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Independent predictors of in-hospital mortality and the need for intensive care in hospitalized non-critical COVID-19 patients: a prospective cohort study.

ABSTRACT: One of the most helpful strategies to deal with ongoing coronavirus pandemics is to use some prudence when treating patients infected with SARS-CoV-2. We aimed to evaluate the clinical, demographic, and laboratory parameters that might have predictive value for in-hospital mortality and the need for intensive care and build a model based on them. This study was a prospective, observational, single-center study including non-critical patients admitted to COVID-19 wards. Besides classical clinic-demographic features, basic laboratory parameters obtained on admission were tested, and then new models for each outcome were developed built on the most significant variables. Receiver operating characteristics (ROC) analyses were performed by calculating each model's probability. A total of 368 non-critical hospitalized patients were recruited, the need for ICU care was observed in 70 patients (19%). The total number of patients who died in either ICU or wards was 39 (10.6%). The first two models (based on clinical features and demographics) were developed to predict ICU and death, respectively; older age, male sex, active cancer, and low baseline saturation were noted to be independent predictors. The area under the curve values of the first two models were noted 0.878 and 0.882 (p < .001; confidence interval [CI] 95% [0.837-0.919], p < .001; CI 95% [0.844-0.922]). Following two models, the third and fourth were based on laboratory parameters with clinic-demographic features. Initial lower sodium and lower albumin levels were determined as independent factors in predicting the need for ICU care; higher blood urea nitrogen and lower albumin were independent factors in predicting in-hospital mortality. The area under the curve values of the third and fourth model was noted 0.938 and 0.929, respectively (p < .001; CI 95% [0.912-0.965], p < .001; CI 95% [0.895-962]). By integrating the widely available blood tests results with simple clinic demographic data, non-critical patients can be stratified according to their risk level. Such stratification is essential to filter the patients' non-critical underlying diseases and conditions that can obfuscate the physician's predictive capacity.

SUBMITTER: Basaran NC

PROVIDER: S-EPMC9122556 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The impact of the coronavirus disease 2019 (COVID-19) pandemic among patients with chronic liver disease is unknown. Given the high prevalence of nonalcoholic fatty liver disease (NAFLD), we determined the predictors of mortality and hospital resource use among patients with NAFLD admitted with COVID-19 by using electronic medical records data for adult patients with COVID-19 hospitalized in a multihospital health system who were discharged between March and December 2020. NAFLD was diagnosed by imaging or liver biopsy without other liver diseases. Charlson's comorbidity index (CCI) and Elixhauser comorbidity index (ECI) scores were calculated. In the study sample, among the 4,835 patients hospitalized for COVID-19, 553 had NAFLD (age: 55 ± 16 years, 51% male, 17% White, 11% Black, 58% Hispanic, 8% Asian, 5% from congregated living, 58% obese, 15% morbid obesity [body mass index ≥ 40], 51% type 2 diabetes, 63% hypertension, mean [SD] baseline CCI of 3.9 [3.2], and baseline ECI of 13.4 [11.3]). On admission, patients with NAFLD had more respiratory symptoms, higher body temperature and heart rate, higher alanine aminotransferase and aspartate aminotransferase than non-NAFLD controls (n = 2,736; P < 0.05). Of the patients with NAFLD infected with COVID-19, 3.9% experienced acute liver injury. The NAFLD group had significantly longer length of stay, intensive care unit use, and mechanical ventilation, with a crude inpatient mortality rate of 11%. In multivariate analysis, independent predictors of inpatient mortality among patients with NAFLD infected with COVID-19 were older age, morbid obesity, ECI score ≥ 11, higher Fibrosis-4 Index (FIB-4) score, and oxygen saturation <90% (all P < 0.05), but not sex, race/ethnicity, or any individual comorbidity (all P > 0.05). Conclusion: Patients with NAFLD infected with COVID-19 tend to be sicker on admission and require more hospital resource use. Independent predictors of mortality included higher FIB-4 and multimorbidity scores, morbid obesity, older age, and hypoxemia on admission.

Project description:BackgroundThe neonatal period is the most vulnerable time for survival in which children face the highest risk of dying in their lives. Neonatal mortality (NM) remains a global public concern, especially in sub-Saharan African (SSA) countries. Although, better progress has been made in reducing NM before 2016, Ethiopia is currently one of the top ten countries affected by NM. Studies are limited to secondary data extraction in Ethiopia which focus only on survival status during admission, and no study has been conducted in the study area in particular.ObjectiveTo assess the survival status and predictors of neonatal mortality among neonates admitted to the NICU of WURH and Nekemte Specialized Hospital, Western Ethiopia.MethodsAn institution-based prospective cohort study was conducted among a cohort of 412 neonates admitted to the NICU of WURH and Nekemte Specialized Hospital from September 1, 2020 to December 30, 2020. All neonates consecutively admitted to the NICU of the two hospitals during the study period were included in the study. Data entry was performed using Epidata version 3.0 and the analysis was performed using STATA version 14. A Kaplan Meier survival curve was constructed to estimate the cumulative survival probability. A cox proportional hazards regression model was used to identify the predictors of NM. Hazard Ratios with 95% CI were computed and all the predictors associated with the outcome variable at p-value ≤ 0.05 in the multivariable cox proportional hazards analysis were declared as a significant predictor of NM.ResultsA total of 412 neonates were followed for a median of 27 days with an IQR of 22-28 days. During the follow-up period, a total of 9249 person day observations (PDO) were detected. At the end of follow-up, 15.3% of neonates died with an overall incidence rate of death 6.81/1000 PDO. The median time to death was 10 days, and the highest incidence rate of death was observed during the first week of the neonatal period. The study found that rural residence (AHR = 2.04, 95%CI: 1.14, 3.66), lack of ANC visits (AHR = 7.77, 95%CI: 3.99, 15.11), neonatal hypothermia (AHR = 3.04, 95%CI: 1.36, 6.80), and delayed initiation of breastfeeding (AHR = 2.26, 95% CI: 1.12, 4.56) as independent predictors of NM. However, a decreased number of pregnancies decrease the risk of NM.Conclusions and recommendationsThe incidence rate of neonatal death was high particularly in the first week of life in the study area. The study found that lack of ANC visit, neonatal hypothermia, increased number of pregnancies, rural residence, and delayed initiation of breastfeeding positively predicted NM. Therefore, there is a need to encourage programs that enhance ANC visits for pregnant mothers and community-based neonatal survival strategies, particularly for countryside mothers.

Project description:BackgroundPerioperative pediatric mortality is significantly higher in low-resource countries due to a scarcity of well-trained professionals and a lack of well-equipped pediatric perioperative services. There has been little research on pediatric mortality in low-income countries. Therefore, this study aimed to assess the incidence of perioperative pediatric mortality and its predictors in 28-day follow-up.MethodsThe data were collected using REDCap, an electronic data collection tool, between June 01, 2019 and July 01, 2021. This study includes pediatric patients aged 0 to 17 years who underwent surgery in Tibebe Ghion Specialized Hospital over 28 days with a total of 1171 patients. STATA version 17 software was used for data analysis. Log-rank tests were fitted to explore survival differences. After bivariable and multivariable Cox regression analysis, an Adjusted Hazard Ratio (AHR) with a 95% Confidence Interval (CI) was reported to declare the strength of association and statistical significance.ResultsThere were 35 deaths in the cohort of 1171 pediatric patients. Twenty of the deaths were in neonates. The overall perioperative mortality among pediatric patients was 2.99%, with an incidence rate of 1.11 deaths per 1000 person day observation (95% CI 0.79, 1.54). The neonatal age group had an AHR = 9.59, 95% CI 3.77, 24.3), transfusion had an AHR = 2.6, 95% CI 1.11, 6.09), and the America Society of Anesthesiology physical status classification III and above had an AHR = 4.39, 95% CI 1.61, 11.9 were found the significant predictors of perioperative pediatric mortality.ConclusionsIn this study, the perioperative mortality of pediatric patients was high in the 28-day follow-up. Neonatal age, transfusion, and America Society of Anesthesiology physical status III and above were significant predictors of pediatric mortality. Therefore, perioperative surgical teams should give special attention to neonates, the America Society of Anesthesiology physical status III and above, and transfusion to reduce pediatric mortality.

Project description:Background and aimsStroke is the second leading cause of death around the globe. Studies examining the predictors of in-hospital mortality and the impact of complications on early outcome of acute ischemic stroke are scant. The aim of this study was to identify predictors of in-hospital mortality in patients with acute ischemic stroke.MethodsThis was a prospective, single-center study of patients with acute ischemic stroke consecutively admitted to the Neurology Department of a general hospital during a 2-year period (from January 1, 2010 to December 31, 2011). Prospective data from this single-center study included variables related to sociodemographics, comorbidities, and medical complications, together with in-hospital mortality. Since stroke mortality may impact differently by sex and is also influenced by hospital length of stay, we proceeded to stratify by these variables.ResultsSix-hundred and seventy-three patients were included. Overall, in-hospital mortality rate was 7.13%. Stratifying by length of stay in-hospital (< 7 days and ≥ 7 days), we observed that within the first week, overall mortality was related to a history of previous stroke, higher stroke severity, and to cardiovascular and respiratory complications. After 7 days, the main factor independently associated with overall in-hospital mortality was stroke severity (National Institutes of Health Stroke Scale (NIHSS) ≥ 14, odds ratio (OR): 17.15; 95% CI, 3.06-96.07).Stratifying by sex, we observed that females had a worse outcome if there was a history of prior stroke (OR: 3.29; 95% CI, 1.19-9.10), higher stroke severity (NIHSS ≥ 14, OR: 16.63; 95% CI, 4.66-59.31), and cardiovascular complications (OR: 29.70; 95% CI, 5.70-154.8). Among men, stroke severity (NIHSS ≥ 14, OR: 23.19; 95% CI, 5.69-94.56), respiratory infections (OR: 3.84; 95% CI, 1.32-11.20), and older age had significant negative impact.ConclusionsStroke severity and potentially modifiable complications (respiratory infections and cardiovascular complications) confer an increased risk of in-hospital death in both women and men, particularly during the first week of admission.

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Independent predictors of in-hospital mortality and the need for intensive care in hospitalized non-critical COVID-19 patients: a prospective cohort study.

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