Association between time in range of relative normoglycemia and in-hospital mortality in critically ill patients: a single-center retrospective study.
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ABSTRACT:
SUBMITTER: Okazaki T
PROVIDER: S-EPMC9277973 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Independent predictors of mortality and transfusion therapy in polytrauma patients from the Chinese population remain unknown. Here, we aimed to identify these predictors by retrospectively collecting and analyzing vital signs and laboratory results for 408 critically ill patients suffering from polytrauma who were treated in Affiliated Kunshan Hospital of Jiangsu University, Jiangsu Province, China from January 2020 to December 2021. We identified risk factors for mortality and transfusion therapy using logistic regression analysis. As a results, we enrolled a total of 408 polytrauma patients, with a male-to-female ratio of 2:1, a mean age of 49.02 ± 16.84 years, a mortality rate of 15.9 %, and a blood transfusion rate of 45.8 %. The multivariate logistic regression showed that decreased Glasgow Coma Scale (GCS) score (Odds ratio (OR) = 0.72, 95 % confidence interval (95%CI): 0.63-0.83, P < 0.001), decreased base excess (BE) (OR = 0.77, 95%CI: 0.67-0.87, P < 0.001), and increased Injury Severity Score (ISS) (OR = 1.12, 95%CI: 1.06-1.17, P < 0.001) were independent risk factors for the mortality. In addition, increased GCS score (OR = 1.17, 95%CI: 1.03-1.35, P = 0.020), increased heart rate (OR = 1.05, 95%CI: 1.04-1.07, P < 0.001), decreased systolic blood pressure (SBP) (OR = 0.97, 95%CI: 0.96-0.99, P < 0.001), increased peripheral oxygen saturation (SpO2) (OR = 1.10, 95%CI: 1.04-1.16, P = 0.002), decreased serum lactate (OR = 0.58, 95%CI: 0.42-0.79, P = 0.001), decreased BE (OR = 0.49, 95%CI: 0.39-0.62, P < 0.001), and increased ISS (OR = 1.25, 95%CI: 1.18-1.33, P < 0.001) were independent risk factors for blood transfusion. The area under receiver operating characteristic curves (AUROCs) of the model to predict mortality and blood transfusion were 0.976 (95%CI: 0.960-0.992, P < 0.001) and 0.973 (95%CI: 0.958-0.987, P < 0.001). In conclusion, decreased BE level was significantly associated with all-cause mortality in polytrauma patients. BE, ISS, and GCS might be independent important predictors for mortality and blood transfusion of polytrauma patients.
| S-EPMC10873658 | biostudies-literature
Project description:Background and purposeThere was little evidence to study the relationship between hypocalcemia and mortality among critically ill patients with intracerebral hemorrhage (ICH) aged ≥16 years. This study aimed to determine the potential association between hypocalcemia and in-hospital and ICU mortality in patients with ICH in the United States.MethodsWe analyzed 1,954 patients with ICH from the e-Intensive Care Unit Collaborative Research Database and divided them into hypocalcemia and non-hypocalcemia groups. Hypocalcemia was defined as albumin-adjusted total calcium below 8.4 mg/dl. The primary and secondary outcomes were hospital and ICU mortality, respectively. We performed multivariable regression and subgroup analyses to evaluate the association of hypocalcemia with hospital and ICU mortality. Cumulative survival rate analysis was performed using Kaplan-Meier curves with log-rank statistics.ResultsWe enrolled 1,954 patients with ICH who had been hospitalized in ICU for >24 h and were older than 16 years (average age, 61.8 years; men, 56.7%). We noted that 373 (19%) hospital mortality occurred, including 235 (12%) ICU mortality. In this sample, 195 patients had hypocalcemia. Multivariable logistic regression analyses showed that hypocalcemia was associated with a 67% increased risk of in-hospital and a 72% increased risk of ICU mortality. This association was consistent across subgroup analyses.ConclusionsHypocalcemia was associated with a high risk of hospital and ICU mortality among critically ill patients with ICH. Future prospective, randomized, controlled studies are needed to confirm our results.
| S-EPMC9868589 | biostudies-literature
Project description:Transfusion therapy is associated with increased morbidity, mortality and costs. Conventional coagulation tests (CCT) are weak bleeding predictors, poorly reflecting coagulation in vivo. Thromboelastometry (ROTEM) provides early identification of coagulation disorders and can guide transfusion therapy by goals, reducing blood components transfusion.The aim of this study is to describe coagulation profile of critically ill patients using ROTEM and evaluate the association between CCT and thromboelastometry.This is a retrospective, observational study conducted in medical-surgical intensive care unit (ICU). Adult patients (?18 years) admitted to ICU between November 2012 and December 2014, in whom ROTEM analyses were performed for bleeding management were included in this study. The first ROTEM and CCT after ICU admission were recorded simultaneously. Additionally, we collected data on blood components transfusion and hemostatic agents immediately after laboratory tests results.The study included 531 patients. Most ROTEM tests showed normal coagulation profile [INTEM (54.8%), EXTEM (54.1%) and FIBTEM (53.3%)] with divergent results in relation to CCT: low platelet count (51.8% in INTEM and 55.9% in EXTEM); prolonged aPTT (69.9% in INTEM and 63.7% in EXTEM) and higher INR (23.8% in INTEM and 27.4% in EXTEM). However 16,7% of patients with normocoagulability in ROTEM received platelet concentrates and 10% fresh frozen plasma.The predominant ROTEM profile observed in this sample of critically ill patients was normal. In contrast, CCT suggested coagulopathy leading to a possibly unnecessary allogenic blood component transfusion. ROTEM test may avoid inappropriate allogeneic blood products transfusion in these patients.
| S-EPMC5819777 | biostudies-literature
Project description:BackgroundPatients infected with severe acute respiratory syndrome coronavirus (SARS-CoV-2) can develop severe illness necessitating intensive care admission. Critically ill patients are susceptible for the development of secondary bacterial infections. Due to a combination of virus- and drug-induced immunosuppression, critically ill patients with corona virus disease 2019 (COVID-19) may even have a higher risk of developing a secondary infection. These secondary infections can aggravate the severity of illness and increase the risk of death. Further research on secondary infections in COVID-19 patients is essential. Therefore, the objective of this study was to investigate the incidence and associated risk factors of secondary bacterial infections and to identify the most common groups of pathogens in critically ill COVID-19 patients.MethodsThis mono-center, retrospective observational cohort study was performed at the intensive care unit (ICU) of the Jessa Hospital, Hasselt, Belgium. All adult COVID-19 patients admitted to the ICU from 13th March 2020 until 17th October 2020, were eligible for inclusion in the study. Data from the resulting 116 patients were prospectively entered into a customized database. The resulting database was retrospectively reviewed to investigate three types of secondary bacterial infections (secondary pneumonia, bloodstream infections of unknown origin, catheter-related sepsis).ResultsOf 94 included patients, 68% acquired at least one of the studied secondary bacterial infections during their ICU stay. Almost two thirds of patients (65.96%, n = 62) acquired a secondary pneumonia, whereas 29.79% (n = 28) acquired a bacteremia of unknown origin and a smaller proportion of patients (14.89%, n = 14) acquired a catheter-related sepsis. Male gender (P = 0.05), diabetes mellitus (P = 0.03) and the cumulative dose of corticosteroids (P = 0.004) were associated with increased risk of secondary bacterial infection. The most common pathogens detected in the cultures of patients with secondary pneumonia were Gram-negative bacilli. Bacteremia of unknown origin and catheter-related sepsis were mostly caused by Gram-positive cocci.ConclusionThis study confirms that the incidence of secondary bacterial infections is very high in critically ill COVID-19 patients. These patients are at highest risk of developing secondary pneumonia. Male gender, a history of diabetes mellitus and the administration of corticosteroids were associated with increased risk of secondary bacterial infection.
| S-EPMC8890021 | biostudies-literature
Project description:BackgroundWarfarin is a widely used anticoagulant with a narrow therapeutic index and large interpatient variability in the therapeutic dose. Warfarin sensitivity has been reported to be associated with increased incidence of international normalized ratio (INR) > 5. However, whether warfarin sensitivity is a risk factor for adverse outcomes in critically ill patients remains unknown. In the present study, we aimed to evaluate the utility of different machine learning algorithms for the prediction of warfarin sensitivity and to determine the impact of warfarin sensitivity on outcomes in critically ill patients.MethodsNine different machine learning algorithms for the prediction of warfarin sensitivity were tested in the International Warfarin Pharmacogenetic Consortium cohort and Easton cohort. Furthermore, a total of 7,647 critically ill patients was analyzed for warfarin sensitivity on in-hospital mortality by multivariable regression. Covariates that potentially confound the association were further adjusted using propensity score matching or inverse probability of treatment weighting.ResultsWe found that logistic regression (AUC = 0.879, 95% CI: 0.834-0.924) was indistinguishable from support vector machine with a linear kernel, neural network, AdaBoost and light gradient boosting trees, and significantly outperformed all the other machine learning algorithms. Furthermore, we found that warfarin sensitivity predicted by the logistic regression model was significantly associated with worse in-hospital mortality in critically ill patients with an odds ratio (OR) of 1.33 (95% CI, 1.01-1.77).ConclusionsOur data suggest that the logistic regression model is the best model for the prediction of warfarin sensitivity clinically and that warfarin sensitivity is likely to be a risk factor for adverse outcomes in critically ill patients.
| S-EPMC9070894 | biostudies-literature
Project description:BackgroundWhile time in targeted blood glucose range (TIR) 70-140 mg/dL is a known factor associated with mortality in critically ill patients, it remains unclear whether TIR is associated with 28-day mortality under the glycemic control with a less tight target glucose range of 70-180 mg/dL. We aimed to examine whether TIR 70-180 mg/dL was associated with 28-day mortality.MethodsThis is a retrospective cohort study using data from a tertiary care center in Japan collected from January 2016 through October 2019. We included adult patients (aged ≥20 years) admitted to the ICU. We excluded patients 1) with diabetic ketoacidosis patients, 2) discharged within 48 hours, 3) with repeated ICU admissions. We calculated TIR 70-180 mg/dL using the measured blood glucose values (≥3 times per day). The primary outcome was 28-day mortality. We examined the association between TIR and 28-day mortality using a logistic regression and Cox proportional hazard models with a stratification by glycosylated hemoglobin (HbA1c) level of 6.5%. Additionally, we repeated the analyses using the TIR category to assess the optimal TIR. For the sensitivity analysis, we repeated the primary analysis using TIR during the first three days from ICU admission.ResultsOf 1,230 patients, the median age was 72 years, 65% were male, and 250 patients (20%) had HbA1c ≥6.5% on admission. In patients with HbA1c <6.5%, TIR <80% was associated with an increased risk of 28-day mortality, with an adjusted odds ratio (OR) of 1.88 (95%CI: 1.36-2.61). Likewise, when using 10% incremental TIR as a categorical variable, lower TIR was associated with a worse 28-day mortality compared with TIR ≥90% (e.g., adjusted OR of TIR <60%, 3.62 [95%CI 2.36-5.53]). Similar associations were found in the analyses using Cox proportional hazards model and using TIR during the first three days. By contrast, in patients with HbA1c ≥6.5%, there was no consistent association of TIR with 28-day mortality.ConclusionsWe found that lower TIR 70-180 mg/dL was associated with a higher 28-day mortality in critically ill patients with HbA1c <6.5%, whereas there was no consistent association in patients with HbA1c ≥6.5%.
| S-EPMC8158903 | biostudies-literature
Project description:ObjectivesTo identify factors influencing the mortality risk in critically ill patients with COVID-19, and to develop a risk prediction score to be used at admission to intensive care unit (ICU).DesignA multicentre cohort study.Setting and participants1542 patients with COVID-19 admitted to ICUs in public hospitals of Abu Dhabi, United Arab Emirates between 1 March 2020 and 22 July 2020.Main outcomes and measuresThe primary outcome was time from ICU admission until death. We used competing risk regression models and Least Absolute Shrinkage and Selection Operator to identify the factors, and to construct a risk score. Predictive ability of the score was assessed by the area under the receiver operating characteristic curve (AUC), and the Brier score using 500 bootstraps replications.ResultsAmong patients admitted to ICU, 196 (12.7%) died, 1215 (78.8%) were discharged and 131 (8.5%) were right-censored. The cumulative mortality incidence was 14% (95% CI 12.17% to 15.82%). From 36 potential predictors, we identified seven factors associated with mortality, and included in the risk score: age (adjusted HR (AHR) 1.98; 95% CI 1.71 to 2.31), neutrophil percentage (AHR 1.71; 95% CI 1.27 to 2.31), lactate dehydrogenase (AHR 1.31; 95% CI 1.15 to 1.49), respiratory rate (AHR 1.31; 95% CI 1.15 to 1.49), creatinine (AHR 1.19; 95% CI 1.11 to 1.28), Glasgow Coma Scale (AHR 0.70; 95% CI 0.63 to 0.78) and oxygen saturation (SpO2) (AHR 0.82; 95% CI 0.74 to 0.91). The mean AUC was 88.1 (95% CI 85.6 to 91.6), and the Brier score was 8.11 (95% CI 6.74 to 9.60). We developed a freely available web-based risk calculator (https://icumortalityrisk.shinyapps.io/ICUrisk/).ConclusionIn critically ill patients with COVID-19, we identified factors associated with mortality, and developed a risk prediction tool that showed high predictive ability. This tool may have utility in clinical settings to guide decision-making, and may facilitate the identification of supportive therapies to improve outcomes.
| S-EPMC8392735 | biostudies-literature
Project description:Evidence regarding the relationship between age-adjusted Charlson comorbidity index (ACCI) and in-hospital mortality is limited. Therefore, the present study investigated whether there was an independent association between ACCI and in-hospital mortality in critically ill patients with cardiogenic shock (CS) after adjusting for other covariates (age, sex, history of disease, scoring system, in-hospital management, vital signs at presentation, laboratory findings and vasopressors). ACCI, calculated retrospectively after hospitalization between 2008 and 2019, was derived from intensive care unit (ICU) admissions at the Beth Israel Deaconess Medical Center (Boston, MA, USA). Patients with CS were classified into two categories based on predefined ACCI scores (low, <8; high, ≥8). Based on baseline ACCI, the risk of in-hospital mortality in patients with CS was calculated using a multivariate Cox proportional risk model, and the threshold effect was calculated using a two-piece linear regression model. The in-hospital mortality rate was ~1.5 times greater in the ACCI high group compared with that in the ACCI low group [hazard ratio (HR)=1.45; 95% confidence interval (CI), 1.14-1.86]. Additional analysis showed that ACCI had a curvilinear association with in-hospital mortality risk in patients with CS, with a saturation effect predicted at 4.5. When ACCI was >4.5, the risk of in-hospital CS death increased significantly with increasing ACCI (HR=1.122; 95% CI, 1.054-1.194). Overall, ACCI was an independent predictor of in-hospital mortality in ICU patients with CS. A non-linear relationship was revealed between ACCI and in-hospital mortality, where in-hospital mortality increased significantly when ACCI was >4.5.
| S-EPMC10203756 | biostudies-literature
Project description:Critically-ill patients with end-stage liver disease (ESLD) are at high risk for death during intensive care unit hospitalization, and currently available prognostic models have limited accuracy in this population. We aimed to identify variables associated with in-hospital mortality among critically ill ESLD patients and to develop and validate a simple, parsimonious model for bedside use.We performed a retrospective chart review of 653 intensive care unit admissions for ESLD patients; modeled in-hospital mortality using multivariable logistic regression; and compared the predictive ability of several different models using the area under receiver operating characteristic (AU-ROC) curves.Multivariable predictors of in-hospital mortality included Model for End-stage Liver Disease (MELD) score, Acute Physiology and Chronic Health Evaluation (APACHE) II score, mechanical ventilation, and gender; there was also an interaction between MELD score and gender (P < .02). MELD alone had better discrimination (AU-ROC 0.83) than APACHE II alone (AU-ROC 0.76), and adding mechanical ventilation to MELD achieved the single largest increase in model discrimination (AU-ROC 0.85; P < .01). In a parsimonious, 2-predictor model, higher MELD scores (OR 1.14 per 1-point increase; 95% CI 1.11-1.16), and mechanical ventilation (OR 6.20; 95% CI 3.05-12.58) were associated with increased odds of death. Model discrimination was also excellent in the validation cohort (AU-ROC 0.90).In critically ill ESLD patients, a parsimonious model including only MELD and mechanical ventilation is more accurate than APACHE II alone for predicting in-hospital mortality. This simple bedside model can provide clinicians and patients with valuable prognostic information for medical decision-making.
| S-EPMC4405501 | biostudies-literature
Project description:Objective:Evaluate host and pathogen factors associated with mortality in those with hospital acquired infections (HAI) in a tertiary intensive care unit in Brazil. Methods:Observational and analytical cohort single center study in a general intensive care unit (ICU) in Northeastern Brazil between January 2016 and August 2018, including those over 18 years of age admitted to the ICU found to have a HAI. Results:A total of 165 patients were included, with a mean age of 72 years and male predominance (53.3%) and observed mortality of 46%. Mortality in those with HAI was significantly associated with older age, increased ICU length of stay and readmission to the ICU in univariate analysis. Multivariate analysis revealed that development of septic shock and obtundation during ICU admission was significantly associated with an increased risk of death (OR: 6.94, 95% CI 1.23-39.27, OR: 2.48, 95% CI 1.17-5.29, respectively). A trend towards mortality risk was noted in those with increased age and prior cardiovascular disease. Surprisingly, mortality risk was independent of site of infection, type of pathogen and antibiotic resistance. Furthermore, having more than one HAI over the course of the ICU admission did not impact mortality. Conclusion:Risk of death in those with HAI is associated with obtundation and septic shock, in addition to vasopressor use. Host factors, rather than pathogen-specific characteristics or infecting site, impact risk of death related to HAI in the ICU.
| S-EPMC7430765 | biostudies-literature