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1914. Adherence to the Sepsis Bundle in Hospital-Onset vs. Community-Onset Sepsis

Abstract Background Every hour of delay between onset of sepsis and administration of the sepsis bundle increases sepsis mortality. Hospital-onset sepsis is known to have higher mortality than community-onset sepsis, but the differences in care between cases of hospital-onset and community-onset sepsis have not been characterized. The purpose of this study was to examine adherence to the sepsis bundle when sepsis arises in different areas of the hospital (ward, intensive care unit [ICU], or peri-operative area) compared with community-onset sepsis. Methods Retrospective cohort study using clinical data from four University of California hospitals. Admissions for sepsis from 2014 to 2016 were identified by diagnosis codes. Generalized linear models were used to estimate likelihood of adherence in terms of relative risk (RR). Time-to-event analysis involved Cox proportional hazards models and Kaplan–Meier curves. Results Overall, the sepsis bundle was administered in accordance with guidelines in 11.1% of cases. On multivariable analysis, cases of hospital-onset sepsis were less likely to receive the sepsis bundle within the recommended time frame (adjusted RR 0.57, P < 0.001) than were cases of community-onset sepsis, including a lower likelihood of having blood cultures drawn (adjusted RR 0.75, P < 0.001), serum lactate checked (adjusted RR 0.48, P < 0.001), or broad-spectrum antibiotics administered within 3 hours (adjusted RR 0.65, P < 0.001). Among the cases of hospital-onset sepsis, those arising in the ICU were more likely than those arising on the ward or in the perioperative area to receive the sepsis bundle within the recommended time frame (RR 1.83, P = 0.002). On time-to-event analysis, hospital-onset was associated with significant delays for all 3-hour bundle components except intravenous fluids. Conclusion Developing sepsis in one of the inpatient hospital areas was associated with a delay in guideline-adherent sepsis care. The ward and perioperative area experienced the longest delays. Further research is needed to determine whether these delays in care contribute to the increased mortality associated with hospital-onset sepsis. Disclosures All authors: No reported disclosures.

Background. Sepsis is a major public health concern. Revised definitions of sepsis in 2016 from the systemic inflammatory response syndrome (SIRS) criteria to the Sequential Organ Failure Assessment (SOFA) score made change in the sepsis case detection. One-hour bundle proposed by the Surviving Sepsis Campaign Bundle 2018 made the process more practically challenging because of its time-constraint.
Methods. We retrospectively reviewed medical records of patients aged over 15 who visited the emergency department (ED) and got admitted to the internal medicine department from January to February 2018 in Somdech Phra Pinklao Hospital. Our study excluded pregnant women and patients who died within 48 hours after the admission. Data needed to complete SIRS, SOFA and quick SOFA (qSOFA) score was collected. Patients' diagnosis, treatments and in-hospital mortality were also reviewed. Prevalence of sepsis according to each definition was calculated. Test performances were summarized separately using sensitivity, specificity, ROC and AUC.
Conclusion. Although SOFA score was a better diagnostic tool to detect sepsis than SIRS, applying the method for all patients in the ED is difficult to be practically implemented. We proposed two-step approach by using SIRS ≥2 followed by SOFA score ≥2 for sepsis case detection.
Disclosures. All authors: No reported disclosures. Background. Sepsis is common and catastrophic. The usefulness of the qSOFA score has been questioned. Thus far, data on the validity of the instrument have been derived from developed countries. The generalizability to developing countries is unknown. This study aimed to ascertain how "qSOFA" predicted death and need for intensive care in patients at a tertiary hospital in Jamaica.

Clinical Performance of the qSOFA Score Among Non-ICU Inpatients With Infection at a Tertiary Hospital in Jamaica
Methods. Seven hundred fifty-two patients admitted between January 2015 and December 2016 with a physician determined diagnosis of infection were randomly selected from the electronic medical database. The details of the first 48 hours of their admission were reviewed.
Results. Most patients were middle-aged females who remained in hospital for an average of 9 days and were managed by Internal Medicine. Two of the most common sites of infection (respiratory and gastrointestinal) were also the two sites associated with the highest risk of death or requiring intensive care. 126 (17%) had a qSOFA score ≥2 at presentation, 4 (0.5%) persons died, and 32 (4%) required admission to ICU. Many more patients met the SIRS criteria than qSOFA at presentation (66% vs. 17%). Meeting the SIRS criteria, however, was not significantly associated with death or needing intensive care. On the other hand, those with a positive qSOFA at presentation were three times more likely to die or need intensive care (OR 3.03; 95% CI 1.1,8.9; P = 0.04). The qSOFA score detected these patients, with a high degree of specificity (84%), especially when utilized at presentation (OR 3.03; 95% CI 1.03-8.92; P = 0.04) and 48 hours after (OR 2.24, 95% CI 0.94-5.37, P = 0.07). The sensitivity of the qSOFA score was poor (39%), but this was improved to 100% when combined with the SIRS score at presentation. There was a suggestion that this combined score also offered the best prognostic accuracy with an AUROC of 0.74 (95% CI 0.66-0.81) when compared with the qSOFA score (AUROC -0.68, 95% CI 0.60-0.76) or SIRS criteria alone (AUROC -0.71, 95% CI 0.63-0.79). However, there was significant overlap of the curves and the differences were not significant.
cases of hospital-onset and community-onset sepsis have not been characterized. The purpose of this study was to examine adherence to the sepsis bundle when sepsis arises in different areas of the hospital (ward, intensive care unit [ICU], or peri-operative area) compared with community-onset sepsis.
Methods. Retrospective cohort study using clinical data from four University of California hospitals. Admissions for sepsis from 2014 to 2016 were identified by diagnosis codes. Generalized linear models were used to estimate likelihood of adherence in terms of relative risk (RR). Time-to-event analysis involved Cox proportional hazards models and Kaplan-Meier curves.
Results. Overall, the sepsis bundle was administered in accordance with guidelines in 11.1% of cases. On multivariable analysis, cases of hospital-onset sepsis were less likely to receive the sepsis bundle within the recommended time frame (adjusted RR 0.57, P < 0.001) than were cases of community-onset sepsis, including a lower likelihood of having blood cultures drawn (adjusted RR 0.75, P < 0.001), serum lactate checked (adjusted RR 0.48, P < 0.001), or broad-spectrum antibiotics administered within 3 hours (adjusted RR 0.65, P < 0.001). Among the cases of hospital-onset sepsis, those arising in the ICU were more likely than those arising on the ward or in the perioperative area to receive the sepsis bundle within the recommended time frame (RR 1.83, P = 0.002). On time-to-event analysis, hospital-onset was associated with significant delays for all 3-hour bundle components except intravenous fluids.
Conclusion. Developing sepsis in one of the inpatient hospital areas was associated with a delay in guideline-adherent sepsis care. The ward and perioperative area experienced the longest delays. Further research is needed to determine whether these delays in care contribute to the increased mortality associated with hospital-onset sepsis.
Disclosures. All authors: No reported disclosures. Conclusion. Temperature trajectory modeling may help identify postoperative patients at higher risk for surgical complication after surgery. While risk stratification seems to work better in high complication surgeries or models with more patients, the promise of this modeling technique relies on the ability to identify high-risk patients with a single variable.