Dataset Information

Biometric covariates and outcome in COVID-19 patients: are we looking close enough?

ABSTRACT:

Background

The impact of biometric covariates on risk for adverse outcomes of COVID-19 disease was assessed by numerous observational studies on unstratified cohorts, which show great heterogeneity. However, multilevel evaluations to find possible complex, e.g. non-monotonic multi-variate patterns reflecting mutual interference of parameters are missing. We used a more detailed, computational analysis to investigate the influence of biometric differences on mortality and disease evolution among severely ill COVID-19 patients.

Methods

We analyzed a group of COVID-19 patients requiring Intensive care unit (ICU) treatment. For further analysis, the study group was segmented into six subgroups according to Body mass index (BMI) and age. To link the BMI/age derived subgroups with risk factors, we performed an enrichment analysis of diagnostic parameters and comorbidities. To suppress spurious patterns, multiple segmentations were analyzed and integrated into a consensus score for each analysis step.

Results

We analyzed 81 COVID-19 patients, of whom 67 required mechanical ventilation (MV). Mean mortality was 35.8%. We found a complex, non-monotonic interaction between age, BMI and mortality. A subcohort of patients with younger age and intermediate BMI exhibited a strongly reduced mortality risk (p < 0.001), while differences in all other groups were not significant. Univariate impacts of BMI or age on mortality were missing. Comparing MV with non-MV patients, we found an enrichment of baseline CRP, PCT and D-Dimers within the MV group, but not when comparing survivors vs. non-survivors within the MV patient group.

Conclusions

The aim of this study was to get a more detailed insight into the influence of biometric covariates on the outcome of COVID-19 patients with high degree of severity. We found that survival in MV is affected by complex interactions of covariates differing to the reported covariates, which are hidden in generic, non-stratified studies on risk factors. Hence, our study suggests that a detailed, multivariate pattern analysis on larger patient cohorts reflecting the specific disease stages might reveal more specific patterns of risk factors supporting individually adapted treatment strategies.

SUBMITTER: Sharafutdinov K

PROVIDER: S-EPMC8567725 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Publications

Biometric covariates and outcome in COVID-19 patients: are we looking close enough?

Sharafutdinov Konstantin K Fritsch Sebastian Johannes SJ Marx Gernot G Bickenbach Johannes J Schuppert Andreas A

BMC infectious diseases 20211104 1

<h4>Background</h4>The impact of biometric covariates on risk for adverse outcomes of COVID-19 disease was assessed by numerous observational studies on unstratified cohorts, which show great heterogeneity. However, multilevel evaluations to find possible complex, e.g. non-monotonic multi-variate patterns reflecting mutual interference of parameters are missing. We used a more detailed, computational analysis to investigate the influence of biometric differences on mortality and disease evolutio ...[more]

PMID: 34736400

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Project description:IntroductionSince the start of the COVID-19 pandemic 2019, quite a few patients became critical and needed ICU admission with ventilator assistance. Tracheostomy, which was initially performed late during the course of patient on ventilator, has now been considered a procedure that can be performed relatively early as this leads to early weaning of patients and overcomes the shortage of critical beds.ObjectiveThis study aims to focus on the outcomes of tracheotomised COVID-19 patients in terms of survival and any tracheostomy related morbidity.MethodsA prospective study was performed on COVID-19 patients undergoing tracheostomy at this tertiary care teaching hospital, which also was a dedicated centre for treating COVID-19 patients. The duration of this study was from April 2020 to September 2021. Following tracheostomy, all patients were followed up regularly and clinical changes were recorded. Points that were specifically noted were timing of the tracheostomy, change in ventilator settings, tracheostomy related complications, requirement of oxygen, days needed to wean the patient, decanulation, and, if death, the cause of death.ResultsA total of 136 surgical open tracheostomies were performed on COVID-19 patients over the study period. The mean duration of intubation (timing of tracheostomy) was 12 days. A total of 73 out of 136 (53.6%) patients survived. 51 patients (37.5%) got decannulated during the course of the hospital stay. 9 patients were decanulated during the follow up visits and 13 patients were lost to follow up. 63 out of 136 (46.3%) patients died due to COVID pneumonia. Most of the patients who died had gone into multi-organ failure. Air leak syndromes (pneumothorax and pneumomediastinum) were common findings. 10 patients already had surgical emphysema before taking up for tracheostomy and 6 developed 2-3 days after tracheostomy. The most common complication was bleeding, which was seen in 28 out of 136 patients. The Median weaning of period of patients who survived was 5 days.ConclusionPerforming tracheostomy early in COVID-19 patients helps in early weaning of the patient from the ventilator and makes nursing care easier and increases the availability of ICU beds. The mortality rate was 46% amongst the 136 tracheostomies done in COVID-19 patients. Local site bleeding was the most common complication and surgical emphysema was also seen more than routine tracheostomies.Supplementary informationThe online version contains supplementary material available at 10.1007/s12070-022-03248-1.

Dataset Information

Biometric covariates and outcome in COVID-19 patients: are we looking close enough?

Background

Methods

Results

Conclusions

Publications

Biometric covariates and outcome in COVID-19 patients: are we looking close enough?

Similar Datasets

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