Combining multiple comorbidities with Acute Physiology Score to predict hospital mortality of critically ill patients: a linked data cohort study

There is limited evidence for the association between malnutrition and hospital mortality as well as Intensive Care Unit length-of-stay (ICU-LOS) in critically ill patients. We aimed to examine the aforementioned associations by conducting a prospective cohort study in an ICU of a Singapore tertiary hospital. Between August 2015 and October 2016, all adult patients with ≥24 h of ICU-LOS were included. The 7-point Subjective Global Assessment (7-point SGA) was used to determine patients’ nutritional status within 48 hours of ICU admission. Multivariate analyses were conducted in two ways: 1) presence versus absence of malnutrition, and 2) dose-dependent association for each 1-point decrease in the 7-point SGA. There were 439 patients of which 28.0% were malnourished, and 29.6% died before hospital discharge. Malnutrition was associated with an increased risk of hospital mortality [adjusted-RR 1.39 (95%CI: 1.10–1.76)], and this risk increased with a greater degree of malnutrition [adjusted-RR 1.09 (95%CI: 1.01–1.18) for each 1-point decrease in the 7-point SGA]. No significant association was found between malnutrition and ICU-LOS. Conclusion: There was a clear association between malnutrition and higher hospital mortality in critically ill patients. The association between malnutrition and ICU-LOS could not be replicated and hence requires further evaluation.

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Association of delayed time in the emergency department with the clinical outcomes for critically ill patients

QJM ◽

10.1093/qjmed/hcaa192 ◽

2020 ◽

Author(s):

S Lin ◽

S Ge ◽

W He ◽

M Zeng

Keyword(s):

Emergency Department ◽

Cohort Study ◽

Hospital Mortality ◽

Clinical Outcomes ◽

Critically Ill ◽

Waiting Time ◽

Critically Ill Patients ◽

Retrospective Cohort ◽

Stratified Analysis ◽

Delayed Time

Summary Background Previous studies have shown the association of waiting time in the emergency department with the prognosis of critically ill patients, but these studies linking the waiting time to clinical outcomes have been inconsistent and limited by small sample size. Aim To determine the relationship between the waiting time in the emergency department and the clinical outcomes for critically ill patients in a large sample population. Design A retrospective cohort study of 13 634 patients. Methods We used the Medical Information Mart for Intensive Care III database. Multivariable logistic regression was used to determine the independent relationships of the in-hospital mortality rate with the delayed time and different groups. Interaction and stratified analysis were conducted to test whether the effect of delayed time differed across various subgroups. Results After adjustments, the in-hospital mortality in the ≥6 h group increased by 38.1% (OR 1.381, 95% CI 1.221–1.562). Moreover, each delayed hour was associated independently with a 1.0% increase in the risk of in-hospital mortality (OR 1.010, 95% CI 1.008–1.010). In the stratified analysis, intensive care unit (ICU) types, length of hospital stay, length of ICU stay, simplified acute physiology score II and diagnostic category were found to have interactions with ≥6 h group in in-hospital mortality. Conclusions In this large retrospective cohort study, every delayed hour was associated with an increase in mortality. Furthermore, clinicians should be cautious of patients diagnosed with sepsis, liver/renal/metabolic diseases, internal hemorrhage and cardiovascular disease, and if conditions permit, they should give priority to transferring to the corresponding ICUs.

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The association between the duration of postoperative acute kidney injury and in-hospital mortality in critically ill patients after non-cardiac surgery: an observational cohort study

Renal Failure ◽

10.3109/0886022x.2015.1044755 ◽

2015 ◽

Vol 37 (6) ◽

pp. 985-993 ◽

Cited By ~ 15

Author(s):

Hung-Chieh Wu ◽

Wei-Jie Wang ◽

Yu-Wei Chen ◽

Han-Hsiang Chen

Keyword(s):

Acute Kidney Injury ◽

Cardiac Surgery ◽

Cohort Study ◽

Hospital Mortality ◽

Critically Ill ◽

Critically Ill Patients ◽

Kidney Injury ◽

Observational Cohort Study ◽

Observational Cohort

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Contrasting effects of preexisting hyperglycemia and higher body size on hospital mortality in critically ill patients: a prospective cohort study

BMC Endocrine Disorders ◽

10.1186/1472-6823-14-50 ◽

2014 ◽

Vol 14 (1) ◽

Cited By ~ 6

Author(s):

Marina Verçoza Viana ◽

Rafael Barberena Moraes ◽

Amanda Rodrigues Fabbrin ◽

Manoella Freitas Santos ◽

Vanessa Bielefeldt Leotti Torman ◽

...

Keyword(s):

Cohort Study ◽

Body Size ◽

Hospital Mortality ◽

Critically Ill ◽

Prospective Cohort Study ◽

Critically Ill Patients ◽

Prospective Cohort

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Systemic inflammatory response syndrome criteria and the prediction of hospital mortality in critically ill patients: a retrospective cohort study

Revista Brasileira de Terapia Intensiva ◽

10.5935/0103-507x.20170047 ◽

2017 ◽

Vol 29 (3) ◽

Cited By ~ 4

Author(s):

Leandro Utino Taniguchi ◽

Ellen Maria Campos Pires ◽

José Mauro Vieira Jr ◽

Luciano Cesar Pontes de Azevedo

Keyword(s):

Cohort Study ◽

Systemic Inflammatory Response Syndrome ◽

Inflammatory Response ◽

Hospital Mortality ◽

Critically Ill ◽

Retrospective Cohort Study ◽

Critically Ill Patients ◽

Retrospective Cohort ◽

Systemic Inflammatory Response

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ACEI/ARB Medication During ICU Stay Decrease All-Cause In-hospital Mortality in Critically Ill Patients With Hypertension: A Retrospective Cohort Study Based on Machine Learning

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.787740 ◽

2022 ◽

Vol 8 ◽

Author(s):

Boshen Yang ◽

Sixuan Xu ◽

Di Wang ◽

Yu Chen ◽

Zhenfa Zhou ◽

...

Keyword(s):

Machine Learning ◽

Cohort Study ◽

Hospital Mortality ◽

Critically Ill ◽

Critically Ill Patients ◽

Retrospective Cohort ◽

Learning Models ◽

Hyperparameter Optimization ◽

Icu Stay ◽

Machine Learning Models

Background: Hypertension is a rather common comorbidity among critically ill patients and hospital mortality might be higher among critically ill patients with hypertension (SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg). This study aimed to explore the association between ACEI/ARB medication during ICU stay and all-cause in-hospital mortality in these patients.Methods: A retrospective cohort study was conducted based on data from Medical Information Mart for Intensive Care IV (MIMIC-IV) database, which consisted of more than 40,000 patients in ICU between 2008 and 2019 at Beth Israel Deaconess Medical Center. Adults diagnosed with hypertension on admission and those had high blood pressure (SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg) during ICU stay were included. The primary outcome was all-cause in-hospital mortality. Patients were divided into ACEI/ARB treated and non-treated group during ICU stay. Propensity score matching (PSM) was used to adjust potential confounders. Nine machine learning models were developed and validated based on 37 clinical and laboratory features of all patients. The model with the best performance was selected based on area under the receiver operating characteristic curve (AUC) followed by 5-fold cross-validation. After hyperparameter optimization using Grid and random hyperparameter search, a final LightGBM model was developed, and Shapley Additive exPlanations (SHAP) values were calculated to evaluate feature importance of each feature. The features closely associated with hospital mortality were presented as significant features.Results: A total of 15,352 patients were enrolled in this study, among whom 5,193 (33.8%) patients were treated with ACEI/ARB. A significantly lower all-cause in-hospital mortality was observed among patients treated with ACEI/ARB (3.9 vs. 12.7%) as well as a lower 28-day mortality (3.6 vs. 12.2%). The outcome remained consistent after propensity score matching. Among nine machine learning models, the LightGBM model had the highest AUC = 0.9935. The SHAP plot was employed to make the model interpretable based on LightGBM model after hyperparameter optimization, showing that ACEI/ARB use was among the top five significant features, which were associated with hospital mortality.Conclusions: The use of ACEI/ARB in critically ill patients with hypertension during ICU stay is related to lower all-cause in-hospital mortality, which was independently associated with increased survival in a large and heterogeneous cohort of critically ill hypertensive patients with or without kidney dysfunction.

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Combining Sequential Organ Failure Assessment (SOFA) Score with Acute Physiology and Chronic Health Evaluation (APACHE) II Score to Predict Hospital Mortality of Critically Ill Patients

Anaesthesia and Intensive Care ◽

10.1177/0310057x0703500409 ◽

2007 ◽

Vol 35 (4) ◽

pp. 515-521 ◽

Cited By ~ 41

Author(s):

K. M. Ho

Keyword(s):

Hospital Mortality ◽

Critically Ill ◽

Sofa Score ◽

Critically Ill Patients ◽

Characteristic Curve ◽

Apache Ii ◽

Brier Score ◽

Apache Ii Score ◽

Failure Assessment ◽

Predict Hospital Mortality

The ability to accurately adjust for the severity of illness in outcome studies of critically ill patients is essential. Previous studies have showed that Sequential Organ Failure Assessment (SOFA) score and Acute Physiology and Chronic Health Evaluation (APACHE) II score can predict hospital mortality of critically ill patients. The effects of combining these two scores to predict hospital mortality of critically ill patients has not been evaluated. This cohort study evaluated the performance of combining the APACHE II score with SOFA score in predicting hospital mortality of critically ill patients. A total of 1,311 consecutive adult patients admitted to a tertiary 22-bed multidisciplinary intensive care unit (ICU) in Western Australia were considered. The APACHE II, Admission SOFA, Delta SOFA and maximum SOFA score were all related to hospital survival in the univariate analyses. Combining Max SOFA (area under receiver operating characteristic curve 0.875 vs. 0.858, P=0.014; Nagelkerke R2: 0.411 vs. 0.371; Brier Score: 0.086 vs. 0.090) or Delta SOFA score (area under receiver operating characteristic curve 0.874 vs. 0.858, P=0.003; Nagelkerke R2: 0.412 vs. 0.371; Brier Score: 0.086 vs. 0.090) with the APACHE II score improved the discrimination and overall performance of the predictions when compared with using the APACHE II score alone, especially in the emergency ICU admissions. Combining Max SOFA or Delta SOFA score with the APACHE II score may improve the accuracy of risk adjustment in outcome studies of critically ill patients.

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Statins’ safety and impact on the clinical outcomes in COVID-19 critically ill patients: A Multicenter, Cohort Study

10.21203/rs.3.rs-828175/v2 ◽

2021 ◽

Author(s):

Khalid Al Sulaiman ◽

Ohoud Aljuhani ◽

Ghazwa B. Korayem ◽

Ali F. Altebainawi ◽

Shmeylan Al Harbi ◽

...

Keyword(s):

Cohort Study ◽

Propensity Score ◽

Hospital Mortality ◽

Critically Ill ◽

Critically Ill Patients ◽

Hazard Ratio ◽

Icu Stay ◽

Markers Of Inflammation ◽

The Impact ◽

Statin Use

Abstract Purpose The complications of Severe Corona Virus Disease 2019 (COVID-19) are attributed to the overproduction of early response proinflammatory cytokines, causing a systemic hyperinflammatory state. Statins are potentially a potent adjuvant therapy in COVID-19 infection due to their pleiotropic and anti-inflammatory effects, which are independent of their cholesterol-lowering activity. This study investigates the impact of statin use on the outcome of critically ill patients with COVID-19. Methods A multicenter, retrospective cohort study of all adult critically ill patients with confirmed COVID-19 admitted to Intensive Care Units (ICUs) between March 1, 2020, and March 31, 2021. Eligible patients were classified into two groups based on statin use during ICU stay and were matched with a propensity score which was based on patient’s age and admission APACHE II and SOFA scores. The primary endpoint was in-hospital mortality. Other outcomes were considered secondary... Results A total of 1049 patients were eligible; 502 patients were included after propensity score matching (1:1 ratio). The 30-day (hazard ratio 0.75 (95% CI 0.58, 0.98), P = 0.03) and in-hospital mortality (hazard ratio 0.69 (95% CI 0.54, 0.89), P = 0.004) were significantly lower in patients who received statin therapy on multivariable cox proportional hazards regression analysis. Moreover, patients who received statin have a lower risk of hospital-acquired pneumonia (OR 0.48(95% CI 0.32, 0.69), P = < 0.001), lower levels of markers of inflammation on follow up and no increased risk of liver injury. Conclusion The use of statin during ICU stay in COVID-19 critically ill patients may have a beneficial role and survival benefits with a good safety profile.

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