{'fraction_non_alphanumeric': 0.0355848191166679, 'fraction_numerical': 0.020418731967152475, 'mean_word_length': 5.175422567382366, 'pattern_counts': {'":': 0, '<': 12, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Glomerular Hyperfiltration and Renal Disease Progression in Type 2 Diabetes

OBJECTIVE To describe the prevalence and determinants of hyperfiltration (glomerular filtration rate [GFR] ≥120 mL/min/1.73 m2), GFR decline, and nephropathy onset or progression in type 2 diabetic patients with normo- or microalbuminuria. RESEARCH DESIGN AND METHODS We longitudinally studied 600 hypertensive type 2 diabetic patients with albuminuria <200 μg/min and who were retrieved from two randomized trials testing the renal effect of trandolapril and delapril. Target blood pressure (BP) was <120/80 mmHg, and HbA1c was <7%. GFR, albuminuria, and glucose disposal rate (GDR) were centrally measured by iohexol plasma clearance, nephelometry in three consecutive overnight urine collections, and hyperinsulinemic euglycemic clamp, respectively. RESULTS Over a median (range) follow-up of 4.0 (1.7–8.1) years, GFR declined by 3.37 (5.71–1.31) mL/min/1.73 m2 per year. GFR change was bimodal over time: a larger reduction at 6 months significantly predicted slower subsequent decline (coefficient: −0.0054; SE: 0.0009), particularly among hyperfiltering patients. A total of 90 subjects (15%) were hyperfiltering at inclusion, and 11 of 47 (23.4%) patients with persistent hyperfiltration progressed to micro- or macroalbuminuria versus 53 (10.6%) of the 502 who had their hyperfiltration ameliorated at 6 months or were nonhyperfiltering since inclusion (hazard ratio 2.16 [95% CI 1.13–4.14]). Amelioration of hyperfiltration was independent of baseline characteristics or ACE inhibition. It was significantly associated with improved BP and metabolic control, amelioration of GDR, and slower long-term GFR decline on follow-up. CONCLUSIONS Despite intensified treatment, patients with type 2 diabetes have a fast GFR decline. Hyperfiltration affects a subgroup of patients and may contribute to renal function loss and nephropathy onset or progression. Whether amelioration of hyperfiltration is renoprotective is worth investigating.

This cohort study included subjects from two randomized, double-blind, placebo-controlled clinical trials, BENEDICT-B (10) and DEMAND (11) both designed to evaluate the effect of ACE inhibitor therapy on onset and progression of nephropathy in subjects with type 2 diabetes. The two study populations were considered together since they were selected, monitored and treated according to similar pre-defined guidelines. Major similarities included: 1. Selection criteria: i. type 2 diabetes (WHO criteria), ii. arterial hypertension (systolic >130 mmHg and/or diastolic BP >85 mmHg, or concomitant antihypertensive therapy) iii. normo-or micro-albuminuria [urinary albumin excretion (UAE) in at least two of three consecutive overnight urine collections <20µg/min or ≥20 and <200µg/min, respectively], iv. serum creatinine <1.5mg/dl and HbA 1C <11%, 2. Enrollment period (from February 10, 1998to June 22, 2005 and follow-up duration (up to progression to an end-point or completion of pre-planned treatment period by the last randomized patient) 3. Treatment targets (systolic/diastolic BP<120/80 mmHg and HbA 1C <7%) 4. Clinical outcomes, including six monthly measurements of GFR and albuminuria by gold-standard procedures 5. Approaches used to assess the main outcomes: i. GFR decline by linear regression analysis ii. progression to persistent microalbuminuria or macroalbuminuria defined as at least two out of three consecutive overnight UAE >20 µg/min or >200 µg/min, respectively, confirmed in two consecutive visits two months apart 6. Efficacy and safety variables recorded according to the same timetable by case record forms and databases with a similar frame 7. Study treatments including an ACE inhibitor alone or in combination with a calcium channel blocker (CCB), or placebo.
Both studies were coordinated and monitored by the Mario Negri Institute for Pharmacological Research and were run by the same network of investigators. They conformed to the Declaration of Helsinki guidelines and were approved by the Ethical Committees of participating Centers. All patients provided written consent. Data were handled in respect of anonymity and confidentiality.
Measurements, Estimates and Definitions BLOOD PRESSURE -The blood pressure was measured at the brachial artery of the non-dominant arm in the morning, before study drug administration and after five minutes rest in the sitting position, by using a validated oscillometric device (Omron 705IT ® ) and a standard cuff. The mean of 3 measurements taken 2 min apart was recorded for statistical analyses.
GLOMERULAR FILTRATION RATE -In all patients the GFR was centrally measured at the Coordinating Center with the iohexol (Omnipaque 300, GE Healthcare, Milan, Italy) plasma clearance technique (13) at baseline and every six months throughout the whole observation period. Iohexol plasma levels were measured by high-performance-liquid chromatography (HPLC) and the clearance was calculated according to a one-compartment model with Bröchner-Mortensen adjustment (15) and normalized to 1.73m 2 of body surface area.
GLUCOSE DISPOSAL RATE -Glucose disposal rate (GDR) was assessed at inclusion and at 1 year in a subgroup by the hyperinsulinemic euglycemic clamp (16). GDR was calculated as the mean of the glucose infusion rate per kilogram of body weight required to maintain steady-state euglycemia during the last 30 minutes of the clamp.
LABORATORY EVALUATIONS -Urinary albumin was measured by nephelometry (Beckman Array System) in three timed overnight urine samples collected in bottles with a preservative. HbA 1c was centrally measured by ion-exchange HPLC (normal range: 3.53 to 5.21%). Other parameters were evaluated with a Beckman Synchron CX5 instrument and a Coulter MaxM (Beckman Coulter).
Definitions HYPERFILTRATION -Patients who had a measured GFR at inclusion exceeding the upper limit of the normal range (120 ml/min/1.73m 2 ) were a priori categorized as "hyperfiltering" and those with lower GFRs as "non-hyperfiltering". Since the reproducibility range of GFR measurement by the iohexol plasma clearance technique is ±6.28% ((13,15)), a pre-defined cut-off 10% GFR reduction largely exceeding the reproducibility range of the measurement was expected to univocally identify patients with true GFR reductions from those with random data fluctuations related to the variability of the method. Thus, among patients who were hyperfiltering at baseline, those with a GFR reduction >10% at month six were considered as patients with ameliorated hyperfiltration. Those with smaller reductions were categorized as "persistently hyperfiltering".
END POINTS -Pre-defined end points were: a.-the rate of GFR decline over time (GFR slope) defined as the regression line between repeated GFR measurements and time (17,18), and b.-time to onset of persistent micro-or macro albuminuria defined as UAE ≥20 and <200 µg/min or ≥200 µg/min, respectively (10,11).

Statistical Analysis
Analyses were performed at the Laboratory of Biostatistics of the Clinical Research Center by SPSS 14.0.1 (Chicago, IL), STATA 11.0 and SAS 9.1 (Institute Inc, Cary, North Carolina). Data were expressed as mean ± standard deviation (SD), median and interquartile range (IQR) or number and percent as appropriate. P<0.05 indicated statistical significance.
COMPARATIVE AND CORRELATION ANALYSES -Baseline and follow-up characteristics were compared by paired or unpaired t-test, Wilcoxon rank sum test, chi-square or Fisher's exact test. Correlations between variables were evaluated using Pearson r or Spearman rho correlation coefficients.
GFR SLOPE ANALYSES -These analyses were pre-planned for a subgroup of patients from the BENEDICT Study (19) and for all patients from DEMAND (11) who had at least 3 follow-up GFR measurements in addition to baseline GFR. GFR changes over time were initially evaluated by a single slope linear model (14). However, on the basis of previous evidence that patients included in randomized trials may have a bi-modal rate of GFR decline (8,17,20) we also a priori used a two-phase model in which GFR changes from baseline to month six and GFR slope from month six to study end were assessed separately. To test the possibility that GFR reduction at six months could be affected by GFR at baseline (regression to the mean), GFR changes at six months were a posteriori compared between hyperfiltering and nonhyperfiltering patients after adjusting for baseline GFR values by using an analysis of covariance (ANCOVA) (21).

MULTIVARIABLE REGRESSION ANALYSES:
The relationships between baseline GFR, or GFR changes from baseline to month six, and subsequent GFR decline were evaluated by two multivariable models considering as outcomes the GFR slopes calculated throughout the whole follow-up period (Model 1) or from month six to study end (Model 2), respectively. To account for possible heterogeneity between studies, we developed a meta-analysis of individual patient continuous outcome data using a random trial effect with patient-level covariates in which the original study and the observation from an individual patient were at the highest and lowest level, respectively (22). The possibility of including treatments as a random instead of a fixed effect was eventually assessed by the likelihood ratio test. Continuous explanatory variables were approximately centered to the mean for every analysis. Baseline GFR was introduced as a covariate in both Models 1 and 2. Then the analyses in Model 2 were repeated by considering GFR changes at six months instead of baseline GFR. The models included covariates a priori considered to be potentially associated with the outcomes (age; gender; smoking habit; baseline systolic BP, HbA1C, GFR, and albuminuria; previous inclusion in BENEDICT-B or DEMAND; randomization to ACE inhibitor therapy yes or no, and treatment arms) or found a posteriori to be significantly associated (p<0.05) with the outcome at univariable analyses. Systolic was considered instead of diastolic BP to avoid co-linearity. Independent variables that were non-normally distributed were log-transformed before analyses. In additional sensitivity analyses we further evaluated the bimodal GFR change over time by considering repeated GFR measures as the outcome in a spline function with a knot at six months (23). Finally, we analyzed the slope of GFR in patients with persistent hyperfiltration as compared to those who had their initial hyperfiltration ameliorated at six months considered alone or together with those who were non hyperfiltering since inclusion.
PROGRESSION TO MICRO OR MACRO ALBUMINURIA -In subjects with at least one follow-up measurement of albuminuria, we a priori evaluated the association between baseline GFR, or hyperfiltration at inclusion, and the development of micro-or macro-albuminuria by Kaplan-Meier analysis and log-rank test, and by a multivariate proportional hazard model considering time to micro-or-macro-albuminuria as the dependent variable. We included in the model also potential confounders with a proven or expected relationship with the outcome such as age, gender, baseline albuminuria, baseline HbA 1C and systolic or diastolic BP, randomization to an ACE inhibitor yes or no, and inclusion in the DEMAND or BENEDICT-B trial. The same approach was used in post-hoc analyses evaluating progression to microor-macro-albuminuria in patients with hyperfiltration at inclusion who were persistently hyperfiltering at six months as compared to patients who had their hyperfiltration at inclusion ameliorated at six months considered alone or in combination with those who were persistently non-hyperfiltering since inclusion.
The assumption of proportionality was assessed by the log-minus-log procedure.
Supplementary Table 1. Baseline characteristics of patients with or without GFR slope data and of patients who were persistently hyperfiltering at month 6 compared to all other patients who were normofiltering or had their hyperfiltration at baseline ameliorated at month 6 (Others). Antihypertensive drugs -no.

Antidiabetic Treatments
Baseline ( Supplementary Table 3. Univariable results of fixed effects meta-analysis with patient-level covariates and random trial effects considering GFR decline from baseline (Model 1) and from month 6 (Model 2) to study end as dependent variables The estimates and SE for the intercept and the trial as a random effect for ear single covariate are not shown in order to simplify the  The coefficient reflects the relationship between independent and dependent variables (GFR slope). A negative coefficient indicates that an increase in the independent variable is associated with a decrease of GFR slope. For the particular case of GFR change, a negative coefficient of a negative change indicates that a decrease in this variable is associated with a positive of GFR slope.  The coefficient reflects the relationship between independent and dependent variables (GFR slope). A negative coefficient indicates that an increase in the independent variable is associated with a decrease of GFR slope. For the particular case of GFR change, a negative coefficient of a negative change indicates that a decrease in this variable is associated with a positive of GFR slope. # replacing GFR change for the change (baseline to mo-6) of HbA1c [-0.0066 (0.012), p= 0.6] or of systolic blood pressure [-0.00065 (0.0009), p= 0.50] or including both covariates lead to non-significant results.