Death review caused by Covid 19 in Bangladesh

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Abstract

Introduction

COVID-19 pandemic had taken away lots of human life prematurely worldwide and death laid its icy hands also on Bangladesh. So, objectives of this study were to explore the monthly distributions, age, sex, co-morbidities, localities and duration of hospital stay among the COVID death cases.

Methods

In this observational study six months hospital death files were collected and explored for monthly distributions, age, sex, co-morbidities, localities and hospital stay. RT-PCR positive confirmed 113 COVID deaths were enrolled and suspected COVID deaths were excluded. Ethical clearance from the hospital authority was taken before hand. Data was compiled and analyzed by SPSS-20.

Results

There was a low frequency of death in May-2021 and October-2021(7.1% and 2.7% respectively) but more during June -2021 to September 2021 (12.4%, 16.8%, 42.5% and 18.6% respectively). Female deaths were little more than male deaths(53.1% vs 46.9%). Age more than 51 years were the most vulnerable where 26(23%) deaths were at age group 51-60 years, 39(34.5%) deaths were at 61-70 years and 22(19.4%) deaths were more than 71 years. Mean age of death was found 60.66 years and mean duration of hospital stay was found 9.45 days. Maximum duration of hospital stay was 45 days for one patient. Co-morbidities of death cases revealed 52(46.00%) patients had DM and HTN both, 17(15.0%) patients had HTN, 16(14.1%) had DM, 3(2.6%) had BA and COPD, 4(3.5%) had CKD, 2(1.7%) had cancer, 3(2.6%) had CVD, 19(16.8%) had IHD and 16(14.1%) patients had no co-morbidities. Locality of the death cases revealed 44(38.9%) came from rural areas and 69(61.1%) came from urban areas.

Conclusion

Higher age group and multiple co-morbidities specially DM, HTN and IHD were related with COVID deaths mostly found in our study.

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  1. SciScore for 10.1101/2022.01.23.22269626: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.


    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.