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Predicting in-hospital mortality for sepsis: a comparison between qSOFA and modified qSOFA in a 2-year single-centre retrospective analysis.

ABSTRACT: Sepsis is a life-threating organ dysfunction caused by a dysregulated host response to infection. This study proposed a new tool, i.e. modified qSOFA, for the early prognostic assessment of septic patients. All cases of sepsis/septic shock consecutively observed in 2 years (January 2017-December 2018), at St. Anna University Hospital of Ferrara, Italy, were included. Each patient was evaluated with qSOFA and a modified qSOFA (MqSOFA), i.e. adding a SpO2/FiO2 ratio to qSOFA. Logistic regression and survival analyses were applied to compare the two scores. A total number of 1137 consecutive cases of sepsis and septic shock were considered. Among them 136 were excluded for incomplete report of vital parameters. A total number of 668 patients (66.7%) were discharged, whereas 333 (33.3%) died because of sepsis-related complications. Data analysis showed that MqSOFA (AUC 0.805, 95% C.I. 0.776-0.833) had a greater ability to detect in-hospital mortality than qSOFA (AUC 0.712, 95% C.I. 0.678-0.746) (p < 0.001). Eighty-five patients (8.5%) were reclassified as high-risk (qSOFA< 2 and MqSOFA≥ 2) resulting in an improvement of sensitivity with a minor reduction in specificity. A significant difference of in-hospital mortality was observed between low-risk and reclassified high-risk (p < 0.001) and low-risk vs. high-risk groups (p < 0.001). We demonstrated that MqSOFA provided a better predictive score than qSOFA regarding patient's outcome. Since sepsis is an underhanded and time-dependent disease, physicians may rely upon the herein proposed simple score, i.e. MqSOFA, to establish patients' severity and outcome.

SUBMITTER: Guarino M

PROVIDER: S-EPMC7979592 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Predicting in-hospital mortality for sepsis: a comparison between qSOFA and modified qSOFA in a 2-year single-centre retrospective analysis.

Guarino Matteo M Gambuti Edoardo E Alfano Franco F De Giorgi Alfredo A Maietti Elisa E Strada Andrea A Ursini Francesco F Volpato Stefano S Caio Giacomo G Contini Carlo C De Giorgio Roberto R

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology 20201028 4

Sepsis is a life-threating organ dysfunction caused by a dysregulated host response to infection. This study proposed a new tool, i.e. modified qSOFA, for the early prognostic assessment of septic patients. All cases of sepsis/septic shock consecutively observed in 2 years (January 2017-December 2018), at St. Anna University Hospital of Ferrara, Italy, were included. Each patient was evaluated with qSOFA and a modified qSOFA (MqSOFA), i.e. adding a SpO2/FiO2 ratio to qSOFA. Logistic regression a ...[more]

PMID: 33118057

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Project description:BackgroundThe majority of the prognostic scoring tools for peritonitis are impractical in low resource settings because they are complex while others are quite costly. The quick Sepsis-related Organ Failure Assessment (qSOFA) score and the Physiologic Indicators for Prognosis in Abdominal Sepsis (PIPAS) severity score are two strictly bedside prognostic tools but their predictive ability for mortality of peritonitis is yet to be compared. We compared the predictive ability of the qSOFA criteria and the PIPAS severity score for in-hospital mortality of peritonitis.MethodThis was a prospective cohort study on consecutive peritonitis cases managed surgically in a tertiary hospital in Uganda between October 2020 to June 2021. PIPAS severity score and qSOFA score were assessed preoperatively for each case and all cases were then followed up intra- and postoperatively until discharge from the hospital, or up to 30 days if the in-hospital stay was prolonged; the outcome of interest was in-hospital mortality. We used Receiver Operating Characteristic curve analysis to assess and compare the predictive abilities of these two tools for peritonitis in-hospital mortality. All tests were 2 sided (p < 0.05) with 95% confidence intervals.ResultsWe evaluated 136 peritonitis cases. Their mean age was 34.4 years (standard deviation = 14.5). The male to female ratio was 3:1. The overall in-hospital mortality rate for peritonitis was 12.5%. The PIPAS severity score had a significantly better discriminative ability (AUC = 0.893, 95% CI 0.801-0.986) than the qSOFA score (AUC = 0.770, 95% CI 0.620-0.920) for peritonitis mortality (p = 0.0443). The best PIPAS severity cut-off score (a score of > = 2) had sensitivity and specificity of 76.5%, and 93.3% respectively, while the corresponding values for the qSOFA criteria (score > = 2), were 58.8% and 98.3% respectively.ConclusionsThe in-hospital mortality in this cohort of peritonitis cases was high. The PIPAS severity score tool has a superior predictive ability and higher sensitivity for peritonitis in-hospital mortality than the qSOFA score tool although the latter tool is more specific. We recommend the use of the PIPAS severity score as the initial prognostic tool for peritonitis cases in the emergency department.

Project description:BackgroundA feasible and accurate risk prediction systems for emergency department (ED) patients is urgently required. The Modified Early Warning Score (MEWS) is a wide-used tool to predict clinical outcomes in ED. Literatures showed that machine learning (ML) had better predictability in specific patient population than traditional scoring system. By analyzing a large multicenter dataset, we aim to develop a ML model to predict in-hospital morality of the adult non traumatic ED patients for different time stages, and comparing performance with other ML models and MEWS.MethodsA retrospective observational cohort study was conducted in five Taiwan EDs including two tertiary medical centers and three regional hospitals. All consecutively adult (>17 years old) non-traumatic patients admit to ED during a 9-year period (January first, 2008 to December 31th, 2016) were included. Exclusion criteria including patients with (1) out-of-hospital cardiac arrest and (2) discharge against medical advice and transferred to other hospital (3) missing collect variables. The primary outcome was in-hospital mortality and were categorized into 6, 24, 72, 168 hours mortality. MEWS was calculated by systolic blood pressure, pulse rate, respiratory rate, body temperature, and level of consciousness. An ensemble supervised stacking ML model was developed and compared to sensitive and unsensitive Xgboost, Random Forest, and Adaboost. We conducted a performance test and examine both the area under the receiver operating characteristic (AUROC) and the area under the precision and recall curve (AUPRC) as the comparative measures.ResultAfter excluding 182,001 visits (7.46%), study group was consisted of 24,37,326 ED visits. The dataset was split into 67% training data and 33% test data for ML model development. There was no statistically difference found in the characteristics between two groups. For the prediction of 6, 24, 72, 168 hours in-hospital mortality, the AUROC of MEW and ML mode was 0.897, 0.865, 0.841, 0.816 and 0.939, 0.928, 0.913, 0.902 respectively. The stacking ML model outperform other ML model as well. For the prediction of in-hospital mortality over 48-hours, AUPRC performance of MEWS drop below 0.1, while the AUPRC of ML mode was 0.317 in 6 hours and 0.2150 in 168 hours. For each time frame, ML model achieved statistically significant higher AUROC and AUPRC than MEWS (all P < 0.001). Both models showed decreasing prediction ability as time elapse, but there was a trend that the gap of AUROC values between two model increases gradually (P < 0.001). Three MEWS thresholds (score >3, >4, and >5) were determined as baselines for comparison, ML mode consistently showed improved or equally performance in sensitivity, PPV, NPV, but not in specific.ConclusionStacking ML methods improve predicted in-hospital mortality than MEWS in adult non-traumatic ED patients, especially in the prediction of delayed mortality.

Project description:BackgroundThe Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) Task Force recently introduced a new clinical score termed quick Sequential (Sepsis-related) Organ Failure Assessment (qSOFA) for identification of patients at risk of sepsis outside the intensive care unit (ICU). We attempted to compare the discriminatory capacity of the qSOFA versus the Systemic Inflammatory Response Syndrome (SIRS) score for predicting mortality, ICU-free days, and organ dysfunction-free days in patients with suspicion of infection outside the ICU.MethodsThe Weill Cornell Medicine Registry and Biobank of Critically Ill Patients is an ongoing cohort of critically ill patients, for whom biological samples and clinical information (including vital signs before and during ICU hospitalization) are prospectively collected. Using such information, qSOFA and SIRS scores outside the ICU (specifically, within 8 hours before ICU admission) were calculated. This study population was therefore comprised of patients in the emergency department or the hospital wards who had suspected infection, were subsequently admitted to the medical ICU and were included in the Registry and Biobank.ResultsOne hundred fifty-two patients (67% from the emergency department) were included in this study. Sixty-seven percent had positive cultures and 19% died in the hospital. Discrimination of in-hospital mortality using qSOFA [area under the receiver operating characteristic curve (AUC), 0.74; 95% confidence intervals (CI), 0.66-0.81] was significantly greater compared with SIRS criteria (AUC, 0.59; 95% CI, 0.51-0.67; p = 0.03). The qSOFA performed better than SIRS regarding discrimination for ICU-free days (p = 0.04), but not for ventilator-free days (p = 0.19), any organ dysfunction-free days (p = 0.13), or renal dysfunction-free days (p = 0.17).ConclusionsIn patients with suspected infection who eventually required admission to the ICU, qSOFA calculated before their ICU admission had greater accuracy than SIRS for predicting mortality and ICU-free days. However, it may be less clear whether qSOFA is also better than SIRS criteria for predicting ventilator free-days and organ dysfunction-free days. These findings may help clinicians gain further insight into the usefulness of qSOFA.

Dataset Information

Predicting in-hospital mortality for sepsis: a comparison between qSOFA and modified qSOFA in a 2-year single-centre retrospective analysis.

Publications

Predicting in-hospital mortality for sepsis: a comparison between qSOFA and modified qSOFA in a 2-year single-centre retrospective analysis.

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