High mortality among hospitalized adult patients with COVID-19 pneumonia in Peru: A single centre retrospective cohort study.
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ABSTRACT: Background
Peru is the country with the world's highest COVID-19 death rate per capita. Characteristics associated with increased mortality among adult patients with COVID-19 pneumonia in this setting are not well described.Methods
Retrospective, single-center cohort study including 1537 adult patients hospitalized with a diagnosis of SARS-CoV-2 pneumonia between May 2020 and August 2020 at a national hospital in Lima, Peru. The primary outcome measure was in-hospital mortality.Results
In-hospital mortality was 49.71%. The mean age was 60 ± 14.25 years, and 68.38% were males. We found an association between mortality and inflammatory markers, mainly leukocytes, D-dimer, lactate dehydrogenase, C-reactive protein and ferritin. A multivariate model adjusted for age, hypertension, diabetes mellitus, and corticosteroid use demonstrated that in-hospital mortality was associated with greater age (RR: 2.01, 95%CI: 1.59-2.52) and a higher level of oxygen requirement (RR: 2.77, 95%CI: 2.13-3.62). Conclusions: In-hospital mortality among COVID-19 patients in Peru is high and is associated with greater age and higher oxygen requirements.
SUBMITTER: Mas-Ubillus G
PROVIDER: S-EPMC8903290 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Publications
High mortality among hospitalized adult patients with COVID-19 pneumonia in Peru: A single centre retrospective cohort study.
Mas-Ubillus Guiliana G Ortiz Pedro J PJ Huaringa-Marcelo Jorge J Sarzo-Miranda Paola P Muñoz-Aguirre Patricia P Diaz-Ramos Alejandra A Arribasplata-Purizaca Kattia K Mendoza Doris D Rojas-Poma Juan J Marcelo-Ruiz Cristian C Ayala-Diaz Pedro P Hidalgo-Arroyo Edwin E Tupia-Cespedes Lourdes L
PloS one 20220308 3
<h4>Background</h4>Peru is the country with the world's highest COVID-19 death rate per capita. Characteristics associated with increased mortality among adult patients with COVID-19 pneumonia in this setting are not well described.<h4>Methods</h4>Retrospective, single-center cohort study including 1537 adult patients hospitalized with a diagnosis of SARS-CoV-2 pneumonia between May 2020 and August 2020 at a national hospital in Lima, Peru. The primary outcome measure was in-hospital mortality.< ...[more]
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Project description:BackgroundInformation on the clinical characteristics and outcomes of hospitalized Covid-19 patients with or without diabetes mellitus (DM) is limited in the Arab region. This study aims to fill this gap.MethodsIn this single-center retrospective study, medical records of hospitalized adults with confirmed Covid-19 [RT-PCR positive for SARS-CoV2] at King Saud University Medical City (KSUMC)-King Khaled University Hospital (KKUH), Riyadh, Saudi Arabia from May to July 2020 were analyzed. Clinical, radiological and serological information, as well as outcomes were recorded and analyzed.ResultsA total of 439 patients were included (median age 55 years; 68.3% men). The most prevalent comorbidities were vitamin D deficiency (74.7%), DM (68.3%), hypertension (42.6%) and obesity (42.2%). During hospitalization, 77 out of the 439 patients (17.5%) died. DM patients have a significantly higher death rate (20.5% versus 12.3%; p = 0.04) and lower survival time (p = 0.016) than non-DM. Multivariate cox proportional hazards regression model revealed that age [Hazards ratio, HR 3.0 (95% confidence interval, CI 1.7-5.3); p < 0.001], congestive heart failure [adjusted HR 3.5 (CI 1.4-8.3); p = 0.006], smoking [adjusted HR 5.8 (CI 2.0-17.2); p < 0.001], β-blocker use [adjusted HR 1.7 (CI 1.0-2.9); p = 0.04], bilateral lung infiltrates [adjusted HR 1.9 (CI 1.1-3.3); p = 0.02], creatinine > 90 µmol/l [adjusted HR 2.1 (CI 1.3-3.5); p = 0.004] and 25(OH)D < 12.5 nmol/l [adjusted HR 7.0 (CI 1.7-28.2); p = 0.007] were significant predictors of mortality among hospitalized Covid-19 patients. Random blood glucose ≥ 11.1 mmol/l was significantly associated with intensive care admission [adjusted HR 1.5 (CI 1.0-2.2); p = 0.04], as well as smoking, β-blocker use, neutrophil > 7.5, creatinine > 90 µmol/l and alanine aminotransferase > 65U/l.ConclusionThe prevalence of DM is high among hospitalized Covid-19 patients in Riyadh, Saudi Arabia. While DM patients have a higher mortality rate than their non-DM counterparts, other factors such as old age, congestive heart failure, smoking, β-blocker use, presence of bilateral lung infiltrates, elevated creatinine and severe vitamin D deficiency, appear to be more significant predictors of fatal outcome. Patients with acute metabolic dysfunctions, including hyperglycemia on admission are more likely to receive intensive care.
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Project description:BackgroundSecondary bacterial pneumonia is an important complication of seasonal influenza, but little data is available about impact on death and risk factors. This study identified risk factors for all-cause in-hospital mortality and secondary bacterial pneumonia among hospitalized adult patients with community-acquired influenza.MethodsA retrospective cohort study was performed at a tertiary teaching hospital in southwest China. The study cohort included all adult hospitalized patients with a laboratory-confirmed, community-acquired influenza virus infection during three consecutive influenza seasons from 2017 to 2020. Cause-specific Cox regression was used to analyze risk factors for mortality and secondary bacterial pneumonia, respectively, accounting for competing events (discharge alive and discharge alive or death without secondary bacterial pneumonia, respectively).ResultsAmong 174 patients enrolled in this study, 14.4% developed secondary bacterial pneumonia and 11.5% died during hospitalization. For all-cause in-hospital mortality, time-varying secondary bacterial pneumonia was a direct risk factor of death (cause-specific hazard ratio [csHR] 3.38, 95% confidence interval [CI] 1.25-9.17); underlying disease indirectly increased death risk through decreasing the hazard of being discharged alive (csHR 0.55, 95% CI 0.39-0.77). For secondary bacterial pneumonia, the final model only confirmed direct risk factors: age ≥ 65 years (csHR 2.90, 95% CI 1.27-6.62), male gender (csHR 3.78, 95% CI 1.12-12.84) and mechanical ventilation on admission (csHR 2.96, 95% CI 1.32-6.64).ConclusionsSecondary bacterial pneumonia was a major risk factor for in-hospital mortality among adult hospitalized patients with community-acquired influenza. Prevention strategies for secondary bacterial pneumonia should target elderly male patients and critically ill patients under mechanical ventilation.
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Project description:BackgroundThe novel coronavirus SARS-CoV-2 and its associated disease, COVID-19, have caused worldwide disruption, leading countries to take drastic measures to address the progression of the disease. As SARS-CoV-2 continues to spread, hospitals are struggling to allocate resources to patients who are most at risk. In this context, it has become important to develop models that can accurately predict the severity of infection of hospitalized patients to help guide triage, planning, and resource allocation.ObjectiveThe aim of this study was to develop accurate models to predict the mortality of hospitalized patients with COVID-19 using basic demographics and easily obtainable laboratory data.MethodsWe performed a retrospective study of 375 hospitalized patients with COVID-19 in Wuhan, China. The patients were randomly split into derivation and validation cohorts. Regularized logistic regression and support vector machine classifiers were trained on the derivation cohort, and accuracy metrics (F1 scores) were computed on the validation cohort. Two types of models were developed: the first type used laboratory findings from the entire length of the patient's hospital stay, and the second type used laboratory findings that were obtained no later than 12 hours after admission. The models were further validated on a multicenter external cohort of 542 patients.ResultsOf the 375 patients with COVID-19, 174 (46.4%) died of the infection. The study cohort was composed of 224/375 men (59.7%) and 151/375 women (40.3%), with a mean age of 58.83 years (SD 16.46). The models developed using data from throughout the patients' length of stay demonstrated accuracies as high as 97%, whereas the models with admission laboratory variables possessed accuracies of up to 93%. The latter models predicted patient outcomes an average of 11.5 days in advance. Key variables such as lactate dehydrogenase, high-sensitivity C-reactive protein, and percentage of lymphocytes in the blood were indicated by the models. In line with previous studies, age was also found to be an important variable in predicting mortality. In particular, the mean age of patients who survived COVID-19 infection (50.23 years, SD 15.02) was significantly lower than the mean age of patients who died of the infection (68.75 years, SD 11.83; P<.001).ConclusionsMachine learning models can be successfully employed to accurately predict outcomes of patients with COVID-19. Our models achieved high accuracies and could predict outcomes more than one week in advance; this promising result suggests that these models can be highly useful for resource allocation in hospitals.
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Project description:IntroductionStaphylococcus aureus bacteremia is associated with significant morbidity and mortality. Given the paucity of recent Canadian data, we estimated the mortality rate associated with S. aureus bacteremia in a tertiary care hospital and identified risk factors associated with mortality.MethodsWe retrospectively reviewed the records of adults with S. aureus bacteremia admitted to a tertiary care centre in southwestern Ontario between 2008 and 2012. Cox regression analysis was used to evaluate associations between predictor variables and all-cause, in-hospital, and 90-day postdischarge mortality.ResultsOf the 925 patients involved in the study, 196 (21.2%) died in hospital and 62 (6.7%) died within 90 days after discharge. Risk factors associated with in-hospital and all-cause mortality included age, sepsis (adjusted hazard ratio [adjusted HR] 1.49, 95% confidence interval [CI] 1.08-2.06, p = 0.02), admission to the intensive care unit (adjusted HR 3.78, 95% CI 2.85-5.02, p < 0.0001), hepatic failure (adjusted HR 3.36, 95% CI 1.91-5.90, p < 0.0001) and metastatic cancer (adjusted HR 2.58, 95% CI 1.77-3.75, p < 0.0001). Methicillin resistance, hepatic failure, cerebrovascular disease, chronic obstructive pulmonary disease and metastatic cancer were associated with postdischarge mortality.InterpretationThe all-cause mortality rate in our cohort was 27.9%. Identification of predictors of mortality may guide empiric therapy and provide prognostic clarity for patients with S. aureus bacteremia.
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Project description:BackgroundFirst reported case of Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) in Kazakhstan was identified in March 2020. Many specialized tertiary hospitals in Kazakhstan including National Research Cardiac Surgery Center (NRCSC) were re-organized to accept coronavirus disease 2019 (COVID-19) infected patients during summer months of 2020. Although many studies from worldwide reported their experience in treating patients with COVID-19, there are limited data available from the Central Asia countries. The aim of this study is to identify predictors of mortality associated with COVID-19 in NRCSC tertiary hospital in Nur-Sultan, Kazakhstan.MethodsThis is a retrospective cohort study of patients admitted to the NRCSC between June 1st-August 31st 2020 with COVID-19. Demographic, clinical and laboratory data were collected from electronic records. In-hospital mortality was assessed as an outcome. Patients were followed-up until in-hospital death or discharge from the hospital. Descriptive statistics and factors associated with mortality were assessed using univariate and multivariate logistic regression models.ResultsTwo hundred thirty-nine admissions were recorded during the follow-up period. Mean age was 57 years and 61% were males. Median duration of stay at the hospital was 8 days and 34 (14%) patients died during the hospitalization. Non-survivors were more likely to be admitted later from the disease onset, with higher fever, lower oxygen saturation and increased respiratory rate compared to survivors. Leukocytosis, lymphopenia, anemia, elevated liver and kidney function tests, hypoproteinemia, elevated inflammatory markers (C-reactive protein (CRP), ferritin, and lactate dehydrogenase (LDH)) and coagulation tests (fibrinogen, D-dimer, international normalized ratio (INR), and activated partial thromboplastin time (aPTT)) at admission were associated with mortality. Age (OR 1.2, CI:1.01-1.43), respiratory rate (OR 1.38, CI: 1.07-1.77), and CRP (OR 1.39, CI: 1.04-1.87) were determined to be independent predictors of mortality.ConclusionThis study describes 14% mortality rate from COVID-19 in the tertiary hospital. Many abnormal clinical and laboratory variables at admission were associated with poor outcome. Age, respiratory rate and CRP were found to be independent predictors of mortality. Our finding would help healthcare providers to predict the risk factors associated with high risk of mortality. Further investigations involving large cohorts should be provided to support our findings.
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Project description:During the COVID-19 pandemic, the high prevalence of comorbidities and the disparities between the public and private health subsystems in Mexico substantially contributed to the severe impact of the disease. The objective of this study was to evaluate and compare the risk factors at admission for in-hospital mortality of patients with COVID-19. A 2-year retrospective cohort study of hospitalized adult patients with COVID-19 pneumonia was conducted at a private tertiary care center. The study population consisted of 1258 patients with a median age of 56 ± 16.5 years, of whom 1093 recovered (86.8%) and 165 died (13.1%). In the univariate analysis, older age (p < 0.001), comorbidities such as hypertension (p < 0.001) and diabetes (p < 0.001), signs and symptoms of respiratory distress, and markers of acute inflammatory response were significantly more frequent in non-survivors. The multivariate analysis showed that older age (p < 0.001), the presence of cyanosis (p = 0.005), and previous myocardial infarction (p = 0.032) were independent predictors of mortality. In the studied cohort, the risk factors present at admission associated with increased mortality were older age, cyanosis, and a previous myocardial infarction, which can be used as valuable predictors for patients' outcomes. To our knowledge, this is the first study analyzing predictors of mortality in COVID-19 patients attended in a private tertiary hospital in Mexico.
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Project description:BackgroundSevere influenza, especially influenza pneumonia, causes large numbers of deaths each year. Some patients who develop severe influenza have no known risk factors. In this study we investigated risk factors for mortality of patients with influenza A-related pneumonia who have different basic conditions. We also evaluated the power of pneumonia severity assessment tools in Chinese patients hospitalized with influenza A-related pneumonia. Together, these results could provide a basis for a screening method that has improved ability for the early identification of critical patients who will have poor prognoses in clinical practice.MethodsThis single-center, retrospective case-control study included 152 adult patients with severe influenza over six influenza seasons. Data for diagnoses and demographics, as well clinical data, laboratory findings, treatment methods, 30-day and 60-day outcomes of the patients were collected. Patients who had any of the risk factors for severe influenza were included in the high-risk group, and those that had no known risk factors were included in the low-risk group.ResultsThe PSI, CURB-65 and PIRO-CAP tools all underestimated the mortality rate of patients hospitalized with influenza A-related pneumonia, and this underestimate was more pronounced for low-risk patients. D-dimer (Odds ratio [OR] = 1.052, 95% confidence interval [CI] 1.001-1.106, p = 0.045) and direct bilirubin (OR = 1.143, 95%CI 1.049-1.246, p = 0.002) were independent risk factors for mortality of patients with influenza A-related pneumonia. When used in combination with ferritin and D-dimer, the area under receiver operator characteristic curve (AUCROC) was 0.851 (95%CI 0.780-0.922, p < 0.001), 0.840 (95%CI 0.763-0.916, p < 0.001) and 0.829 (95%CI 0.748-0.911, p < 0.001) for PSI, CURB-65 and PIRO-CAP, respectively, which was higher than that obtained using PSI, CURB-65 and PIRO-CAP alone.ConclusionsThe findings demonstrate that currently used community-acquired pneumonia (CAP) scoring systems could underestimate the risk of influenza A-related pneumonia mortality. D-dimer was shown to be an independent risk factor of mortality for influenza A-related pneumonia in hospitalized patients, and a combination of D-dimer with ferritin could improve the predictive value of PSI, CURB-65 and PIRO-CAP for adverse prognoses of patients with influenza A-related pneumonia.
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