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. 2022 Jun;50(Supp1):S57-S61.
doi: 10.5152/TJAR.2022.21321.

Prognosis of Old Intensive Care COVID-19 Patients at a Glance: The Senior COVID Study

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Prognosis of Old Intensive Care COVID-19 Patients at a Glance: The Senior COVID Study

Charles-Hervé Vacheron et al. Turk J Anaesthesiol Reanim. 2022 Jun.

Abstract

Objective: Admission in the intensive care unit of the old patient with coronavirus disease 19 raises an ethical question concerning the scarce resources and their short-term mortality.

Methods: Patients aged over 60 from 7 different intensive care units admitted between March 1, 2020 and May 6, 2020, with a diagnosis of coronavirus disease 19 were included in the cohort. Twenty variables were collected during the admission, such as age, severity (Simplified Acute Physiology Score [SAPS] II), several data on physiological status before intensive care unit comorbidities, evaluation of autonomy, frailty, and biological variables. The objective was to model the 30-day mortality with relevant variables, compute their odds ratio associated with their 95% CI, and produce a nomogram to easily estimate and communicate the 30-day mortality. The performance of the model was estimated with the area under the receiving operating curve.

Results: We included 231 patients, among them 60 (26.0%) patients have died on the 30th day. The relevant variables selected to explain the 30-day mortality were Instrumental Activities of Daily Living (IADL) score (0.82 [0.71-0.94]), age 1.12 (1.07-1.18), SAPS II 1.05 (1.02-1.08), and dementia 6.22 (1.00-38.58). A nomogram was computed to visually represent the final model. Area under the receiving operating curve was at 0.833 (0.776-0.889).

Conclusions: Age, autonomy, dementia, and severity at admission were important predictive variables for the 30-day mortality status, and the nomogram could help the physician in the decision-making process and the communication with the family.

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Figures

Figure 1.
Figure 1.
Nomogram of the logistic regression model.

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