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Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388971%3A_____%2F22%3A00560516" target="_blank" >RIV/61388971:_____/22:00560516 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216208:11130/22:10465586

  • Result on the web

    <a href="https://www.bmj.com/content/378/bmj-2021-069881" target="_blank" >https://www.bmj.com/content/378/bmj-2021-069881</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1136/bmj-2021-069881" target="_blank" >10.1136/bmj-2021-069881</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis

  • Original language description

    OBJECTIVEnTo externally validate various prognostic models and scoring rules for predicting short term mortality in patients admitted to hospital for covid-19.nDESIGNnTwo stage individual participant data meta-analysis.nSETTINGnSecondary and tertiary care.nPARTICIPANTSn46 914 patients across 18 countries, admitted to a hospital. with polymerase chain reaction confirmed covid-19. nMODEL SELECTION AND ELIGIBILITY CRITERIAnPrognostic models identified by the living systematic review and through contacting experts. A priori models were excluded that had a high risk of bias in the participant domain of PROBAST (prediction model study risk of bias assessment tool) or for which the applicability was deemed poor.nMETHODSnEight prognostic models with diverse predictors were identified and validated. A two stage individual participant data meta-analysis was performed of the estimated model concordance (C) statistic, calibration slope, calibration-in-the-large, and observed to expected ratio (O:E) across the included clusters. Main outcome measures 30 day mortality or in-hospital mortality.nRESULTSnDatasets included 27 clusters from 18 different countries and contained data on 46 914patients. The pooled estimates ranged from 0.67 to 0.80 (C statistic), 0.22 to 1.22 (calibration slope), and 0.18 to 2.59 (O:E ratio) and were prone to substantial between study heterogeneity. The 4C Mortality Score by Knight et al (pooled C statistic 0.80, 95% confidence interval 0.75 to 0.84, 95% prediction interval 0.72 to 0.86) and clinical model by Wang et al (0.77, 0.73 to 0.80, 0.63 to 0.87) had the highest discriminative ability. On average, 29% fewer deaths were observed than predicted by the 4C Mortality Score (pooled O:E 0.71, 95% confidence interval 0.45 to 1.11, 95% prediction interval 0.21 to 2.39), 35% fewer than predicted by the Wang clinical model (0.65, 0.52 to 0.82, 0.23 to 1.89), and 4% fewer than predicted by Xie et al's model (0.96, 0.59 to 1.55, 0.21 to 4.28).n

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30303 - Infectious Diseases

Result continuities

  • Project

    <a href="/en/project/LM2018131" target="_blank" >LM2018131: Czech National Infrastructure for Biological Data</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    British Medical Journal

  • ISSN

    0959-535X

  • e-ISSN

  • Volume of the periodical

    378

  • Issue of the periodical within the volume

    JUL 12 2022

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    11

  • Pages from-to

    e069881

  • UT code for WoS article

    000839395300002

  • EID of the result in the Scopus database

    2-s2.0-85133913942