Platelet size as a predictor for severity and mortality in COVID-19 patients: a systematic review and meta-analysis

  1. Sarah Daniels
  2. Hua Wei
  3. David W. Denning

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Abstract

Background

Parameters reflecting platelet size can be sensitive indicators that circulating platelets are activated and COVID-19 patients are at increased risk of thrombosis. This systematic review aims to assess the association of mean platelet volume (MPV), platelet distribution width (PDW) and platelet-large cell ratio (P-LCR) with disease severity and mortality in COVID-19 patients.

Methods

English and Chinese databases were searched electronically to identify studies reporting data on MPV, PDW or P-LCR in COVID-19 patients. Included articles underwent a quality rating. A meta-analysis was performed using the standard mean difference and interpreted as the common language effect size (CLES).

Results

Twenty-two studies (11,906 patients) were included in the meta-analysis. Of these, 14 were rated poor and eight were fair. The MPV and P-LCR was significantly higher at hospital admission in severe patients compared to non-severe patients. The MPV, PDW and P-LCR were significantly higher at hospital admission in non-survivors compared to survivors. There was a marked increase in the probability of a severe COVID-19 patient presenting with higher P-LCR at hospital admission than a non-severe patient (CLES: 68.7% [95% CI: 59.8%, 76.5%]), when compared with MPV and PDW ((CLES: 59.2% [95% CI: 53.1%, 65.1%]) and (CLES: 55.9% [95% CI: 50.6%, 62.2%]), respectively).

Conclusion

Severe COVID-19 disease is associated with the increased production of larger, younger platelets. When comparing MPV, PDW and P-LCR, P-LCR is the most important biomarker for evaluating platelet activity. P-LCR testing at hospital admission could identify COVID-19 patients with increased risk for thrombotic events, allowing preventative treatment.

Summary Table

What is known on this topic

  • The incidence of thrombotic complications is high in COVID-19 patients with severe disease.

  • Parameters reflecting platelet size can be sensitive indicators that circulating platelets are activated and that COVID-19 patients are at increased risk of thrombosis.

What does this paper add

  • When compared to MPV and PDW, P-LCR is the most important biomarker for evaluating platelet activity in COVID-19 patients at hospital admission and could be used to identify patients with increased risk for thrombotic events.

  • Current evidence is predominantly derived from retrospective design. Prospective studies are warranted to accurately determine cut-off values that may be used in the clinical setting.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.07.15.21260576: (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.
    RandomizationInclusion/exclusion criteria: Studies were included in this review if they met the criteria as follows: Inclusion criteria: 1) Adult patients with laboratory-confirmed COVID-19; 2) biomarker reflecting platelet size (i.e., MPV, PDW and/or P-LCR); 3) investigation of an association between a biomarker reflecting platelet size and disease severity and/or mortality in COVID-19; 4) original (experimental) research including randomised controlled trials, case-control studies, cohort studies, cross-sectional, case reports and series of cases.;
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We carried out a systematic search of the literature from Medline, Embase, PubMed, Web of Science, the Cochrane Central Register of Controlled
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    All the statistical heterogeneity was assessed using RevMan v5.4.1 (2020).
    RevMan
    suggested: (RevMan, RRID:SCR_003581)
    For unreported p values, an appropriate t-test was performed using Graphpad v9.1.1 (2021) if raw data was available.
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)

    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:
    Strengths and limitations of the study: Heterogeneity was explored by conducting sensitivity analyses, minimizing the effect of possible confounders. Specifically, the day the blood test was performed and clinical outcome measures. Our data established that these parameters did not influence the results of the meta-analysis for MPV and P-LCR in severe patients, and for all three platelet size biomarkers in non-survivors. A limitation of our study was that most of the included studies were cross-sectional retrospective. Thus, the studies were dependent on the data that was entered into a clinical database and not collected for research from a predesigned protocol. Consequently, some key statistics may not be measured due to unavailable data, and certain variables that have the potential to impact the outcome may not have been recorded at all. For example, only one study excluded patients who had taken platelet medication for >10 days prior to the study [29]. In addition to this, many studies did not describe the full process of the blood collection and analysis as it was conducted by hospital staff prior to the start of the study. This could weaken the conclusions made by the authors. As an example, Wang et al [25] concludes that an MPV-to-lymphocyte ratio of >8.9 was a high risk for COVID-19 severity. However, without a description of the blood test methodology, clinicians cannot determine what laboratory conditions this cut-off would apply to, as different conditions can giv...

    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 10.1101/2021.07.15.21260576v1 on medRxiv