CHARACTERISTICS AND OUTCOMES OF INDIVIDUALS WITH COVID-19: EVIDENCE FROM A HOSPITAL BASED STUDY

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Abstract

Objective

To determine the characteristics and outcomes of Covid-19 patients at Livingstone teaching hospital.

Methods

A database cross sectional review of COVID 19 patients at Livingstone Teaching Hospital. Data on demographics and clinical characteristics were obtained along with the comorbidities presented with by the patients using a structured data collection form. Data were analysed using STATA 64. Mann-Whitney and t-test were used on continuous independent variables. Chi-square test was used to determine associations between two categorical variables. Logistic regression was used to control for confounders.

Results

A total of 222 (62.54%) were male and 133 (37.46%) were female. Discharged were 274 (77.18%), while 81 (22.82%) died. Among those who died were the older clients with a median age of 65 (p <0.001). The median interquartile range (IQR)] age was 48.5 years. Patients presented with a cough 180 (50.7%), chest pain 123 (34.65%) and shortness of breath 121 (34.04%). Statistically significant comorbidities recorded included Hypertension 121 (34.08%), Diabetes mellitus 69 (19.44%), and HIV 38 (10.7%). The most prevalent underlying condition observed was hypertension 121 (34.08).

Conclusion

HIV positive and diabetics had an increased odds of succumbing to COVID-19 death. It is recommended that targeted policies should be considered the risky groups.

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  1. SciScore for 10.1101/2022.05.13.22274812: (What is this?)

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

    Table 1: Rigor

    EthicsField Sample Permit: We conducted a census of all patients admitted at Livingstone Teaching Hospital after permission had been granted by the University of Lusaka, School of Medicine & Health Sciences Research Ethics Committee, the National Health Research Authority (NHRA) and Mulungushi University School of Medicine and Health Sciences research ethics committee (MUSoMHS-REC).
    IRB: We conducted a census of all patients admitted at Livingstone Teaching Hospital after permission had been granted by the University of Lusaka, School of Medicine & Health Sciences Research Ethics Committee, the National Health Research Authority (NHRA) and Mulungushi University School of Medicine and Health Sciences research ethics committee (MUSoMHS-REC).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data was analysed using STATA 64 to produce descriptive statistics.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    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.