Daily Sepsis Research Analysis

BACKGROUND AND OBJECTIVES: The Phoenix criteria for pediatric sepsis and septic shock have recently been proposed for worldwide application. The Phoenix sepsis criteria are based on organ dysfunction scoring. Although many screening tools exist, their performance in predicting Phoenix outcomes is not known. We hypothesized that the quick Pediatric Septic Shock Screening Score (qPS4) would demonstrate greater sensitivity compared with the Liverpool quick Sequential Organ Failure Assessment (LqSOFA) and a commonly used 2-stage screening tool created at Children's Hospital of Philadelphia (CHOP). METHODS: We performed a secondary analysis of the qPS4 validation set data from a retrospective cohort study of pediatric emergency department patients with suspected infection. The exposure was a positive screen prior to outcome occurring. We calculated the predictive characteristics of qPS4, LqSOFA, and CHOP for Phoenix sepsis and septic shock within 24 hours of arrival. RESULTS: We analyzed 47 176 encounters. Within 24 hours of arrival to the ED, 628 (1.3%) met criteria for sepsis and 228 (0.5%) met criteria for septic shock. The qPS4 predicted sepsis with 67.8% sensitivity and 89.6% specificity compared with LqSOFA (sensitivity 47.0%, specificity 95.7%) and the CHOP screen (sensitivity 49.7%, specificity 92.1%) (P < .05 for all compared to qPS4). The qPS4 predicted septic shock with 85.5% sensitivity and 89.0% specificity compared with LqSOFA (sensitivity 59.2%, specificity 95.2%) and the 2-stage CHOP screen (sensitivity 64.9%, specificity 91.5%) (P < .05 for all compared to qPS4). CONCLUSIONS: The qPS4 predicted Phoenix sepsis and septic shock with greater sensitivity and clinically similar specificity compared with widely used bedside tools.

OBJECTIVE: Our research aimed to explore the application of pulse pressure (PP) at the bedside of elderly intensive care unit (ICU) patients with sepsis through a large-scale retrospective cohort study. METHODS: We obtained data from four heterogeneous datasets, which included information on elderly sepsis patients (≥ 65 years). The data were divided into the inference and validation datasets. Thereby enhancing the generalizability of the study. The primary outcome was mortality at 28 days, and piecewise exponential additive mixed model (PAMM) were employed to estimate the strength of the associations over time. RESULTS: We included 12,525 elderly patients with sepsis in the initial inference dataset. Based on the PAMM's inference results, we identified a specific low PP phenotype from the time-dependent endpoint dataset. The phenotype indicates an imbalance between the patient's cardiac pumping ability and circulatory resistance, contributing to an increased 28-day mortality (hazard ratio, 2.36; 95% CI, 2.12-2.63). The consistency of these results was validated using data from various sources. CONCLUSION: Low PP phenotype (PP < 45 mmHg 72 h after intensive care unit admission and lasting for > 3h) may provide an early dynamic warning of the therapeutic effects of resuscitation interventions in long-hospitalized elderly patients with sepsis. IMPLICATIONS FOR CLINICAL PRACTICE: The results demonstrate acceptable consistency across heterogeneous datasets and hold promise for further development and integration into bedside monitoring systems for elderly sepsis patients.

BACKGROUND: The dysregulated stress response is a key pathological mechanism underlying sepsis and is strongly associated with poor clinical outcomes. Stress hyperglycemia, a common manifestation of this response, may provide valuable prognostic information in sepsis patients. The stress hyperglycemia ratio (SHR) offers a more accurate reflection of the stress response and may be instrumental in assessing sepsis prognosis. METHODS: This study aimed to investigate the relationship between SHRs and clinical outcomes in sepsis patients. Data were obtained from the Medical Information Mart for Intensive Care IV database. Demographic information, intensive care unit (ICU) parameters within the first 24 h, laboratory results, insulin administration, survival time, and outcomes were extracted for analysis. Four SHR metrics (SHRfirst, SHRmin, SHRmax, and SHRmean) were calculated based on blood glucose values during the first 24 h of ICU admission (first, minimum, maximum, and mean, respectively). The predictive performance of each SHR metric was compared using the area under the receiver operating characteristic (ROC) curve. Kaplan-Meier survival analysis was performed to assess survival rates across groups defined by ROC curve-generated cut-off values. Associations between SHR and 28-day as well as 1-year mortality were further examined using both univariate and multivariate Cox regression analyses. RESULTS: A total of 5,025 sepsis patients were included, of whom 656 died within 28 days of ICU admission. SHR was significantly higher in the non-survivor group. Among the SHR metrics, SHRmax demonstrated the highest predictive value for both 28-day and 1-year mortality. Higher SHR values were consistently associated with increased mortality (all P < 0.001). For SHRmax, each 1-unit increase was associated with a 77% increase in mortality in univariate analysis and a 71.6% increase in multivariate analysis. Sensitivity analyses indicated that the relationship between SHR and mortality was stronger in patients without diabetes. CONCLUSIONS: SHR serves as a robust marker of the dysregulated stress response in sepsis and holds significant prognostic value, particularly SHRmax, in predicting mortality. These findings underscore the potential clinical utility of SHR in guiding therapeutic strategies aimed at modulating the stress response and blood glucose levels in critically ill sepsis patients. Further research is warranted to explore SHR-targeted interventions in sepsis management.