Hospitalized COVID-19 patients with diabetes have an increased risk for pneumonia, intensive care unit requirement, intubation, and death: A cross-sectional cohort study in Mexico in 2020

A simplified pneumonia severity index (PSI) for clinical outcome prediction in COVID-19

BACKGROUND

The Pneumonia Score Index (PSI) was developed to estimate the risk of dying within 30 days of presentation for community-acquired pneumonia patients and is a strong predictor of 30-day mortality after COVID-19. However, three of its required 20 variables (skilled nursing home, altered mental status and pleural effusion) are not discreetly available in the electronic medical record (EMR), resulting in manual chart review for these 3 factors. The goal of this study is to compare a simplified 17-factor version (PSI-17) to the original (denoted PSI-20) in terms of prediction of 30-day mortality in COVID-19.

METHODS

In this retrospective cohort study, the hospitalized patients with confirmed SARS-CoV-2 infection between 2/28/20-5/28/20 were identified to compare the predictive performance between PSI-17 and PSI-20. Correlation was assessed between PSI-17 and PSI-20, and logistic regressions were performed for 30-day mortality. The predictive abilities were compared by discrimination, calibration, and overall performance.

RESULTS

Based on 1,138 COVID-19 patients, the correlation between PSI-17 and PSI-20 was 0.95. Univariate logistic regression showed that PSI-17 had performance similar to PSI-20, based on AUC, ICI and Brier Score. After adjusting for confounding variables by multivariable logistic regression, PSI-17 and PSI-20 had AUCs (95% CI) of 0.85 (0.83-0.88) and 0.86 (0.84-0.89), respectively, indicating no significant difference in AUC at significance level of 0.05.

CONCLUSION

PSI-17 and PSI-20 are equally effective predictors of 30-day mortality in terms of several performance metrics. PSI-17 can be obtained without the manual chart review, which allows for automated risk calculations within an EMR. PSI-17 can be easily obtained and may be a comparable alternative to PSI-20.

Factors Associated with Length of Hospitalization in Patients with Diabetes and Mild COVID-19: Experiences from a Tertiary University Center in Serbia

Background and Objectives: During the COVID-19 pandemic, there was an increased number of hospitalized COVID-19-positive patients suffering from type 2 diabetes mellitus (T2DM). The objective of this research study was to explore factors associated with the length of hospitalization of patients with T2DM and the mild form of COVID-19. Material and Methods: This retrospective cohort study involved all patients who tested positive for COVID-19 and those who were treated in the dedicated COVID-19 department of the University Clinical Center (UCC) in Nis between 10 September 2021 and 31 December 2021. Upon admission, patients underwent blood tests for biochemical analysis, including blood count, kidney and liver function parameters (C-reactive protein (CRP), creatinine kinase, and D-dimer), and glycemia and HbA1c assessments. Additionally, all patients underwent lung radiography. Univariate and multivariate regression analyses were employed to assess the impact of specific factors on the length of hospitalization among patients with T2DM. Results: Out of a total of 549 treated COVID-19-positive patients, 124 (21.0%) had T2DM, while 470 (79.0%) did not have diabetes. Among patients with T2DM, men were significantly younger than women (60.6 ± 16.8 vs. 64.2 ± 15.3, p < 0.01). The average hospitalization length of patients with diabetes was 20.2 ± 9.6 (5 to 54 days), and it was significantly longer than for patients without diabetes, at 15.0 ± 3.4, which ranged from 3 days to 39 (t-test ≈ 5.86, p < 0.05). According to the results of the univariate regression analysis, each year of age is associated with an increase in the length of hospital stay of 0.06 days (95% CI: 0.024 to 0.128, p = 0.004). Patients who received oxygen therapy were treated for 2.8 days longer than those who did not receive oxygen treatment (95% CI: 0.687 to 4988, p = 0.010), and each one-unit increase in CRP level was associated with a 0.02-day reduction in the length of hospitalization (95% CI: 0.004 to 0.029, p = 0.008). Based on the results of the multivariate regression analysis, each year of age is associated with an increase in the length of hospitalization by 0.07 days (95% CI: 0.022 to 0.110, p = 0.003). Patients who received oxygen therapy were treated for 3.2 days longer than those who did not receive oxygen therapy (95% CI: 0.653 to 5726, p = 0.014), and each unit increase in CRP level was associated with a 0.02-day reduction in the length of hospitalization (95% CI: 0.005 to 0.028, p = 0.004). Conclusions: Based on the presented results, COVID-19-positive patients with diabetes had, on average, longer hospitalizations than COVID-19 patients without diabetes. The hospital treatment of patients with T2DM and a milder form of COVID-19 was associated with older age, the use of oxygen therapy, and elevated CRP values. Patients who received oxygen therapy were treated approximately 3 days longer than those who did not receive this therapy.

Predictive model for early detection of type 2 diabetes using patients' clinical symptoms, demographic features, and knowledge of diabetes

Background and Aims

With the global rise in type 2 diabetes, predictive modeling has become crucial for early detection, particularly in populations with low routine medical checkup profiles. This study aimed to develop a predictive model for type 2 diabetes using health check-up data focusing on clinical details, demographic features, biochemical markers, and diabetes knowledge.

Methods

Data from 444 Nigerian patients were collected and analysed. We used 80% of this data set for training, and the remaining 20% for testing. Multivariable penalized logistic regression was employed to predict the disease onset, incorporating waist-hip ratio (WHR), triglycerides (TG), catalase, and atherogenic indices of plasma (AIP).

Results

The predictive model demonstrated high accuracy, with an area under the curve of 99% (95% CI = 97%-100%) for the training set and 94% (95% CI = 89%-99%) for the test set. Notably, an increase in WHR (adjusted odds ratio [AOR] = 70.35; 95% CI = 10.04-493.1, p-value < 0.001) and elevated AIP (AOR = 4.55; 95% CI = 1.48-13.95, p-value = 0.008) levels were significantly associated with a higher risk of type 2 diabetes, while higher catalase levels (AOR = 0.33; 95% CI = 0.22-0.49, p < 0.001) correlated with a decreased risk. In contrast, TG levels (AOR = 1.04; 95% CI = 0.40-2.71, p-value = 0.94) were not associated with the disease.

Conclusion

This study emphasizes the importance of using distinct clinical and biochemical markers for early type 2 diabetes detection in Nigeria, reflecting global trends in diabetes modeling, and highlighting the need for context-specific methods. The development of a web application based on these results aims to facilitate the early identification of individuals at risk, potentially reducing health complications, and improving diabetes management strategies in diverse settings.

Diabetes is associated with increased risk of death in COVID-19 hospitalizations in Mexico 2020: A retrospective cohort study

Background and Aim

The COVID-19 disease course can be thought of as a function of prior risk factors consisting of comorbidities and outcomes. Survival analysis data for diabetic patients with COVID-19 from an up to date and representative sample can increase efficiency in resource allocation. The study aimed to quantify mortality in Mexico for individuals with diabetes in the setting of COVID-19 hospitalization.

Methods

This retrospective cohort study utilized publicly available data from the Mexican Federal Government, covering the period from April 14, 2020, to December 20, 2020 (last accessed). Survival analysis techniques were applied, including Kaplan-Meier curves to estimate survival probabilities, log-rank tests to compare survival between groups, Cox proportional hazard models to assess the association between diabetes and mortality risk, and restricted mean survival time (RMST) analyses to measure the average survival time.

Results

A total of 402,388 adults age greater than 18 with COVID-19 were used in the analysis. Mean age = 16.16 (SD = 15.55), 214,161 males (53%). Twenty-day Kaplan-Meier estimates of mortality were 32% for COVID-19 patients with diabetes and 10.2% for those without diabetes with log-rank p < 0.01. Univariable analysis showed increased mortality in diabetic patients (hazard ratio [HR]: 3.61, 95% confidence interval [CI]: 3.54-3.67, p < 0.01) showing a 254% increase in death. After controlling for confounding variables, multivariate analysis continued to show increased mortality in diabetics (HR: 1.37, 95% CI: 1.29-1.44, p < 0.01) indicating a 37% increase in death. Multivariable RMST at Day 20 showed in Mexico, hospitalized COVID-19 patients were associated with less mean survival time by 2.01 days (p < 0.01) and a 10% increased mortality (p < 0.01).

Conclusions

In the present analysis, COVID-19 patients with diabetes in Mexico had shorter survival times. Further interventions aimed at improving comorbidities in the population, particularly in individuals with diabetes, may contribute to better outcomes in COVID-19 patients.