Comparative Analysis of COVID-19 Outcomes in Type 1 and Type 2 Diabetes: A Three-Year Retrospective Study.

Background and Objectives: This comprehensive retrospective study assesses COVID-19 outcomes in type 1 (T1D) and type 2 diabetes (T2D) patients across three years, focusing on how these outcomes varied with the evolving pandemic and changes in diabetes management. The study aims to determine if COVID-19 outcomes, including severity, intensive care unit (ICU) admission rates, duration of hospitalization, and mortality, are significantly different between these diabetes subtypes. Materials and Methods: The study analyzed data from patients admitted to the Victor Babes Hospital for Infectious Diseases and Pulmonology with confirmed COVID-19 and pre-existing diabetes, from the years 2020, 2021, and 2022. Results: Among 486 patients (200 without diabetes, 62 with T1D, 224 with T2D), T2D patients showed notably higher severity, with 33.5% experiencing severe cases, compared to 25.8% in T1D. Mortality rates were 11.6% in T2D and 8.1% in T1D. T2D patients had longer hospital stays (11.6 ± 7.0 days) compared to T1D (9.1 ± 5.8 days) and were more likely to require ICU admission (OR: 2.24) and mechanical ventilation (OR: 2.46). Hyperglycemia at admission was significantly higher in the diabetes groups, particularly in T2D (178.3 ± 34.7 mg/dL) compared to T1D (164.8 ± 39.6 mg/dL). Conclusions: The study reveals a discernible difference in COVID-19 outcomes between T1D and T2D, with T2D patients having longer hospital admissions, mechanical ventilation necessities, and mortality risks.

Environmental Factors Influencing the Dynamics and Evolution of COVID-19: A Systematic Review on the Study of Short-Term Ozone Exposure.

The potential influence of environmental factors, particularly air pollutants such as ozone (O3), on the dynamics and progression of COVID-19 remains a significant concern. This study aimed to systematically review and analyze the current body of literature to assess the impact of short-term ozone exposure on COVID-19 transmission dynamics and disease evolution. A rigorous systematic review was conducted in March 2023, covering studies from January 2020 to January 2023 found in PubMed, Web of Science, and Scopus. We followed the PRISMA guidelines and PROSPERO criteria, focusing exclusively on the effects of short-term ozone exposure on COVID-19. The literature search was restricted to English-language journal articles, with the inclusion and exclusion criteria strictly adhered to. Out of 4674 identified studies, 18 fulfilled the inclusion criteria, conducted across eight countries. The findings showed a varied association between short-term ozone exposure and COVID-19 incidence, severity, and mortality. Some studies reported a higher association between ozone exposure and incidence in institutional settings (OR: 1.06, 95% CI: 1.00-1.13) compared to the general population (OR: 1.00, 95% CI: 0.98-1.03). The present research identified a positive association between ozone exposure and both total and active COVID-19 cases as well as related deaths (coefficient for cases: 0.214; for recoveries: 0.216; for active cases: 0.467; for deaths: 0.215). Other studies also found positive associations between ozone levels and COVID-19 cases and deaths, while fewer reports identified a negative association between ozone exposure and COVID-19 incidence (coefficient: -0.187) and mortality (coefficient: -0.215). Conversely, some studies found no significant association between ozone exposure and COVID-19, suggesting a complex and potentially region-specific relationship. The relationship between short-term ozone exposure and COVID-19 dynamics is complex and multifaceted, indicating both positive and negative associations. These variations are possibly due to demographic and regional factors. Further research is necessary to bridge current knowledge gaps, especially considering the potential influence of short-term O3 exposure on COVID-19 outcomes and the broader implications on public health policy and preventive strategies during pandemics.

Developing Prediction Models for COVID-19 Outcomes: A Valuable Tool for Resource-Limited Hospitals.

Purpose: Coronavirus disease is a global pandemic with millions of confirmed cases and hundreds of thousands of deaths worldwide that continues to create a significant burden on the healthcare systems. The aim of this study was to determine the patient clinical and paraclinical profiles that associate with COVID-19 unfavourable outcome and generate a prediction model that could separate between high-risk and low-risk groups. Patients and Methods: The present study is a multivariate observational retrospective study. A total of 483 patients, residents of the municipality of Timișoara, the biggest city in the Western Region of Romania, were included in the study group that was further divided into 3 sub-groups in accordance with the disease severity form. Results: Increased age (cOR=1.09, 95% CI: 1.06-1.11, p<0.001), cardiovascular diseases (cOR=3.37, 95% CI: 1.96-6.08, p<0.001), renal disease (cOR=4.26, 95% CI: 2.13-8.52, p<0.001), and neurological disorder (cOR=5.46, 95% CI: 2.71-11.01, p<0.001) were all independently significantly correlated with an unfavourable outcome in the study group. The severe form increases the risk of an unfavourable outcome 19.59 times (95% CI: 11.57-34.10, p<0.001), while older age remains an independent risk factor even when disease severity is included in the statistical model. An unfavourable outcome was positively associated with increased values for the following paraclinical parameters: white blood count (WBC; cOR=1.10, 95% CI: 1.05-1.15, p<0.001), absolute neutrophil count (ANC; cOR=1.15, 95% CI: 1.09-1.21, p<0.001) and C-reactive protein (CRP; cOR=1.007, 95% CI: 1.004-1.009, p<0.001). The best prediction model including age, ANC and CRP achieved a receiver operating characteristic (ROC) curve with the area under the curve (AUC) = 0.845 (95% CI: 0.813-0.877, p<0.001); cut-off value = 0.12; sensitivity = 72.3%; specificity = 83.9%. Conclusion: This model and risk profiling may contribute to a more precise allocation of limited healthcare resources in a clinical setup and can guide the development of strategies for disease management.

Analysis of Deaths and Favorable Developments of Patients with SARS-CoV-2 Hospitalized in the Largest Hospital for Infectious Diseases and Pneumo-Phthisiology in the West of the Country.

Purpose: Romania is one of the European countries that has been hit the hardest by the severe acute respiratory syndrome caused by the new coronavirus SARS-CoV-2, with over 1.91 million reported cases and over 59,257 deaths. The aim of this study was to identify the main predictors of death in hospitalized patients. Patients and Methods: In the period from 1 March 2020 to 30 June 2021, an observational, retrospective, randomized, case-control study was conducted, which included a sample of 139 patients who died in hospital and another sample of 275 patients who had been discharged in an improved or healed condition. Confirmation of COVID-19 cases was performed by RT-PCR from nasopharyngeal and oropharyngeal exudates. Statistical data were analyzed by logistic regression, Cox regression and a comparison of survival curves by the log-rank (Mantel-Cox) test. Results: The most powerful logistic regression model identified the following independent predictors of death: history of coagulopathy HR = 30.73 [1.94-487.09], p = 0.015; high percentage of neutrophils HR = 1.09 [1.01-1.19], p = 0.027; and decreased blood-oxygenation HR = 53881.97 [1762.24-1647489.44], p < 0.001. Cox regression identified the following factors that influenced the evolution of cases: history of coagulopathy HR = 2.44 [1.38-4.35], p = 0.000; O2 saturation HR = 0.98 [0.96-0.99], p = 0.043; serum creatinine HR = 1.23 [1.08-1.39], p = 0.001; dyspnea on admission HR = 2.99 [1.42-6.30], p = 0.004; hospitalization directly in the ICU HR = 3.803 [1.97-7.33], p < 0.001; heart damage HR = 16.76 [1.49-188.56], p = 0.022; and decreased blood-oxygenation HR = 35.12 [5.92-208.19], p < 0.001. Conclusion: Knowledge of the predictors of death in hospitalized patients allows for the future optimization of triage and therapeutic case management for COVID-19.

The utility of indirect imagistic signs in the diagnosis of anterior cruciate ligament ruptures.

We conducted a retrospective study, between 2013 and 2018. The study was conducted by analyzing the comparative imaging of two groups of patients. The two groups comprise 42 patients, 14 women and 28 men aged between 17 and 70 years old, to whom objective variables of statistical relevance were tracked. The results of this study show that there is a significant correlation between an angle value of less than 45° and the rupture of the anterior crossed ligament.