Dataset Information

Establishment of a novel risk score for in-hospital mortality in adult sepsis patients.

ABSTRACT:

Background

Existing scoring systems have limitations in predicting the in-hospital mortality of adult sepsis patients. We aimed to develop and validate a novel risk score for predicting the in-hospital mortality of adult sepsis patients.

Methods

The clinical data of 1,335 adult sepsis inpatients were retrospectively analyzed. Enrolled patients were randomly divided into a modeling group and a validation group at a 3:2 ratio. The modeling group (n=801) was used to develop the risk score by univariate and multivariate logistic regression analyses. The score's performance was validated in the validation group (n=534). We classified patients into four risk levels according to the novel risk score.

Results

Age, central vein catheterization, mechanical ventilation, vasopressin, Charlson comorbidity index (CCI), respiratory rate (RR), heart rate (HR), Glasgow coma scale (GCS) score, platelet (PLT), hematocrit (HCT), aspartate aminotransferase (AST), and activated partial thrombin time (APTT) were independent risk factors for in-hospital death in adult sepsis patients. Continuous variables were converted into classified variables to develop the risk score, with a total score of 39 points. Adult sepsis patients with low, lower medium, higher medium, and high risk levels had in-hospital mortality rates of 9.8%, 24.7%, 55.8%, and 83.5%, respectively.

Conclusions

Compared with the Acute Physiology and Chronic Health Evaluation II scoring system (APACHE II) and the Modified Early Warning Score (MEWS), the novel risk score showed good predictive performance for in-hospital mortality in adult sepsis patients.

SUBMITTER: Zheng YJ

PROVIDER: S-EPMC9372666 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Publications

Establishment of a novel risk score for in-hospital mortality in adult sepsis patients.

Zheng Yan-Jun YJ Zhu Xiao-Juan XJ Chen Yu-Wei YW Zheng Yu-Zhen YZ Zhou Yi Y Chen Wen-Jie WJ Zheng Xiang-Tao XT Zhong Ming M Yang Zhi-Tao ZT Mao En-Qiang EQ Chen Er-Zhen EZ Chen Ying Y

Annals of translational medicine 20220701 14

<h4>Background</h4>Existing scoring systems have limitations in predicting the in-hospital mortality of adult sepsis patients. We aimed to develop and validate a novel risk score for predicting the in-hospital mortality of adult sepsis patients.<h4>Methods</h4>The clinical data of 1,335 adult sepsis inpatients were retrospectively analyzed. Enrolled patients were randomly divided into a modeling group and a validation group at a 3:2 ratio. The modeling group (n=801) was used to develop the risk ...[more]

PMID: 35965826

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Project description:RationaleImmunosuppressive medical conditions are risk factors for mortality from severe infections. It is unknown whether hospital characteristics affect this risk.ObjectivesTo determine whether the odds of death for an immunosuppressed patient with sepsis relative to a nonimmunosuppressed patient with sepsis varies according to the hospital's yearly case volume of immunosuppressed patients with sepsis.MethodsPatients with sepsis at hospitals in the Vizient database were characterized as immunosuppressed or not immunosuppressed on the basis of diagnosis codes and medication use. Hospitals were grouped into quartiles based on their average volumes of immunosuppressed patients with sepsis per year. Multilevel logistic regression with clustering of patients by hospital was used to determine whether the odds of in-hospital death from sepsis owing to a suppressed immune state varied by hospital quartile.ResultsThere were 350,183 patients with sepsis at 60 hospitals in the Vizient database from 2010 to 2012. Immunosuppressed patients with sepsis at the 15 hospitals in the lowest quartile (64 to 224 immunosuppressed patients with sepsis per year) had an increased odds of in-hospital death relative to nonimmunosuppressed patients with sepsis at these hospitals (adjusted odds ratio, 1.38; 95% confidence interval, 1.27-1.50; P < 0.001). The odds of in-hospital death for immunosuppressed patients with sepsis relative to nonimmunosuppressed patients with sepsis was similar for patients at hospitals in the second, third, and fourth quartiles (225 to 1,056 immunosuppressed patients with sepsis per year). The adjusted odds of death from sepsis owing to a suppressed immune state of 1.21 (95% confidence interval, 1.18-1.25; P < 0.001) for patients at these 45 hospitals was significantly less than for patients at the 15 hospitals in the lowest quartile (P = 0.004 for difference).ConclusionsThe risk of death from sepsis owing to a suppressed immune state was greatest at hospitals with the lowest volume of immunosuppressed patients with sepsis. Further study is needed to determine whether this finding is related to differences in patient characteristics or in care delivery at hospitals with different amounts of exposure to immunosuppressed patients.

Project description:PURPOSE:Sepsis is a common acute life-threatening condition that emergency physicians routinely face. Diagnostic options within the Emergency Department (ED) are limited due to lack of infrastructure, consequently limiting the use of invasive hemodynamic monitoring or imaging tests. The mortality rate due to sepsis can be assessed via multiple scoring systems, for example, mortality in emergency department sepsis (MEDS) score and sepsis patient evaluation in the emergency department (SPEED) score, both of which quantify the variation of mortality rates according to clinical findings, laboratory data, or therapeutic interventions. This study aims to improve the management processes of sepsis patients by comparing SPEED score and MEDS score for predicting the 28-day mortality in cases of emergency sepsis. METHODS:The study is a cross-sectional, prospective study including 61 sepsis patients in ED in Suez Canal University Hospital, Egypt, from August 2017 to June 2018. Patients were selected by two steps: (1) suspected septic patients presenting with at least one of the following abnormal clinical findings: (a) body temperature higher than 38 °C or lower than 36 °C, (b) heart rate higher than 90 beats/min, (c) hyperventilation evidenced by respiratory rate higher than 20 breaths/min or PaCO2 lower than 32 mmHg, and (d) white blood cell count higher than 12,000/μL or lower than 4000/μL; (2) confirmed septic patients with at least a 2-point increase from the baseline total sequential organ failure assessment (SOFA) score following infection. Other inclusion criteria included adult patients with an age ≥18 years regardless of gender and those who had either systemic inflammatory response syndrome or suspected/confirmed infection. Patients were shortly follow-up for the 28-day mortality. Each patient was subject to SPEED score and MEDS score and then the results were compared to detect which of them was more effective in predicting outcome. The receiver operating characteristic curves were also done for MEDS and SPEED scores. RESULTS:Among the 61 patients, 41 died with the mortality rate of 67.2%. The mortality rate increased with a higher SPEED and MEDS scores. Both SPEED and MEDS scores revealed significant difference between the survivors and nonsurvivors (p = 0.004 and p < 0.001, respectively), indicating that both the two systems are effective in predicting the 28-day mortality of sepsis patients. Thereafter, the receiver operating characteristic curves were plotted, which showed that SPEED was better than the MEDS score when applied to the complete study population with an area under the curve being 0.87 (0.788-0.963) as compared with 0.75 (0.634-0.876) for MEDS. Logistic regression analysis revealed that the best fitting predictor of 28-day mortality for sepsis patients was the SPEED scoring system. For every one unit increase in SPEED score, the odds of 28-day mortality increased by 37%. CONCLUSION:SPEED score is more useful and accurate than MEDS score in predicting the 28-day mortality among sepsis patients. Therefore SPEED rather than MEDS should be more widely used in the ED for sepsis patients.

Project description:BackgroundPatients suffering from major trauma often experience complications such as sepsis. The early recognition of patients at high risk of sepsis after trauma is critical for precision therapy. We aimed to derive and validate a novel predictive score for sepsis risk using electronic medical record (EMR) data following trauma.Materials and methodsClinical and laboratory variables of 684 trauma patients within 24 h after admission were collected, including 411 patients in the training cohort and 273 in the validation cohort. The least absolute shrinkage and selection operator (LASSO) technique was adopted to identify variables contributing to the early prediction of traumatic sepsis. Then, we constructed a traumatic sepsis score (TSS) using a logistic regression model based on the variables selected in the LASSO analysis. Moreover, we evaluated the discrimination and calibration of the TSS using the area under the curve (AUC) and the Hosmer-Lemeshow (H-L) goodness-of-fit test.ResultsBased on the LASSO, seven variables (injury severity score, Glasgow Coma Scale, temperature, heart rate, albumin, international normalized ratio, and C-reaction protein) were selected for construction of the TSS. Our results indicated that the incidence of sepsis after trauma increased with an increasing TSS (P trend = 7.44 × 10-21 for the training cohort and P trend = 1.16 × 10-13 for the validation cohort). The areas under the receiver operating characteristic (ROC) curve of TSS were 0.799 (0.757-0.837) and 0.790 (0.736-0.836) for the training and validation datasets, respectively. The discriminatory power of our model was superior to that of a single variable and the sequential organ failure assessment (SOFA) score (P < 0.001). Moreover, the TSS was well calibrated (P > 0.05).ConclusionsWe developed and validated a novel TSS with good discriminatory power and calibration for the prediction of sepsis risk in trauma patients based on the EMR data.

Dataset Information

Establishment of a novel risk score for in-hospital mortality in adult sepsis patients.

Background

Methods

Results

Conclusions

Publications

Establishment of a novel risk score for in-hospital mortality in adult sepsis patients.

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