Dataset Information

Risk factors for in-hospital mortality in laboratory-confirmed COVID-19 patients in the Netherlands: A competing risk survival analysis.

ABSTRACT:

Background

To date, survival data on risk factors for COVID-19 mortality in western Europe is limited, and none of the published survival studies have used a competing risk approach. This study aims to identify risk factors for in-hospital mortality in COVID-19 patients in the Netherlands, considering recovery as a competing risk.

Methods

In this observational multicenter cohort study we included adults with PCR-confirmed SARS-CoV-2 infection that were admitted to one of five hospitals in the Netherlands (March to May 2020). We performed a competing risk survival analysis, presenting cause-specific hazard ratios (HRCS) for the effect of preselected factors on the absolute risk of death and recovery.

Results

1,006 patients were included (63.9% male; median age 69 years, IQR: 58-77). Patients were hospitalized for a median duration of 6 days (IQR: 3-13); 243 (24.6%) of them died, 689 (69.9%) recovered, and 74 (7.4%) were censored. Patients with higher age (HRCS 1.10, 95% CI 1.08-1.12), immunocompromised state (HRCS 1.46, 95% CI 1.08-1.98), who used anticoagulants or antiplatelet medication (HRCS 1.38, 95% CI 1.01-1.88), with higher modified early warning score (MEWS) (HRCS 1.09, 95% CI 1.01-1.18), and higher blood LDH at time of admission (HRCS 6.68, 95% CI 1.95-22.8) had increased risk of death, whereas fever (HRCS 0.70, 95% CI 0.52-0.95) decreased risk of death. We found no increased mortality risk in male patients, high BMI or diabetes.

Conclusion

Our competing risk survival analysis confirms specific risk factors for COVID-19 mortality in a the Netherlands, which can be used for prediction research, more intense in-hospital monitoring or prioritizing particular patients for new treatments or vaccination.

SUBMITTER: Nijman G

PROVIDER: S-EPMC7997038 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Risk factors for in-hospital mortality in laboratory-confirmed COVID-19 patients in the Netherlands: A competing risk survival analysis.

Nijman Gerine G Wientjes Maike M Ramjith Jordache J Janssen Nico N Hoogerwerf Jacobien J Abbink Evertine E Blaauw Marc M Dofferhoff Ton T van Apeldoorn Marjan M Veerman Karin K de Mast Quirijn Q Ten Oever Jaap J Hoefsloot Wouter W Reijers Monique H MH van Crevel Reinout R van de Maat Josephine S JS

PloS one 20210326 3

<h4>Background</h4>To date, survival data on risk factors for COVID-19 mortality in western Europe is limited, and none of the published survival studies have used a competing risk approach. This study aims to identify risk factors for in-hospital mortality in COVID-19 patients in the Netherlands, considering recovery as a competing risk.<h4>Methods</h4>In this observational multicenter cohort study we included adults with PCR-confirmed SARS-CoV-2 infection that were admitted to one of five hosp ...[more]

PMID: 33770140

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Project description:COVID-19 poses dire threats for low and middle-income countries (LMICs). Yet, there remains limited rigorous evidence describing the characteristics and outcomes of hospitalized patients for LMICs, and often the evidence was based on small samples and/or unicentric. The objective of this study was to examine risk factors of COVID-19 mortality in Argentina, a hard-hit middle-income Latin American country. We analyze data on 5,146 COVID-19 patients from 11 centers across 10 cities in Argentina, making this one of the largest multi-centric retrospective observational descriptive studies in the LMICs. Information on demographics and co-morbidities was extracted from medical records. Outcomes of relevance consisted of whether the patient was discharged or deceased (as established in medical records), along with date of each event. We use survival models that account for competing risks. Median age was 60 years (IQR: 48-72), there were fewer women (40.8%) hospitalized than men (59.2%), and the most prevalent comorbidities were hypertension (40.9%), diabetes (20.0%) and obesity (19.1%). Patients were hospitalized for a median duration of 8 days (IQR: 5-13), and in-hospital mortality was 18.1%, though it varied substantially across health centers (95%CI: 17.1%-19.2%). Baseline characteristics most associated with in-hospital mortality were respiratory rate (adjusted HR = 3.6, 95%CI: 2.5-5.4 for ≥ 26 breathes/min), older age (adjusted HR = 2.5, 95%CI: 2.0-3.3 for the 80+ age group), and chronic kidney disease (adjusted HR = 2.2, 95%CI: 1.8-2.8). Associations were attenuated when survival models did not account for the competing risk of being discharged. We document lower mortality rates than those in prior studies, likely due to a lower prevalence of comorbidities amongst patients in our sample. Compared with standard Cox models, we find that, when using competing risk models, risk factors have a larger role in explaining COVID-19 mortality. Overall, we provide rigorous evidence describing the characteristics and outcomes of hospitalized patients for LMICs. Thus, our findings are useful to conduct a more accurate in-hospital monitoring of patient subgroups who may be at greater risk. They also provide valuable guidance for public health and policy efforts in Argentina and other developing countries.

Project description:Gram-negative bloodstream infections (GNBSI) are confirmed by the presence of gram-negative bacteria in the bloodstream and pose a significant healthcare issue as they increase the risk of sepsis and mortality. In England, the aim is to reduce GNBSI cases and further deterioration through enhanced population surveillance of patients with a laboratory-confirmed GNBSI to inform on healthcare policies. The objective of this study was to evaluate the factors associated with in-hospital mortality in patients with a laboratory-confirmed Escherichia coli, Klebsiella or Pseudomonas aeruginosa GNBSIs, with data obtained from the enhanced data capture for the surveillance of GNBSIs. All patients with a laboratory-confirmed GNBSI at a single centre, admitted between April 2017 and March 2019, were included in this retrospective observational study. Demographic and recent exposure to healthcare risk factors were collected and assessed for the association with in-hospital mortality. In 1113 patients with laboratory-confirmed GNBSIs, the in-hospital mortality rate was 13%. Multivariable analysis confirmed that patients with respiratory (OR = 3.73, 95%CI = 2.05-6.76), gastrointestinal (2.61; 1.22-5.58) or skin (3.61; 1.24-10.54) infection primary focus had a greater risk of in-hospital mortality, compared to upper urinary tract infections. Increased risk of in-hospital mortality was also observed in patients with hospital-onset GNBSIs (OR = 1.87; 1.17-2.97) compared with community-onset healthcare acquired GNBSIs, or who were on dialysis at the time of the GNBSI (3.28; 1.01-10.14), as well as in patients who had recently been discharged from hospital (1.55; 1.01-2.38), or had a vascular device recently manipulated (2.41; 1.01-5.74). Results confirm that the data obtained from the enhanced data capture for GNBSIs in England can predict in-hospital mortality in patients with a GNBSI. Several factors associated with an increased risk of in-hospital mortality have been identified. Results should be reported back to clinicians in order to identify patients at a greater risk of dying in-hospital who may benefit from further monitoring.

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Project description:IntroductionDespite the extra mortality associated with COVID-19 death globally, there is scant data on COVID-19-related paediatric mortality in Sub-Saharan Africa. We assessed predictors of critical care needs and hospital mortality in South African children with laboratory-confirmed SARS-CoV-2 infection in region with high HIV infection burden.MethodsWe conducted a secondary multicentre analysis of the AFREhealth cohort (a multinational, multicentre cohort of paediatric COVID-19 clinical outcomes across six African countries) of children admitted to the Inkosi Albert Luthuli, a quaternary hospital in KwaZulu-Natal, South Africa, with confirmed RT-PCR between March 2020 and December 2020. We constructed multivariable logistic regression to explore factors associated with the need for critical care (high care/ intensive care hospitalisation or oxygen requirement) and cox-proportional hazards models to further assess factors independently associated with in-hospital death.ResultsOf the 82 children with PCR-confirmed SARS-CoV-2 infection (mean ± SD age: 4.2 ± 4.4 years), 35(42.7%) were younger than one year, 52(63%) were female and 59(71%) had a pre-existing medical condition. Thirty-seven (45.2%) children required critical care (median (IQR) duration: 7.5 (0.5-13.5) days) and 14(17%) died. Independent factors associated with need for critical care were being younger than 1 year (aPR: 3.02, 95%CI: 1.05-8.66; p = 0.04), having more than one comorbidity (aPR: 2.47, 95%CI: 1.32-4.61; p = 0.004), seizure (aPR: 2.39, 95%CI: 1.56-3.68; p < 0.001) and impaired renal function. Additionally, independent predictors of in-hospital mortality were exposure to HIV infection (aHR: 6.8, 95%CI:1.54-31.71; p = 0.01), requiring invasive ventilation (aHR: 3.59, 95%CI: 1.01-12.16, p = 0.048) and increase blood urea nitrogen (aHR: 1.06, 95%CI: 1.01-1.11; p = 0.017). However, children were less likely to die from COVID-19 if they were primarily admitted to quaternary unit (aHR: 0.23, 95%CI: 0.1-0.86, p = 0.029).ConclusionWe found a relatively high hospital death rate among children with confirmed COVID-19. During COVID-19 waves, a timely referral system and rapid identification of children at risk for critical care needs and death, such as those less than one year and those with comorbidities, could minimize excess mortality, particularly in high HIV-infection burden countries.

Dataset Information

Risk factors for in-hospital mortality in laboratory-confirmed COVID-19 patients in the Netherlands: A competing risk survival analysis.

Background

Methods

Results

Conclusion

Publications

Risk factors for in-hospital mortality in laboratory-confirmed COVID-19 patients in the Netherlands: A competing risk survival analysis.

Similar Datasets

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