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Sinfras > Diet > Clinical features, risk factors and a prediction model for in-hospital mortality among diabetic patients infected with COVID-19: data from a referral centre in Iran
Diet

Clinical features, risk factors and a prediction model for in-hospital mortality among diabetic patients infected with COVID-19: data from a referral centre in Iran

Loknath Das
Last updated: 2021/11/19 at 10:25 AM
By Loknath Das 2 Min Read
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Frontiers | Symptom Prediction and Mortality Risk Calculation for COVID-19  Using Machine Learning | Artificial Intelligence

Contents
AbstractObjectivesStudy designMethodsResultsConclusions

Abstract

Objectives

The aim of this study was to identify risk factors of in-hospital mortality among diabetic patients infected with COVID-19.

Study design

Retrospective cohort study.

Methods

Using logistic regression analysis, the independent association of potential prognostic factors and COVID-19 in-hospital mortality was investigated in three models. Model 1 included demographic data and patient history; model 2 consisted of model 1, plus vital signs and pulse oximetry measurements at hospital admission; and model 3 included model 2, laboratory test results at hospital admission. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were reported for each predictor in the different models. Moreover, to examine the discriminatory powers of the models, a corrected area under the receiver-operating characteristic curve (AUC) was calculated.

Results

Among 560 patients with diabetes (men = 291) who were hospitalised for COVID-19, the mean age of the study population was 61.8 (standard deviation [SD] 13.4) years. During a median length of hospitalisation of 6 days, 165 deaths (men = 93) were recorded. In model 1, age and a history of cognitive impairment were associated with higher mortality; however, taking statins, oral anti-diabetes drugs and beta-blockers were associated with a lower risk of mortality (AUC = 0.76). In model 2, adding the data for respiratory rate (OR 1.07 [95% CI 1.00–1.14]) and oxygen saturation (OR 0.95 [95% CI 0.92–0.98]) slightly increased the AUC to 0.80. In model 3, the data for platelet count (OR 0.99 [95% CI 0.99–1.00]), lactate dehydrogenase (OR 1.002 [1.001–1.003]), potassium (OR 2.02 (95% CI 1.33–3.08]) and fasting plasma glucose (OR 1.04 [1.02–1.07]) significantly improved the discriminatory power of the model to AUC 0.86 (95% CI 0.83–0.90).

Conclusions

Among patients with type 2 diabetes, a combination of past history and pulse oximetry data, with four non-expensive laboratory measures, was significantly associated with in-hospital COVID-19 mortality.

[“source=sciencedirect”]

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TAGGED: A, Among, and, Centre, Clinical, COVID-19, data, Diabetic, factors, Features, For, From, in, in-hospital, infected, Iran, model', mortality, patients, prediction, referral, risk, With
Loknath Das November 19, 2021
By Loknath Das
I am a blogger with the main motive of writing articles at my choice of level. I do love to write articles and keep my website updated regularly , if you love my article then be sure to share with your friends as they would love to read my article...
Previous Article What social media told us in the time of COVID-19: a scoping review
Next Article Generation and persistence of S1 IgG and neutralizing antibodies in post-COVID-19 patients

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