Predictors of mortality in COVID-19 patients treated with convalescent plasma therapy

Naomi Rahimi-Levene, Jonathan Shapira, Irma Tzur, Eli Shiloah, Victoria Peer, Ella Levin, Marina Izak, Eilat Shinar, Tomer Ziv-Baran, Miriam Weinberger, Oren Zimhony, Jacob Chen, Yasmin Maor

Research output: Contribution to journalArticlepeer-review

Abstract

Several options to treat hospitalized severe COVID-19 patients have been suggested. The study aimed to describe survival in patients treated with convalescent COVID plasma (CCP) and to identify in-hospital mortality predictors. This prospective cohort study examined data from 112 severe COVID-19 patients hospitalized in the Corona Departments in an acute care hospital who received two units of CCP (at least one of them high-titer). Demographic and medical data was retrieved from the patients' electronic health records (EHR). Possible predictors for in-hospital mortality were analyzed in a univariate analysis and those found to be clinically significant were further analyzed in a multivariable analysis. Median age was 67 years (IQR 55-74) and 66 (58.9%) of them were males. Of them, 20 (17.9%) died in hospital. On multivariable analysis diabetes mellitus (p = 0.004, OR 91.54), mechanical ventilation (p = 0.001, OR 59.07) and lower albumin levels at treatment (p = 0.027, OR 0.74) were significantly associated with increased in-hospital mortality. In our study, in-hospital mortality in patients receiving CCP is similar to that reported for the general population, however certain variables mentioned above were associated with increased in-hospital mortality. In the literature, these variables were also associated with a worse outcome in patients with COVID- 19 who did not receive CCP. As evidence points toward a benefit from CCP treatment in immunocompromised patients, we believe the above risk factors can further define COVID- 19 patients at increased risk for mortality, enabling the selection of candidates for early treatment in an outpatient setting if possible.

Original languageEnglish
Article numbere0271036
JournalPLoS ONE
Volume17
Issue number7 July
DOIs
StatePublished - Jul 2022

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