COVID-19 disease progression according to initial symptoms. A telemedicine cohort study

  1. Karla Murillo-Villanueva
  2. Blanca Velázquez-Hernández
  3. José A. Jácome-Mondragón
  4. Judit J. Cervantes-Llamas
  5. Juan O. Talavera

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Abstract

Objective

COVID-19 progression to severe or critical illness may be related to initial clinical presentation. Main objective was to identify initial symptoms related to highest risk of disease progression, in mild or moderate suspected or confirmed COVID-19 patients or in asymptomatic subjects in contact with a recently diagnosed patient.

Design and methods

Historic cohort study of Mexican patients with suspected or confirmed mild or moderate COVID-19 or asymptomatic subjects in recent contact with positive patients. They sought medical attention in “Centro Médico ABC” or claimed for remote attention, and daily telemedicine follow up until recovery or illness progression, from April 17th to October 08th 2020. Data excerpted for analysis were sex, age, body mass index, comorbidities, and signs, and symptoms presented in first day of disease manifestations and during follow up. We used logistic regression to identify initial symptoms associated with progression disease and through a conjunctive consolidation analysis a symptom index was created.

Results

120 of 1635 patients (7.2%) had clinical progression disease. By logistic regression we found as initial symptoms related to progression: fever OR 3 (1.89-4.77, p<0.001), cough OR 2.34 (1.56-3.52, p<0.001), myalgias or arthralgias OR 1.69 (1.09-2.63, p=0.018), and fatigue OR 1.65 (1.08-2.53, p=0.019). Conjunctive consolidation was processed with the previous symptoms, and a 3 groups score resulted C-19PAIS Index: 1) Fever with cough or fever with fatigue, with a probability of progression disease of 29% (31/106 patients), 2) Fever or cough or fatigue or cough with fatigue, 10.7% (66/615 patients) and 3) No fever, no cough, no fatigue, 2% (23/914).

Conclusions

Initial symptoms predict clinical progression in COVID-19 patients.

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  1. ScreenIT

    SciScore for 10.1101/2022.01.03.22268669: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The Institutional Review Board of CMABC approved this study (Protocol approval ABC-20-93).
    Sex as a biological variableAll of them with an age >18 years, not pregnant, with an oxygen saturation measurement ≥90% when evaluated at hospital, and in those patients at home that referred dyspnea an evaluation of oxygen saturation measurement ≥90% was necessary.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisSample size calculation: The sample size calculation was based on the requirements for a multivariable model (events per variable, EPV); considering that 6.2% was estimated to present the outcome of clinical progression (13), and following the assumption of 10-20 events per variable (14), and that the study has 8 parameters (symptoms), we calculated a minimum required sample size of 1324 patients, expecting 80 patients with progressive illness; and a maximum of 2648.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical significance was set at p<0.05 and performed with SPSS version 27.0
    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: We detected the following sentences addressing limitations in the study:
    This study has limitations. Clinical interview was realized by many doctors with different training (general practitioners, internists, and otorhinolaryngologists), although, all of them received a standardized training to participate in the program. C-19PAIS Index may help discern those with low from high risk of progression, identifying those who require more intensive monitoring and extension tests, anticipate, and prevent adverse outcomes.

    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 10.1101/2022.01.03.22268669v1 on medRxiv