, tachycardia, systolic blood pressure <70 mmHg, tachypnoea, GCS, sedation, PaO2:FiO2, acidaemia, alkalaemia, oliguria, hyponatraemia, hypernatraemia, low haematocrit, and uraemia. In contrast to previous studies, we did not find that leukopaenia was associated with increased hospital mortality. We did, however, find that a low haematocrit was associated with higher hospital mortality. This finding warrants further investigation in a prospective study.
The ICNARC model had the best discrimination of the three scores analysed, with an AUROC of 0.78, but all scores were poorly calibrated. The APACHE II model had the highest accuracy at predicting hospital mortality, with a SMR of 1.01. The SAPS II and the ICNARC score both underestimated hospital mortality.
Increased hospital mortality is associated with both increasing length of hospital stay prior to ICU admission and severe sepsis, suggesting that, if appropriate, such patients should be admitted to the ICU early and treated aggressively.
Key messages
The ICU mortality for patients with haematological malignancy in this study was 43.1%, and the hospital mortality was 59.2%.
All of the severity-of-illness scores tested showed poor calibration for mortality, underestimating actual mortality when the predicted mortality was low.
Increased hospital mortality is associated with increasing length of hospital stay before ICU admission in patients with haematological malignancy.
Severe sepsis on ICU admission is associated with a poorer outcome in patients with haematological malignancy.
A low haematocrit on admission to the ICU is also associated with a poor outcome in patients with haematological malignancies.
Acute Physiology and Chronic Health Evaluation II
area under the receiver operating characteristic curve
Case Mix Programme Database
Glasgow Coma Score
haemopoeitic stem cell transplant
Intensive Care National Audit and Research Centre
intensive care unit
invasive mechanical ventilation
odds ratio
Simplified Acute Physiology Score II
standardised mortality ratio.
The authors would like to thank all the units contributing data to the CMPD. They would also like to thank Richard Pugh for his comments on the manuscript.
Authors' Affiliations
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- Silfvast T, Pettila V, Ihalainen A, Elonen E: Multiple organ failure and outcome of critically ill patients with haematological malignancy. Acta Anaesthesiol Scand 2003, 47: 301-306. 10.1034/j.1399-6576.2003.00058.xView ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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Re: Live in Mons or Tournai???
Thanks a bunch. More metropol..is what i'm looking for. I was concerned that I would find that in a town the size of Tournai....I figured that Mons, since it had 3 universities...would be a little more 'alive'. I appreciate your reply.
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subset: commoncrawl


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Recent comments
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Last-minute Brooklyn pre-k picks for 4-year-olds
Applications for pre-kindergarten for all children born in 2012 are due March 9. The city says it will guarantee a seat for all 4-year-olds but it doesn't guarantee where! Many of the most popular zoned schools in Brooklyn have room only for children who live in the zone. We've compiled a district by district list of our best bets for schools and programs that may have seats, based on last year's acceptances.
Remember: It's always a good idea to visit yourself. When it comes to your child, you're the expert.
Need more information about districts? Click on our district maps on the homepage.
Watch our video on "What to look for in a pre-kindergarten" and read our tips.
Families can apply to up to 12 programs online at nyc.gov/prek, over the phone at 718-935-2067, or in person at a Family Welcome Center.
Our picks for pre-k; applications due March 9!
Applications for pre-kindergarten for all children born in 2012 are due next Wednesday, March 9 (The Department of Education extended the deadline to apply from March 4.) For those still looking, we can recommend some pre-k programs. [Brooklyn picks are in a separate post.] While some of the most popular programs have many more applicants than seats, these had some space last year and may not be oversubscribed this year. It doesn't hurt to apply, because even if you're not matched in this first application round, your name will be put on a waitlist. Spaces frequently open up, even into the fall.
We've done our best to identify programs we can recommend based on the data available and our school visits. Parents should be sure to visit too: It's a bad sign if a program is unwilling to let you see the classrooms. Watch our video on "What to look for in a pre-kindergarten" and read our tips.
Families can apply to up to 12 programs online at nyc.gov/prek, over the phone at 718-935-2067, or in person at a Family Welcome Center.
Apply now for new middle school programs
Fifth-graders unhappy with their middle school choices now have a few more options. The Department of Education announced several new middle school programs slated to open in September 2016.
Most of the options are not new schools, but rather new dual language programs opening in established middle schools. The one exception is the new Dock Street School for S.T.E.A.M. Studies in DUMBO, Brooklyn.
Applying to a new school will not override students' choices entered on the middle school applications they submitted last December. According to the DOE's website, "students who receive a match from their new schools application will be able to choose between their new schools and main round matches in the spring."
Students eligible to attend a new middle school program can request an application from their elementary school guidance counselor. Non-public school students can pick up an application at a Family Welcome Center. Applications are due by March 1.
Insideschools event: Get the lowdown on pre-k admissions
Applying to pre-kindergarten for fall 2016?
If your child turns 4 this year, he or she is eligible for free pre-kindergarten, either in a public school or at a site run by a community organization. But what is the quality of these programs and how can you choose the one that works best for your family?
Join Clara Hemphill and the staff of Insideschools for a pre-k workshop on Feb. 11 at The New School. Register here.
Parents of 3s and 4s, it's pre-k time!
Did you know all children may attend a free, full-day pre-kindergarten the year they turn 4? The window of time to apply in 2016 is from Jan. 25 to March 4. That's six weeks! Plenty of time to scroll our site and then tour your favorite pre-kindergarten classrooms in person.
Programs are scattered throughout the city: in public schools, charter schools, religious schools, private nursery schools, Head Start programs, child care centers and community organizations. It's a lot to take in. Many are good, some are not-so-good, but most look like lively hubs where 4-years-old can learn through play with blocks, puzzles, sand tables, Legos and toy kitchens.
Where to start?
Take five minutes to watch our video, "What to look for in a pre-kindergarten." Read about one parent's experience applying: "One mom's trek through the pre-k application maze."
Apply to kindergarten by January 20 (new deadline!)
Got a child born in 2011? Get your kindergarten application in by Wednesday, Jan. 20. The original due date of Jan. 15 was extended to give more parents a chance to get their applications in.
Full-day kindergarten is guaranteed—and required—in New York City for all children who turn 5 during the calendar year. Children have the right to attend their zoned school (space permitting) and most do, but you may apply to other schools as well. You may apply to up to 12 schools online, on the telephone or in person at a Department of Education Family Welcome Center. You'll find out in March where your child is accepted.
If you haven't already, pick up an elementary school directory for your borough, neatly broken down by districts, zoned schools and unzoned schools.
Here are answers to some common questions and misconceptions!
What should I do before I apply?
Visit the school! You want to see the school to see if it's a good fit. Watch our short video: "What to look for on a school tour." Check a school's website or call the parent coordinator to see when tours and open houses are scheduled. The DOE lists some tour dates here. Read the school's profile on Insideschools and check out InsideStats. Do teachers recommend the school to parents? What's the average class size? Is bullying a problem? If you're still uncertain of whether it's a good fit, talk to parents on the playground and read the comments on our profile pages.
How many schools should I apply to?
Apply to as many schools as you are interested in. There's no strategic advantage in listing just one school. The key is to rank the schools in the order that you like them. Do not list any schools you are wary about. If you want your child to attend your zoned school, list that first—or only list the zoned school. If you are concerned about overcrowding and being sent to another school, list your next favorite school to ensure that you are not assigned to a school you did not select. Keep in mind that all schools first accommodate their zoned kids before accepting others. (The eight admissions priorities for zoned schools are spelled out in the directories and in the Chancellor's Regulation 101.)
Most schools are able to accept all zoned students and if you are not accepted in the first round, you are automatically placed on a waitlist. In fact, if you list other schools, and do not get an offer from any of them, you will remain on a waitlist of schools you ranked higher than the school where you were placed. Last year some waitlisted families got offers from out-of-zone and out-of-district schools starting in June and continuing into October. If you do your research, remain persistent and are willing to wait, you may end up with several choices.
What if I don't like my zoned school?
Consider unzoned and charter schools as well as other zoned schools in your district. (Three districts have no zoned schools: District 1 on the Lower East Side, District 7 in the South Bronx and District 23 in Brownsville.)
You don't have to apply to your zoned school but keep in mind that if you are not accepted by any other school, you will most likely be assigned to your zoned school. However, you will be waitlisted at the other schools and there is usually lots of movement in the spring as families accept offers to gifted programs, private schools or move. Keep in touch with schools you are interested in to make sure they know you still want a spot.
You can see in the kindergarten directory which schools had space for students outside of the zone last year and which had a waitlist after the first round of admissions; it's not likely to be too different this year unless there has been rezoning.
This admissions season, the DOE is promoting a new pilot program intended to increase diversity in city schools. Seven schools participating in the program will give increased admissions priority to students who qualify for free or reduced lunch, are English language learners or are in the child welfare system. "Students learn from the diverse experiences and cultures of their fellow students, and it's important that our schools match the diversity of our City," Chancellor Carmen Farina said in a DOE press release.
How do I apply to a dual language program?
More than 100 schools offer dual language programs and the list of schools offering programs is growing. In dual language, students receive instruction in both English and another language. Spanish, Mandarin and French are among the most common languages offered but others include Korean, Japanese, Polish, Arabic and Russian. Next fall there will be a German program starting at PS 17 in Williamsburg! You apply directly to the dual language program on your application. The goal for dual language is to have a 50-50 split of native English speakers and native speakers of the other language offered. Zoned students receive preference in admission, but out of zone students who are native speakers of another language may have a chance of admittance, space permitting.
What about gifted and talented programs?
The admissions timeline, and the application, for gifted and talented programs is different than general kindergarten admissions. Families signed up in November for G&T testing in January and February. The results of the tests will not be sent to families until early April. Qualifying students then apply to programs and will find out in late May if they have got a spot.
Even if you are applying to a G&T program for your child, you must still apply to kindergarten by Jan. 15. If your child is later accepted to a G&T program you'll have a choice of the school you were matched with on the application and the G&T program.
What if my child has special education needs?
Children with special needs also go through the general application process; every school is supposed to offer needed special education services, although in practice this doesn't always happen. Watch our video: "Touring schools for your special needs child." If your child needs a wheelchair accessible site, you can note that on the application.
What if I move after the application due date or I miss the deadline?
If you move after you submit your application but before kindergarten offers are made, you may call the Department of Education, or visit a welcome center, to give them your new address. You will not be able to submit a new application at that time but the DOE will most likely assign you to your new zoned school. If you don't like that placement, you can reach out to other schools in the late spring to ask to be placed on a waiting list.
If you miss the deadline for applying, late applications will still be accepted online, in person and over the phone after Jan. 15, almost until letters are sent in mid-March, according to the Enrollment Office, but you will receive your offer later in the spring. Those who wait until later in the spring or summer to apply, will go directly to their zoned school, or school of interest, to register.
How do I apply to a charter school?
You apply to charter schools separately from district schools and most applications are due by April 1, 2016. You can apply to multiple charter schools on a single application. Find the link to the common application on the New York City Charter School Center's website. Applications are also available on school websites or may be handed out in person when you visit the school.
More questions?
The information in the directory is pretty comprehensive and straightforward but if you still have questions, or want to talk to a DOE official in person, call the DOE's Enrollment Office at 718-935-2009 and see the DOE's kindergarten page for more information.
College counselor: How will a failing grade affect admissions?
Q: I failed my geometry class for one grading period, but I am a straight A student for everything else. Is there any way for me to get accepted by a pretty good college?
A: Short answer: Yes.
Longer answer: Sounds like you had a tough time with your math class, but you are a hard-working student and this failure came as a real shock; failing is not what you ordinarily do. And someone is telling you, "Now, you'll never get into a good college!" Take a deep breath. Everyone messes up on something. But if this one grading period's failure is uncharacteristic, and everything else is fine, you will have no problem getting into a ton of colleges. You may run into a problem, however, if this is part of a pattern of weak grades. (As a side note, remember that you still have time to improve your grade before the end of the semester. Ask your teacher for help!)
Report: Schools are more segregated than neighborhoods
by Clara Hemphill and Nicole Mader
In multi-ethnic New York City, why are so many elementary schools segregated by race and class? For years, school officials and researchers have assumed that school segregation merely reflects segregated housing patterns—because most children attend their zoned neighborhood schools.
However, new research by The New School's Center for New York City Affairs demonstrates that school segregation is not always the result of housing patterns. In fact, as these interactive maps show, there are dozens of high-poverty elementary schools that serve mostly black and Latino children that are located in far more racially and economically mixed neighborhoods.
In Harlem, for example, the estimated household income of children enrolled at PS 125 is barely half that of all the households in the school zone, based on median household income estimates from the most recent American Community Survey by the U.S. Census. PS 125's pupils are 84 percent black and Latino; the proportion of black and Latino people living in the school's attendance zone is just 37 percent.
How Insideschools helped Hugo
Hugo was diagnosed with autism at a very young age.
By the end of 8th grade, he was ready to leave a small program for students on the autism spectrum, but he knew he'd still need counseling and other services in high school.
Insideschools helped him narrow his search.
"When you click on the special education tab on the Insideschools website it will tell you the four- and six-year graduation rates, and whether students with special needs are involved in activities," he said. "You can instantly tell if it's good for special education."
With his interest in animation, he liked the look of Academy for Careers in Television and Film. He said it was a "new kind of school that I hardly knew existed."
Hugo was admitted and now he's a freshman at a high school with one of the highest graduation rates for special education students in the city.
Insideschools is the go-to website for information about New York City public schools. Last year alone, more than 1.8 million visitors turned to Insideschools for help choosing the best schools -- and improving schools for all children. We rely on your support. Please click here to make a tax deductible gift today.
A flawed process: Applying to HS for students with disabilities
by Rachel Howard, Lori Podvesker, Albert Martinez and Todd Dorman of INCLUDEnyc
All 8th-graders have a rough time applying to high schools in New York City, but for the 15,000 8th-graders with disabilities—out of 270,000 total students with disabilities—the application process is even harder. Information in the high school directory can be misleading, and parents of children with disabilities don't get much help at fairs or open houses. Families hear the same mantra: "This school will provide students with disabilities the supports and services indicated on their IEPs." Too often, it's just not true.
Students with disabilities, especially those from high-need neighborhoods, are at the highest risk for placement at the city's lowest performing high schools—or at schools that are unprepared to support them. Through our work at INCLUDEnyc, we've seen kids choose underperforming schools over better ones because they were close by; we've seen others apply to schools that they weren't qualified to attend, or that were geographically inaccessible to them. Too many students with disabilities make uninformed choices about high school—and it shows. The graduation rate for students with disabilities is 36.6 percent (about half of the city average), and the dropout rate is especially high during 9th grade.
Students who meet the criteria for one of 13 federally defined education disabilities are legally entitled to an Individualized Education Program, known as an IEP. An IEP outlines the services, supports, and educational strategies that must be provided so the student can learn and graduate ready for a job or college. The IEP is both a legal contract and a working educational map. But the capacity of any school to fulfill a student's program—which is different for every student—is all but ignored in the NYC high school application process.


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Design a logo for an online shop - repost
This project received 43 bids from talented freelancers with an average bid price of $60 AUD.Get free quotes for a project like this
Project Budget$30 - $250 AUD
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Home / beauty / women's fragrances / perfume /
Marc Jacobs
Marc Jacobs Daisy Eau So Fresh EDT Spray 4.2oz
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reviews (0)
shipping & returns
additional info
Product information
A whimsical interpretation of the original Daisy fragrance, this scent is more fruity, more bubbly, more fun! Open the bottle and you'll be transported to a field of sunshine that bursts with the flirty scent of flowers and the cheerful sweetness of fruits. Its light, woody baseinfuses a subtle but sharp glimmer of musk for an unexpected twist of radiance.


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- Details
- Reviews
Kaikoura is famous for whales and dolphins and arguably one of the world's most exciting arenas for ocean going birds. This full day tour accompanies the Kaikoura Whale Watch Tours from Christchurch. Within close proximity of the beautiful Kaikoura Peninsula, see a considerable array of albatross, petrels, shearwaters, terns, shags and gulls.
- Instant Confirmation
- Close encounter with wildlife
- Informative, friendly and professional guide
- Free hotel pickup and drop-off included
Kaikoura has one of the largest number of different types of seabirds within a small area than anywhere along the New Zealand coastlines. On your arrival in Kaikoura you may enjoy either an early lunch or have free time to explore Kaikoura before being transferred to Ocean Wings Albatross Encounter. Experience the sensation of getting close to the mighty albatross, one of the world's largest flight birds.
There will also be the opportunity during the day to visit a seal colony where fur seals may be viewed at close quarters. This stop provides a great photo opportunity.
Schedule details
Select a month to view a calendar of availability and departure details.
Hotel pickups commence prior to this time, you must contact the local service provider to verify your exact pickup time.
Pricing information
Click the link below to check pricing & availability on your preferred travel date. Our pricing is constantly updated to ensure you always receive the lowest price possible.
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Pricing information
Kaikoura Albatross Encounter Tour from Christchurch
- Transport by air-conditioned coach
- Hotel pickup and drop-off
- Albatross Encounter and seal colony visit
- Food and drinks
- Gratuities (optional)
- Confirmation will be received at time of booking
Cancellation Policy
If you cancel between 3 and 6 day(s) in advance of the scheduled departure, there is a 50 percent cancellation fee.
If you cancel within 2 day(s) of the scheduled departure, there is a 100 percent cancellation fee.
Traveler Reviews
Reviewed by: mana, March 2013
we saw a male Sperm whale,it's awesome!!


text:
Newegg.com - A great place to buy computers, computer parts, electronics, software, accessories, and DVDs online. With great prices, fast shipping, and top-rated customer service - once you know, you Newegg.
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This review is from: CyberpowerPC Desktop PC Gamer Ultra 2081 Phenom II X6 1090T (3.2 GHz) 8 GB DDR3 1 TB HDD AMD Radeon HD 6770 (1 GB) Windows 7 Home Premium 64-bit
Pros: powerful on a budget. bf3 runs smooth on my 42' sharp and this machine.
Cons: owned this machine a couple of months now and it shuts off at random... thinking power supply... glad i have the two year warranty just made the call today. said they would call me back... called at 8 am cali time.. hope they get me back to rockin' :'(
Other Thoughts: waiting on techsupport.READ FULL REVIEW


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Mark Berry reports on Dr. Gibson's introduction and Dr. Whittemore's keynote speech, at the 11th Invest in ME International ME Conference in London.
Discuss the article on the Forums.
XMRV - testing urine
Discussion in 'XMRV Testing, Treatment and Transmission' started by glenp, Jun 13, 2010.
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- 1[transitive, intransitive] stew (something) to cook something slowly, or allow something to cook slowly, in liquid in a closed dish stewed apples The meat needs to stew for two hours. see also stewed See related entries: Ways of cooking
- 2[intransitive] (+ adv./prep.) to think or worry about something I've been stewing over the problem for a while. Leave him to stew. Word Origin Middle English (in the sense 'cauldron'): from Old French estuve (related to estuver
BrE BrE//stjuː//; NAmE NAmE//stuː//Verb Forms present simple I / you / we / they stew
BrE BrE//stjuː//; NAmE NAmE//stuː//he / she / it stews
BrE BrE//stjuːz//; NAmE NAmE//stuːz//past simple stewed
BrE BrE//stjuːd//; NAmE NAmE//stuːd//past participle stewed
BrE BrE//stjuːd//; NAmE NAmE//stuːd//-ing form stewing
BrE BrE//ˈstjuːɪŋ//; NAmE NAmE//ˈstuːɪŋ//Ways of cooking
(informal) to leave somebody to worry and suffer the unpleasant effects of their own actions
let somebody stew in their own juicejump to other results
Check pronunciation: stew


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Elite Image Remanufactured Lexmark 18Y0144 Ink CartridgeInk Cartridges & Printheads
Compatible Lexmark Ink Cartridge - 480 Page Yield - Black - View Complete Details
Product Number: ELI75487
In Stock - Hurry, only 81 left.
Estimated Delivery - 1 business day(s) - Tue 2/28 2 business days - Tue 2/28
Shipping - This item is eligible for Free Shipping on orders over $45
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Made in America
This product was manufactured in the United States.
Not Returnable
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Elite Image Remanufactured Lexmark 18Y0144 Ink Cartridge - Remanufactured ink cartridge is designed for use with Lexmark X4850, X4875, X4950, X4975, X6570, X6575, X7550, X7675, X9350, X9575 and Z1520. Premium cartridge yields approximately 480 pages. Elite Image is ISO certified.
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text:
Speedy Brioche
|Active dry yeast
|1⁄2 Ounce (1 package)
|Warm water
|1⁄4 Cup (4 tbs) (105 to 115 Degree F)
|Buttermilk/Sour milk
|1⁄4 Cup (4 tbs)
|3⁄4 Cup (12 tbs), softened
|1⁄3 Cup (5.33 tbs)
|3 Teaspoon
|Baking powder
|2 Teaspoon
|All purpose flour/Unbleached flour
|5 1⁄2 Cup (88 tbs) (Pillsbury's Best)
(Lightly spoon flour into measuring cup; level off.) Soften yeast in warm water in large bowl.
Add buttermilk, butter, sugar, salt, baking powder, eggs and 2 1/2 cups flour.
Beat 2 minutes at medium speed.
By hand, stir in remaining flour.
On well floured surface, knead dough until smooth and elastic, about 5 minutes.
Grease (not oil) 24 brioche or medium muffin cups.
Divide dough into 24 equal parts.
Remove about 1/5 of dough from each.
Shape all into smooth balls.
Place larger balls in pans.
With finger, make a deep indentation in center of large balls; place smaller balls in indentation.
Cover; let rise in warm place until light and doubled in size, 30 to 45 minutes.
Preheat oven to 350°F.
Bake rolls 25 to 30 minutes until golden brown.
Remove from pans and brush with butter.
Serve warm.
Rate It
Nutrition Rank
Nutrition Facts
Serving size
Calories 2093 Calories from Fat 679
% Daily Value*
Total Fat 77 g118.9%
Saturated Fat 45.5 g227.3%
Trans Fat 0 g
Cholesterol 392.9 mg131%
Sodium 3392.7 mg141.4%
Total Carbohydrates 301 g100.4%
Dietary Fiber 10.8 g43.1%
Sugars 34.7 g
Protein 46 g92.7%
Vitamin A 47% Vitamin C 0.04%
Calcium 47.4% Iron 103.6%
*Based on a 2000 Calorie diet


text:
SEARCH KEYWORD -- Open source
Social media sharing codes
Social media is becoming a very important traffic source to one website. We can see social media share buttons or links in most websites ranging from news website to personal blogs. It is also a very important optimization area where many SEO experts recommend. There are many social medias we can share our links to such as Facebook and Twitter. Most of these website provide share button for us to easily integrate them into our websites, but these buttons usually have default styles(fixed size, f...
Social media,Share button,Cutomize 2013-07-18 23:12:45
"Native vs Web" Is Total Bullshit
The web is dead. HTML5 is the be-all end-all of the future. Users are spending more time on apps and less time on the web. You can do anything on the web that you can in a native app. Yawn. Here's how I feel whenever I hear/read anything about the overplayed "Native Versus Web" argument: It's not an either-or decision Why aren't we still arguing over "Print vs Digital"? Well, because (most) people understand that each medium has its place in this world, and as it turns out, ...
Web app,Native app,Comparison 2012-02-24 05:30:03
Two things I don't like about Hacker News
Hacker News is a very famous IT information hub. We can find many useful links about the latest IT news and fantastic technology demos. But there are two things I don't like about Hacker News. Maybe some of you also have the same feelings.1. About the more link. Every time we click the more link to go to next page, there will be a unique key generated to produce the new page. It is a good security mechanism. Also it may increase pages views as we need to read page by page but can...
Hacker news,More link,Submission,Security 2012-02-28 11:55:37
Do things, tell people.
These are the only things you need to do to be successful*. You can get away with just doing one of the two, but that's rare, and usually someone else is doing the other part for you. If you you don't have any marketable skills, learn some. It's the future. We have Khan Academy and Wikipedia and Codecademy and almost the entire world's collective knowledge at your fingertips. Use it. Then make something that you can talk about. Make something cool. Something interesting. Spend time on it. Go ...
Tihings,Promote,Product,Open source 2012-02-21 05:28:39
XMLHttpRequest Level 2 user guide
XMLHttpRequest, progress, upload, binary data 2012-09-19 11:51:50
Run executable jar on double click on Windows
Normally after installing Java, there will be an association between .jar and the javaw.exe. This enables the executable jar to be opened on double click. You can check the association by going to Control Panel -> Programs -> Default Programs -> Associate a file type or protocol with a program. The default program of a file type can be changed in this dialog. However sometimes there are cases where the file association for .jar may be altered after a third party application instal...
Android Tutorial: Creating and Using an SD Card in the Emulator
In a previous post, I mentioned how user-friendly Android is for developers. There's extensive documentation and information on the architecture, the different components and best practices. However, the documentation has a few blind spots. Many of the tools have little documentation and no usage examples. The information is there, it's just hidden behind a few layers of Android theory.So I'm going to try and document a few of the basic things that you'll probably need to know to st...
Android,Emulator,SDCard,Load,Create 2011-04-13 12:08:41
Why I Still Use Emacs
At school, I'm known as the Emacs guy; when people have questions about configuring Emacs or making it work a certain way, they often come and ask me. Sometimes, some people ask me why use Emacs at all? Isn't it a really old editor and aren't Eclipse or Visual Studio much better? I mean, they don't have weird key bindings and have intellisense, that's surely better for a programmer, right? I will attempt in this post to explain some of the reasons why I still cling to Emacs. Believe me...
Linux,Emacs,Editor,Advantage,IDE 2012-02-20 05:30:41
Google has done more for the world with ngrams
Data is valuable asset for a company in the Internet world. With data of users, a company can gain lots of benefits. They can push specified ads to users by analyzing user behaviors, they can even sell the data to third parties. Data is very important for a company's success, so some companies will keep their data secret in order to gain advantages over competitors. However, Google seems do it in another way. Google shared their ngrams text corpus publicly, which basically contains valuable info...
Ngram,NLP,Data 2013-12-12 07:56:02
A simple way to remove the small arrow on on desktop application shortcut
Maybe many of us will see a small arrow on desktop application shortcut after we install the application on Windows. Some may like it but some people may think it doesn't look beautiful enough. We may need to remove these small arrows somehow the desktop can be clean. So how? Many people may use a third party software to remove the small arrows, then they must go to download the software and install them. But do we necessary do this in order to remove the small arrow?The answer is no. Here I ...
Small Arrow,Shortcut,Desktop,Application,Windows 2014-10-25 08:39:58
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text:
Publisher's Description+
What's new in this version:
Welcome to Skype for iPhone. We're constantly working to make Skype better for you. Here's what's new: * Spread a little extra holiday cheer. Share a personalized holiday video message with your loved ones. Tap on the snowflake button next to the Skype logo to get started. * Notifications are now removed from the Notification Center when the Skype app is launched - decluttering is a good thing. * Have you ever accidentally closed the app during a group call and were unable to join? Now you can e... See all new features »


text:
Your seedling is absolutely scrumptious!!!!!!! The form is exquisite,
the ruffles delightful. The closed standards...superb! And I love the
color. That bushy pink toned beard is further highlighted by the white
ray cascading down the falls. Hope it has good branching, and bud
Keep up the good work!
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À propos
Youth Employment Service (YES) is a non profit and non governmental Organisation founded on the 25th of November 2005 and legalised on the 1s t of December 2006 under the Ministry of Territorial Administration and Decentralisation (MINATD) with registration number 001265/ADR/JO6/APPA. YES main objective is to fight poverty as outlined in the United Nations Millennium Development Goals (MDGs) 2015 by reducing the rate of youth unemployment. This is done through the following approaches as outlined below: Career guidance This includes career planning, management and diversity. The rate of youth unemployment is alarming because of our poor educational system. Youths are not well guided on what to do at the elementary stage. Thus, they are bound to study or pursue their education blindly. That is why you find lots of graduates and undergraduates rooming the streets. YES seeks to guide and direct youth on this domain. Hence reduce youth unemployment. This is done through career courses and workshops. Training; this is the root cause of youth unemployment .Many youths are rooming the streets because they do not have the necessary skills or professional training. As its major target The YES seeks to empower or train youths especially those that are underprivileged after guiding them. Placement; after a good career guidance and training, youths who are unable to create their own small businesses are placed to work in private institutions. YES also offers courses on leadership, entrepreneurship, so as to enable youths become better leaders and know how to manage their own activities after creating their own small businesses in their domain of specialisation. YES assists youths in the creation of personal enterprises this implies, job creation to gain self-employment. This is through YES Mini Grants Awards. YES organises Awards for employers entitled YES Employers Awards. This is done in order to boost employment in the private sector.
Date de fondation : 2005
Adresse email : Identifiez-vous pour voir ces adresses email
Site(s) web:
Numéro de téléphone : +237 77055414 / +237 2223-5509
Adresse :
Rue Avenue Germaine ESSOS, YAOUNDE, Centre, 8203, Cameroun