Insufficient fibrinolysis in COVID-19: a systematic review of thrombolysis based on meta-analysis and meta-regression

  1. Hong-Long Ji
  2. Zhenlei Su
  3. Runzhen Zhao
  4. Andrey A. Komissarov
  5. Guohua Yi
  6. Shan-Lu Liu
  7. Steven Idell
  8. Michael A. Matthay

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Abstract

Background

How aberrant fibrinolysis influences the clinical progression of COVID-19 presents a clinicopathological dilemma challenging intensivists. To investigate whether abnormal fibrinolysis is a culprit or protector or both, we associated elevated plasma D-dimer with clinical variables to identify a panoramic view of the derangements of fibrinolysis that contribute to the pathogenesis of COVID-19 based on studies available in the literature.

Methods

We performed this systematic review based on both meta-analysis and meta-regression to compute the correlation of D-dimer at admission with clinical features of COVID-19 patients in retrospective studies or case series. We searched the databases until Aug 18, 2020, with no limitations by language. The first hits were screened, data extracted, and analyzed in duplicate. We did the random-effects meta-analyses and meta-regressions (both univariate and multivariate). D-dimer associated clinical variables and potential mechanisms were schematically reasoned and graphed.

Findings

Our search identified 42 observational, or retrospective, or case series from six countries (n=14,862 patients) with all races and ages from 1 to 98-year-old. The weighted mean difference of D-dimer was 0.97 μg/mL (95% CI 0.65, 1.29) between relatively mild (or healthy control) and severely affected groups with significant publication bias. Univariate meta-regression identified 58 of 106 clinical variables were associated with plasma D-dimer levels, including 3 demographics, 5 comorbidities, 22 laboratory tests, 18 organ injury biomarkers, 8 severe complications, and 2 outcomes (discharge and death). Of these, 11 readouts were negatively associated with the level of plasma D-dimer. Further, age and gender were confounding factors for the identified D-dimer associated variables. There were 22 variables independently correlated with the D-dimer level, including respiratory rate, dyspnea plasma K + , glucose, SpO 2 , BUN, bilirubin, ALT, AST, systolic blood pressure, and CK. We thus propose that insufficient hyperfibrinolysis (fibrinolysis is accelerated but unable to prevent adverse clinical impact for clinical deterioration COVID-19) as a peculiar mechanism.

Interpretation

The findings of this meta-analysis- and meta-regression-based systematic review supports elevated D-dimer as an independent predictor for mortality and severe complications. D-dimer-associated clinical variables draw a landscape integrating the aggregate effects of systemically suppressive and locally (i.e., in the lung) hyperactive derangements of fibrinolysis. D-dimer and associated clinical biomarkers and conceptually parameters could be combined for risk stratification, potentially for tracking thrombolytic therapy or alternative interventions.

Funding

National Institute of Health.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.07.20190165: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Literature search: Two independent investigators searched the potential studies in the NCBI PubMed, EMBASE, Scopus, Web of Science, Google Scholar, and some preprint platforms, including the medRxiv, Preprint, and bioRxiv.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    EMBASE
    suggested: (EMBASE, RRID:SCR_001650)
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    bioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    Percentages and SDMs were extracted directly from studies if available. Meta-analysis: To perform meta-analysis with the STATA v.
    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: We detected the following sentences addressing limitations in the study:
    Limitations: Because COVID-19 is a new emerging disease, most of the included studies are descriptive, case series, retrospective, single-center, and observational. Most of the studies included are from China/Asia, where the pandemic was discovered. Diversity in cohorts exists from children to seniors associated with variant comorbidities and complications. Inconsistent grouping strategies between studies pose a challenge for meta-analysis, for example, ICU vs non-ICU, ARDS vs non-ARDS, control vs COVID-19, survivor vs non-survivor, severe vs non-severe, VTE vs non-VTE, death vs recovered, mild vs moderate, moderate vs severe, normal vs abnormal D-dimer, etc. We cannot exclude the potential pre- and post-test deviations regarding the methodology for D-dimer assays. Meta-regression but not meta-analysis may partially mitigate these deviations. 5. Conclusions: We have reviewed the fibrinolytic mechanisms for the most common biomarker D-dimer in severe COVID-19 patients and propose a new model of insufficient pulmonary hyperfibrinolysis in both extra- and intravascular compartments. SARS-CoV-2 infection-initiated primary hypercoagulation occurs with hyperfibrinolysis in the lung and other end-organs, presenting with D-dimer elevations. Suppression of the excretion and catabolism in the injured liver and kidney likely contributes to the accumulation of D-dimer in the blood. This process is further enhanced by systemic septic DIC, multiorgan failure, and secondary infection in dec...

    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.

    About SciScore

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  2. Version published to 10.1101/2020.09.07.20190165 on medRxiv