tetano
Editor, Senior Moderator
PLoS One
. 2022 Jul 22;17(7):e0264106.
doi: 10.1371/journal.pone.0264106. eCollection 2022.
The usefulness of D-dimer as a predictive marker for mortality in patients with COVID-19 hospitalized during the first wave in Italy
Shermarke Hassan[SUP] 1 2 [/SUP], Barbara Ferrari[SUP] 3 [/SUP], Raffaella Rossio[SUP] 3 [/SUP], Vincenzo la Mura[SUP] 1 3 [/SUP], Andrea Artoni[SUP] 4 [/SUP], Roberta Gualtierotti[SUP] 1 4 [/SUP], Ida Martinelli[SUP] 4 [/SUP], Alessandro Nobili[SUP] 5 [/SUP], Alessandra Bandera[SUP] 1 6 [/SUP], Andrea Gori[SUP] 1 6 [/SUP], Francesco Blasi[SUP] 1 7 [/SUP], Valter Monzani[SUP] 8 [/SUP], Giorgio Costantino[SUP] 9 10 [/SUP], Sergio Harari[SUP] 9 11 [/SUP], Frits Richard Rosendaal[SUP] 2 [/SUP], Flora Peyvandi[SUP] 1 3 [/SUP], COVID-19 Network working group
Affiliations
Abstract
Background: The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Identification of predictors of poor outcomes will assist medical staff in treatment and allocating limited healthcare resources.
Aims: The primary aim was to study the value of D-dimer as a predictive marker for in-hospital mortality.
Methods: This was a cohort study. The study population consisted of hospitalized patients (age >18 years), who were diagnosed with COVID-19 based on real-time PCR at 9 hospitals during the first COVID-19 wave in Lombardy, Italy (Feb-May 2020). The primary endpoint was in-hospital mortality. Information was obtained from patient records. Statistical analyses were performed using a Fine-Gray competing risk survival model. Model discrimination was assessed using Harrell's C-index and model calibration was assessed using a calibration plot.
Results: Out of 1049 patients, 507 patients (46%) had evaluable data. Of these 507 patients, 96 died within 30 days. The cumulative incidence of in-hospital mortality within 30 days was 19% (95CI: 16%-23%), and the majority of deaths occurred within the first 10 days. A prediction model containing D-dimer as the only predictor had a C-index of 0.66 (95%CI: 0.61-0.71). Overall calibration of the model was very poor. The addition of D-dimer to a model containing age, sex and co-morbidities as predictors did not lead to any meaningful improvement in either the C-index or the calibration plot.
Conclusion: The predictive value of D-dimer alone was moderate, and the addition of D-dimer to a simple model containing basic clinical characteristics did not lead to any improvement in model performance.
. 2022 Jul 22;17(7):e0264106.
doi: 10.1371/journal.pone.0264106. eCollection 2022.
The usefulness of D-dimer as a predictive marker for mortality in patients with COVID-19 hospitalized during the first wave in Italy
Shermarke Hassan[SUP] 1 2 [/SUP], Barbara Ferrari[SUP] 3 [/SUP], Raffaella Rossio[SUP] 3 [/SUP], Vincenzo la Mura[SUP] 1 3 [/SUP], Andrea Artoni[SUP] 4 [/SUP], Roberta Gualtierotti[SUP] 1 4 [/SUP], Ida Martinelli[SUP] 4 [/SUP], Alessandro Nobili[SUP] 5 [/SUP], Alessandra Bandera[SUP] 1 6 [/SUP], Andrea Gori[SUP] 1 6 [/SUP], Francesco Blasi[SUP] 1 7 [/SUP], Valter Monzani[SUP] 8 [/SUP], Giorgio Costantino[SUP] 9 10 [/SUP], Sergio Harari[SUP] 9 11 [/SUP], Frits Richard Rosendaal[SUP] 2 [/SUP], Flora Peyvandi[SUP] 1 3 [/SUP], COVID-19 Network working group
Affiliations
- PMID: 35867647
- DOI: 10.1371/journal.pone.0264106
Abstract
Background: The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Identification of predictors of poor outcomes will assist medical staff in treatment and allocating limited healthcare resources.
Aims: The primary aim was to study the value of D-dimer as a predictive marker for in-hospital mortality.
Methods: This was a cohort study. The study population consisted of hospitalized patients (age >18 years), who were diagnosed with COVID-19 based on real-time PCR at 9 hospitals during the first COVID-19 wave in Lombardy, Italy (Feb-May 2020). The primary endpoint was in-hospital mortality. Information was obtained from patient records. Statistical analyses were performed using a Fine-Gray competing risk survival model. Model discrimination was assessed using Harrell's C-index and model calibration was assessed using a calibration plot.
Results: Out of 1049 patients, 507 patients (46%) had evaluable data. Of these 507 patients, 96 died within 30 days. The cumulative incidence of in-hospital mortality within 30 days was 19% (95CI: 16%-23%), and the majority of deaths occurred within the first 10 days. A prediction model containing D-dimer as the only predictor had a C-index of 0.66 (95%CI: 0.61-0.71). Overall calibration of the model was very poor. The addition of D-dimer to a model containing age, sex and co-morbidities as predictors did not lead to any meaningful improvement in either the C-index or the calibration plot.
Conclusion: The predictive value of D-dimer alone was moderate, and the addition of D-dimer to a simple model containing basic clinical characteristics did not lead to any improvement in model performance.