Thrombocytopenia as a prognostic marker in COVID-19 patients: diagnostic test accuracy meta-analysis

Abstract

This systematic review and meta-analysis aimed to evaluate thrombocytopenia as a prognostic biomarker in patients with coronavirus disease 2019 (COVID-19). We performed a systematic literature search using PubMed, Embase and EuropePMC. The main outcome was composite poor outcome, a composite of mortality, severity, need for intensive care unit care and invasive mechanical ventilation. There were 8963 patients from 23 studies. Thrombocytopenia occurred in 18% of the patients. Male gender (P = 0.037) significantly reduce the incidence. Thrombocytopenia was associated with composite poor outcome (RR 1.90 (1.43-2.52), P < 0.001; I2: 92.3%). Subgroup analysis showed that thrombocytopenia was associated with mortality (RR 2.34 (1.23-4.45), P < 0.001; I2: 96.8%) and severity (RR 1.61 (1.33-1.96), P < 0.001; I2: 62.4%). Subgroup analysis for cut-off <100 × 109/l showed RR of 1.93 (1.37-2.72), P < 0.001; I2: 83.2%). Thrombocytopenia had a sensitivity of 0.26 (0.18-0.36), specificity of 0.89 (0.84-0.92), positive likelihood ratio of 2.3 (1.6-3.2), negative likelihood ratio of 0.83 (0.75-0.93), diagnostic odds ratio of 3 (2, 4) and area under curve of 0.70 (0.66-0.74) for composite poor outcome. Meta-regression analysis showed that the association between thrombocytopenia and poor outcome did not vary significantly with age, male, lymphocyte, d-dimer, hypertension, diabetes and CKD. Fagan's nomogram showed that the posterior probability of poor outcome was 50% in patients with thrombocytopenia, and 26% in those without thrombocytopenia. The Deek's funnel plot was relatively symmetrical and the quantitative asymmetry test was non-significant (P = 0.14). This study indicates that thrombocytopenia was associated with poor outcome in patients with COVID-19.PROSPERO ID: CRD42020213974.

Keywords: Coronavirus; mortality; platelet; severe; thrombocyte.

Fig. 1.

PRISMA flowchart.

Fig. 2.

Forest-plot for thrombocytopenia and composite poor outcome (a) and pooled sensitivity and specificity (b).

Fig. 3.

Fagan's nomogram.

Fig. 4.

Deek's funnel plot and asymmetry test. The vertical axis displays the inverse of the square root of the effective sample size (1/root(ESS)).

Fig. 5.

Summary receiver operating characteristic (SROC) with prediction and confidence contours.

Fig. 6.

Univariable meta-regression and subgroup analyses. Vertical lines represent pooled sensitivity and specificity, respectively.