Sex-specific epidemiological and clinical characteristics of Covid-19 patients in the southeast region of Bangladesh

  1. Md. Aminul Islam
  2. Abdullah Al Marzan
  3. Md. Sydul Islam
  4. Samina Sultana
  5. Md. Iftakhar Parvej
  6. Mohammad Salim Hossain
  7. Mohammad Tohid Amin
  8. Farzana Ehetasum Hossain
  9. Md Abdul Barek
  10. Md. Shafiul Hossen
  11. Md. Shariful Islam
  12. Foysal Hossen
  13. Newaz Mohammed Bahadur
  14. Md. Shahadat Hossain
  15. Nazratun Nayeem Choudhury
  16. Md. Didar-ul Alam
  17. Firoz Ahmed

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Abstract

Background

COVID-19 has become a global pandemic with a high growth rate of confirmed cases. In Bangladesh, both mortality and affected rates are increasing at an alarming rate.

Therefore, more comprehensive studies of the epidemiological and clinical characteristics of COVID-19 are required to control this pandemic.

Purpose

The present study aimed to compare and analyze the sex-specific epidemiological, clinical characteristics, comorbidities, and other information of confirmed COVID-19 patients from the southeast region in Bangladesh for the first time.

Methods

385 lab-confirmed cases were studied out of 2,471 tested samples between 5 June and 10 September 2020. RT-PCR was used for COVID-19 identification and SPSS (version 25) for statistical data analysis.

Results

We found that male patients were roughly affected compared to females patients (male 74.30% vs. female 25.7%) with an average age of 34.86 ± 15.442 years, and B (+ve) blood group has been identified as a high-risk factor for COVID-19 infection. Workplace, local market, and bank were signified as sex-specific risk zone ( p < 0.001). Pre-existing medical conditions such as diabetes, hypertension, cardiovascular and respiratory diseases were identified among the patients. Less than half of the confirmed COVID-19 cases in the southeast region were asymptomatic (37.73%) and more prevalent among females than males (male vs. female: 36.84% vs. 40.51%, p = 0.001).

Conclusions

The findings may help health authorities and the government take necessary steps for identification and isolation, treatment, prevention, and control of this global pandemic.

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  1. Version published to 10.1101/2021.07.05.21259933v3 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2021.07.05.21259933: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableThree hundred eighty-five patients (aged above 5 years) were identified as positive from the southeast region, Bangladesh (Noakhali and Lakshmipur) in where 286 patients were male, and 99 were female.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All statistical analysis was conducted using the IBM Statistical Package for the Social Sciences (SPSS), version 25.0 software.
    Statistical Package for the Social Sciences
    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: We detected the following sentences addressing limitations in the study:
    Albeit this is a novel study, several limitations might be noted in the present study. Firstly, the present study was performed only in a single institution obtaining data via face-to-face information when patients came for coronavirus testing. Hence, the represented data does not give the whole scenario of all COVID-19 patients of the country. Secondly, the limited number of study populations, especially for female patients. Finally, we did not include any data from hospitalized patients and laboratory outputs. However, our study analyzed the demographic and clinical characteristics of COVID-19 patents that aid in identifying possible risk factors and reducing the risk of COVID-19 susceptibility to control this outbreak.

    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.

  3. Version published to 10.1101/2021.07.05.21259933v2 on medRxiv
  4. Version published to 10.1101/2021.07.05.21259933v1 on medRxiv