Paradox of Predictors in Critically ill COVID-19 Patients: Outcome of a COVID-dedicated Intensive Care Unit

  1. Morshed Nasir
  2. Rawshan Ara Perveen
  3. Rumana Nazneen
  4. Tahmina Zahan
  5. Sonia Nasreen Ahmad
  6. ASM Salauddin Chowdhury

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Abstract

Background

The study aimed to analyze the demographic, comorbidities, biomarkers, pharmacotherapy, and ICU-stay with the mortality outcome of COVID-19 patients admitted in the intensive care unit of a tertiary care hospital in a low-middle income country, Bangladesh.

Methods

The retrospective cohort study was done in Holy Family Red Crescent Medical College Hospital from May to September 2020. All 112 patients who were admitted to ICU as COVID-19 cases (confirmed by RT-PCR of the nasopharyngeal swab) were included in the study. Demographic data, laboratory reports of predictive biomarkers, treatment schedule, and duration of ICU-stay of 99 patients were available and obtained from hospital records (non-electronic) and treatment sheets, and compared between the survived and deceased patients.

Results

Out of 99 patients admitted in ICU with COVID-19, 72 were male and 27 were female. The mean age was 61.08 years. Most of the ICU patients were in the 60 - 69 years of age group and the highest mortality rates (35.89%) were observed in this age range. Diabetes mellitus and hypertension were the predominant comorbidities in the deceased group of patients. A significant difference was observed in neutrophil count, creatinine and, NLR, d-NLR levels that raised in deceased patients. There was no significant difference as a survival outcome of antiviral drugs remdesivir or favipiravir, while the use of cephalosporin was found much higher in the survived group than the deceased group (46.66% vs 20.51%) in ICU.

Conclusions

Susceptibility to developing critical illness due to COVID-19 was found more in comorbid males aged more than 60 years. There were wide variations of the biomarkers in critical COVID-19 patients in a different population, which put the healthcare workers into far more challenge to minimize the mortality in ICU in Bangladesh and around the globe during the peak of the pandemic.

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  1. ScreenIT

    SciScore for 10.1101/2021.04.23.21256009: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The study was approved by the designated hospital authority and the institutional ethics board (IERB/32/Res/Oct/2020/19/hf).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Continuous variables were expressed as the mean and standard deviations; categorical variables were summarized as the counts and percentages and statistical analysis (Chi-square test, unpaired t-test, Fisher’s exact test) was done using SPSS version 26.0 and all p values were two-tailed, with P <0.05 considered statistically significant with a 95% confidence interval.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.04.23.21256009v1 on medRxiv