Risk factors for COVID-19-related death, hospitalization and intensive care: a population-wide study of all inhabitants in Stockholm

Interpretability-based machine learning for predicting the risk of death from pulmonary inflammation in Chinese intensive care unit patients

Objective

The objective of this research was to create a machine learning predictive model that could be easily interpreted in order to precisely determine the risk of premature death in patients receiving intensive care after pulmonary inflammation.

Methods

In this study, information from the China intensive care units (ICU) Open Source database was used to examine data from 2790 patients who had infections between January 2019 and December 2020. A 7:3 ratio was used to randomly assign the whole patient population to training and validation groups. This study used six machine learning techniques: logistic regression, random forest, gradient boosting tree, extreme gradient boosting tree (XGBoost), multilayer perceptron, and K-nearest neighbor. A cross-validation grid search method was used to search the parameters in each model. Eight metrics were used to assess the models' performance: accuracy, precision, recall, F1 score, area under the curve (AUC) value, Brier score, Jordon's index, and calibration slope. The machine methods were ranked based on how well they performed in each of these metrics. The best-performing models were selected for interpretation using both the Shapley Additive exPlanations (SHAP) and Local interpretable model-agnostic explanations (LIME) interpretable techniques.

Results

A subset of the study cohort's patients (120/1668, or 7.19%) died in the hospital following screening for inclusion and exclusion criteria. Using a cross-validated grid search to evaluate the six machine learning techniques, XGBoost showed good discriminative ability, achieving an accuracy score of 0.889 (0.874-0.904), precision score of 0.871 (0.849-0.893), recall score of 0.913 (0.890-0.936), F1 score of 0.891 (0.876-0.906), and AUC of 0.956 (0.939-0.973). Additionally, XGBoost exhibited excellent performance with a Brier score of 0.050, Jordon index of 0.947, and calibration slope of 1.074. It was also possible to create an interactive internet page using the XGBoost model.

Conclusion

By identifying patients at higher risk of early mortality, machine learning-based mortality risk prediction models have the potential to significantly improve patient care by directing clinical decision making and enabling early detection of survival and mortality issues in patients with pulmonary inflammation disease.

Association Between Artificial Intelligence Based Chest Computed Tomography and Clinical/Laboratory Characteristics with Severity and Mortality in COVID-19 Hospitalized Patients

Background

Some patients with COVID-19 rapidly develop respiratory failure or mortality, underscoring the necessity for early identification of those prone to severe illness. Numerous studies focus on clinical and lab traits, but only few attend to chest computed tomography. The current study seeks to numerically quantify pulmonary lesions using early-phase CT scans calculated through artificial intelligence algorithms in conjunction with clinical and laboratory helps clinicians to early identify the development of severe illness and death in a group of COVID-19 patients.

Methods

From December 15, 2022, to January 30, 2023, 191 confirmed COVID-19 patients admitted to Xinhua Hospital Affiliated with Shanghai Jiao Tong University School of Medicine were consecutively enrolled. All patients underwent chest CT scans and serum tests within 48 hours prior to admission. Variables significantly linked to critical illness or mortality in univariate analysis were subjected to multivariate logistic regression models post collinearity assessment. Adjusted odds ratio, 95% confidence intervals, sensitivity, specificity, Youden index, receiver-operator-characteristics (ROC) curves, and area under the curve (AUC) were computed for predicting severity and in-hospital mortality.

Results

Multivariate logistic analysis revealed that myoglobin (OR = 1.003, 95% CI 1.001-1.005), APACHE II score (OR = 1.387, 95% CI 1.216-1.583), and the infected CT region percentage (OR = 113.897, 95% CI 4.939-2626.496) independently correlated with in-hospital COVID-19 mortality. Prealbumin stood as an independent safeguarding factor (OR = 0.965, 95% CI 0.947-0.984). Neutrophil counts (OR = 1.529, 95% CI 1.131-2.068), urea nitrogen (OR = 1.587, 95% CI 1.222-2.062), SOFA score(OR = 3.333, 95% CI 1.476-7.522), qSOFA score(OR = 15.197, 95% CI 3.281-70.384), PSI score(OR = 1.053, 95% CI 1.018-1.090), and the infected CT region percentage (OR = 548.221, 95% CI 2.615-114,953.586) independently linked to COVID-19 patient severity.

Three Years of the Coronavirus Disease 2019 Pandemic in a European Region: A Population-Based Longitudinal Assessment in Madrid Between 2020 and 2022

Background

Our objective was to assess the health impact of coronavirus disease 2019 (COVID-19) during 2020-2022 in the Madrid region.

Methods

We included all individuals registered in the Madrid Health System Registry as of 31 December 2019, and followed them until 31 December 2022. Using a unique personal identifier, we linked the databases of primary care, hospitals, pharmacies, certified laboratories performing diagnostic tests, vaccines, and mortality.

Results

Of 6 833 423 individuals, 21.4% had a confirmed COVID-19 diagnosis, and 1.5% had a COVID-19 hospitalization (primary diagnosis). Thirty-day mortality was 1.6% for confirmed COVID-19 (from 11.4% in first semester 2020 to 0.4% in first semester 2022). Thirty-day mortality was 10.8% for COVID-19 hospitalizations (from 14.0% in first semester 2020 to 6.0% in second semester 2022). There were 24 073 deaths within 30 days of a confirmed COVID-19 diagnosis. Advanced age, male sex, higher socioeconomic deprivation, and comorbidities were associated with higher mortality.

Conclusions

By linking administrative and clinical databases, we characterized the burden of the COVID-19 pandemic in Madrid over 3 years. Our analysis proposes a high-level framework for comparisons of the burden of COVID-19 across areas worldwide.

Does atrial fibrillation affect prognosis in hospitalised COVID-19 patients? A multicentre historical cohort study in the Netherlands

OBJECTIVES

The aim of this multicentre COVID-PREDICT study (a nationwide observational cohort study that aims to better understand clinical course of COVID-19 and to predict which COVID-19 patients should receive which treatment and which type of care) was to determine the association between atrial fibrillation (AF) and mortality, intensive care unit (ICU) admission, complications and discharge destination in hospitalised COVID-19 patients.

SETTING

Data from a historical cohort study in eight hospitals (both academic and non-academic) in the Netherlands between January 2020 and July 2021 were used in this study.

PARTICIPANTS

3064 hospitalised COVID-19 patients >18 years old.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was the incidence of new-onset AF during hospitalisation. Secondary outcomes were the association between new-onset AF (vs prevalent or non-AF) and mortality, ICU admissions, complications and discharge destination, performed by univariable and multivariable logistic regression analyses.

RESULTS

Of the 3064 included patients (60.6% men, median age: 65 years, IQR 55-75 years), 72 (2.3%) patients had prevalent AF and 164 (5.4%) patients developed new-onset AF during hospitalisation. Compared with patients without AF, patients with new-onset AF had a higher incidence of death (adjusted OR (aOR) 1.71, 95% CI 1.17 to 2.59) an ICU admission (aOR 5.45, 95% CI 3.90 to 7.61). Mortality was non-significantly different between patients with prevalent AF and those with new-onset AF (aOR 0.97, 95% CI 0.53 to 1.76). However, new-onset AF was associated with a higher incidence of ICU admission and complications compared with prevalent AF (OR 6.34, 95% CI 2.95 to 13.63, OR 3.04, 95% CI 1.67 to 5.55, respectively).

CONCLUSION

New-onset AF was associated with an increased incidence of death, ICU admission, complications and a lower chance to be discharged home. These effects were far less pronounced in patients with prevalent AF. Therefore, new-onset AF seems to represent a marker of disease severity, rather than a cause of adverse outcomes.

Comparative efficacy and safety of nirmatrelvir/ritonavir and molnupiravir for COVID-19: A systematic review and meta-analysis

This study aimed to compare the efficacy and safety of nirmatrelvir/ritonavir (Paxlovid) with molnupiravir in the treatment of coronavirus disease 2019 (COVID-19). To end this, PubMed, Cochrane Library, Web of Science, medRxiv, and Google Scholar were systematically searched to collect relevant evidence up to February 15, 2023. The risk of bias was evaluated using the risk of bias in nonrandomized studies of interventions tool. Data were analyzed using Comprehensive Meta-Analysis software. Eighteen studies involving 57 659 patients were included in the meta-analysis. The meta-analysis showed a significant difference between nirmatrelvir/ritonavir and molnupiravir in terms of all-cause mortality rate (odds ratio [OR] = 0.54, 95% confidence interval [CI]: 0.44-0.67), all-cause hospitalization rate (OR = 0.61, 95% CI: 0.54-0.69), death or hospitalization rate (OR = 0.61, 95% CI: 0.38-0.99), and negative polymerase chain reaction conversion time (mean difference = -1.55, 95% CI: -1.74 to -1.37). However, no significant difference was observed between the two groups in terms of COVID-19 rebound (OR = 0.87, 95% CI: 0.71-1.07). In terms of safety, although the incidence of any adverse events was higher in the nirmatrelvir/ritonavir group (OR = 2.52, 95% CI: 1.57-4.06), no significant difference was observed between the two treatments in terms of adverse events leading to treatment discontinuation (OR = 1.18, 95% CI: 0.69-2.00). The present meta-analysis demonstrated the significant superiority of nirmatrelvir/ritonavir over molnupiravir in improving clinical efficacy in COVID-19 patients during the prevalence of Omicron variant. These findings, however, need to be further confirmed.

Phase Angle and Handgrip Strength as Predictors of Clinical Outcomes in Hospitalized COVID-19 Patients

Phase angle (PhA) and muscle strength are predictors of clinical outcomes in critically ill patients. Malnutrition may affect body composition measurements. The aim of this prospective study was to investigate the association between PhA and handgrip strength (HGS), and clinical outcomes in hospitalized COVID-19 patients. The study included a total of 102 patients. Both PhA and HGS were measured twice, within 48 h of hospital admission and on the 7th day of hospitalization. The primary outcome was the clinical status on the 28th day of hospitalization. Secondary outcomes included the hospital length of stay (LOS), the concentrations of ferritin, C-reactive protein and albumin, oxygen requirements and the severity of pneumonia. A one-way analysis of variance (ANOVA) test and Spearman rS correlation coefficient were used for statistical analysis. No differences were found for PhA [on day 1 (p = 0.769) and day 7 (p = 0.807)] and the primary outcome. A difference was found between HGS on day 1 and the primary outcome (p = 0.008), while no difference was found for HGS on day 7 (p = 0.476). Body mass index was found to be associated with the oxygen requirement on day 7 (p = 0.005). LOS was correlated neither with PhA (rs = −0.081, p = 0.422) nor with HGS (rs = 0.137, p = 0.177) on the first day. HGS could be a useful indicator of clinical outcomes in COVID-19 patients, while PhA does not seem to have a clinical impact. However, further research is needed to validate the results of our study.

Mortality-associated Risk Factors in Hospitalized COVID-19 Patients in Japan: Findings of the CLOT-COVID Study

BACKGROUND

Reports of mortality-associated risk factors in patients with the novel coronavirus disease 2019 (COVID-19) are limited.

METHODS

We evaluated the clinical features that were associated with mortality among patients who died during hospitalization (n = 158) and those who were alive at discharge (n = 2,736) from the large-scale, multicenter, retrospective, observational cohort CLOT-COVID study, which enrolled consecutively hospitalized COVID-19 patients from 16 centers in Japan from April to September 2021. Data from 2,894 hospitalized COVID-19 participants of the CLOT-COVID study were analyzed in this study.

RESULTS

Patients who died were older (71.1 years vs 51.6 years, P < 0.001), had higher median D-dimer values on admission (1.7 µg/mL vs 0.8 µg/mL, P < 0.001), and had more comorbidities. On admission, the patients who died had more severe COVID-19 than did those who survived (mild: 16% vs 63%, moderate: 47% vs 31%, and severe: 37% vs 6.2%, P < 0.001). In patients who died, the incidence of thrombosis and major bleeding during hospitalization was significantly higher than that in those who survived (thrombosis: 8.2% vs 1.5%, P < 0.001; major bleeding: 12.7% vs 1.4%, P < 0.001). Multivariable logistic regression analysis revealed that age >70 years, high D-dimer values on admission, heart disease, active cancer, higher COVID-19 severity on admission, and development of major bleeding during hospitalization were independently associated with a higher mortality risk.

CONCLUSION

This large-scale observational study in Japan identified several independent risk factors for mortality in hospitalized patients with COVID-19 that could facilitate appropriate risk stratification of patients with COVID-19.

COVID-19 and comedications in atrial fibrillation-a case-control study in Stockholm

To test the main hypothesis that anticoagulation reduces risk of hospitalization, intensive care unit (ICU) admission and death in COVID-19. Nested case-control study among patients with atrial fibrillation (AF) in Stockholm. COVID-19 cases were matched to five disease-free controls with same sex, born within ± 1 years. Source population was individuals in Stockholm with AF 1997-2020. Swedish regional and national registers are used. National registers cover hospitals and outpatient clinics, local registers cover primary care. Records were linked through the personal identity number assigned to each Swedish resident. Cases were individuals with COVID-19 (diagnosis, ICU admission, or death). The AF source population consisted of 179,381 individuals from which 7548 cases were identified together with 37,145 controls. The number of cases (controls) identified from hospitalization, ICU admission or death were 5916 (29,035), 160 (750) and 1472 (7,360). The proportion of women was 40% for hospitalization and death, but 20% and 30% for admission to ICU in wave one and two, respectively. Primary outcome was mortality, secondary outcome was hospitalization, tertiary outcome was ICU admission, all with COVID-19. Odds ratios (95% confidence interval) for antithrombotics were 0.79 (0.66-0.95) for the first wave and 0.80 (0.64-1.01) for the second wave. Use of anticoagulation among patients with arrythmias infected with COVID-19 is associated with lower risk of hospitalization and death. If further COVID-variants emerge, or other infections with prothrombotic properties, this emphasize need for physicians to ensure compliance among vulnerable patients.

Association Between the Development of Thrombosis and Worsening of Disease Severity in Patients With Moderate COVID-19 on Admission - From the CLOT-COVID Study

BACKGROUND

The worsening of coronavirus disease 2019 (COVID-19) severity is a critical issue in current clinical settings and may be associated with the development of thrombosis.Methods and Results: This study used patient data obtained in the CLOT-COVID study, a retrospective multicenter cohort study. The demographics of patients with moderate COVID-19 on admission with and without worsened severity during hospitalization were compared and predictors were identified. Of 927 patients with moderate COVID-19 on admission, 182 (19.6%) had worsened severity during hospitalization. Patients with worsening of severity were older, more likely to have hypertension, diabetes, heart disease, and active cancer, and more likely to use pharmacological thromboprophylaxis. Patients with worsening of severity had higher D-dimer levels on admission and were more likely to develop thrombosis and major bleeding during hospitalization than those without worsening. Increased age (odds ratio [OR]: 1.02, 95% confidence interval [CI]: 1.01-1.03, P=0.005), diabetes (OR: 1.63, 95% CI: 1.11-2.33, P=0.012), D-dimer levels >1.0 μg/mL on admission (OR: 2.10, 95% CI: 1.45-3.03, P<0.001), and thrombosis (OR: 6.28, 95% CI: 2.72-14.53, P<0.001) were independently associated with worsening of COVID-19 severity.

CONCLUSIONS

Approximately 20% of patients with moderate COVID-19 had worsened severity during hospitalization. Increased age, diabetes, D-dimer levels >1.0 μg/mL on admission, and the development of thrombosis during hospitalization were significantly associated with worsened COVID-19 severity.

The Role of CRP POC Testing in the Fight against Antibiotic Overuse in European Primary Care: Recommendations from a European Expert Panel

Tackling antibiotic resistance represents one of the major challenges in modern medicine, and limiting antibiotics' overuse represents the first step in this fight. Most antibiotics are prescribed in primary care settings, and lower respiratory tract infections (LRTIs) are one of the most common indications for their prescription. An expert panel conducted an extensive report on C-reactive protein point-of-care (CRP POC) testing in the evaluation of LRTIs and its usefulness to limit antibiotic prescriptions. The expert panel stated that CRP POC testing is a potentially useful tool to limit antibiotic prescriptions for LRTI in a community setting. CRP POC must be used in conjunction with other strategies such as improved communication skills and the use of other molecular POC testing. Potential barriers to the adoption of CRP POC testing are financial and logistical issues. Moreover, the efficacy in limiting antibiotic prescriptions could be hampered by the fact that, in some countries, patients may gain access to antibiotics even without a prescription. Through the realization of a better reimbursement structure, the inclusion in standardized procedures in local guidelines, and better patient education, CRP point-of-care testing can represent a cornerstone in the fight against antimicrobial resistance.

Individual and neighborhood risk factors of hospital admission and death during the COVID-19 pandemic: a population-based cohort study

BACKGROUND

The coronavirus disease 2019 (COVID-19) disproportionately affects minority populations in the USA. Sweden - like other Nordic countries - have less income and wealth inequality but lacks data on the socioeconomic impact on the risk of adverse outcomes due to COVID-19.

METHODS

This population-wide study from March 2020 to March 2022 included all adults in Stockholm, except those in nursing homes or receiving in-home care. Data sources include hospitals, primary care (individual diagnoses), the Swedish National Tax Agency (death dates), the Total Population Register "RTB" (sex, age, birth country), the Household Register (size of household), the Integrated Database For Labor Market Research "LISA" (educational level, income, and occupation), and SmiNet (COVID data). Individual exposures include education, income, type of work and ability to work from home, living area and living conditions as well as the individual country of origin and co-morbidities. Additionally, we have data on the risks associated with living areas. We used a Cox proportional hazards model and logistic regression to estimate associations. Area-level covariates were used in a principal component analysis to generate a measurement of neighborhood deprivation. As outcomes, we used hospitalization and death due to COVID-19.

RESULTS

Among the 1,782,125 persons, male sex, comorbidities, higher age, and not being born in Sweden increase the risk of hospitalization and death. So does lower education and lower income, the lowest incomes doubled the risk of death from COVID-19. Area estimates, where the model includes individual risks, show that high population density and a high percentage of foreign-born inhabitants increased the risk of hospitalization.

CONCLUSIONS

Segregation and deprivation are public health issues elucidated by COVID-19. Neighborhood deprivation, prevalent in Stockholm, adds to individual risks and is associated with hospitalization and death. This finding is paramount for governments, agencies, and healthcare institutions interested in targeted interventions.

Association of BMI with general health, working capacity recovered, and post-acute sequelae of COVID-19

OBJECTIVE

The aim of this study was to determine the risk of post-acute sequelae of COVID-19 associated with the continuous spectrum of BMI.

METHODS

Epidemiology of Long COVID (EPILOC) is a population-based study conducted in Baden-Württemberg (Germany), including subjects aged 18 to 65 years who tested positive for SARS-CoV-2 between October 2020 and April 2021. Eligible subjects answered a standardized questionnaire, including sociodemographic characteristics, lifestyle factors, and the presence of specific symptoms. Participants assessed their current general health recovery and working capacity compared with the pre-infection situation and provided their body height and weight. Generalized additive models were used to assess the association of BMI with general health recovered, working capacity recovered, and prevalence of fatigue, cognitive impairment, and chest symptoms.

RESULTS

The analyses included 11,296 individuals (41% male), with a mean age of 44.0 (SD 13.7) years. Best general health recovery was observed at BMI of 22.1 (95% CI: 21.0-27.0) kg/m² in men and BMI of 21.6 (95% CI: 20.3-23.1) kg/m² in women. In addition, we found that increasing BMI was consistently associated with post-COVID fatigue, neurocognitive impairment, and chest symptoms.

CONCLUSIONS

High BMI contributes to impaired recovery after SARS-CoV-2 infection; however, a low BMI is associated with impaired recovery as well.

Influence of obesity on incidence of thrombosis and disease severity in patients with COVID-19: From the CLOT-COVID study

BACKGROUND

The influence of obesity on the development of thrombosis and severity of coronavirus disease 2019 (COVID-19) remains unclear.

METHOD

The CLOT-COVID study was a retrospective multicenter cohort study enrolling 2894 consecutive hospitalized patients with COVID-19 between April 2021 and September 2021 among 16 centers in Japan. The present study consisted of 2690 patients aged over 18 years with available body mass index (BMI), who were divided into an obesity group (BMI ≥30) (N = 457) and a non-obesity group (BMI <30) (N = 2233).

RESULTS

The obesity group showed more severe status of COVID-19 at admission compared with the non-obesity group. The incidence of thrombosis was not significantly different between the groups (obesity group: 2.6 % versus non-obesity group: 1.9 %, p = 0.39), while the incidence of a composite outcome of all-cause death, or requirement of mechanical ventilation or extracorporeal membrane oxygenation during hospitalization was significantly higher in the obesity group (20.1 % versus 15.0 %, p < 0.01). After adjusting confounders in the multivariable logistic regression model, the risk of obesity relative to non-obesity for thrombosis was not significant (adjusted OR, 1.39; 95 % CI, 0.68-2.84, p = 0.37), while the adjusted risk of obesity relative to non-obesity for the composite outcome was significant (adjusted OR, 1.85; 95 % CI, 1.39-2.47, p < 0.001).

CONCLUSIONS

In the present large-scale observational study, obesity was not significantly associated with the development of thrombosis during hospitalization; however, it was associated with severity of COVID-19.

Drug-Drug Interactions among Patients Hospitalized with COVID-19 in Greece

The modulation of the pharmacological action of drugs due to drug-drug interactions (DDIs) is a critical issue in healthcare. The aim of this study was to evaluate the prevalence and the clinical significance of potential DDIs in patients admitted to the University Hospital of Heraklion in Greece with coronavirus disease 2019 (COVID-19). Cardiovascular disorders (58.4%) and diabetes (types I and II) (29.6%) were the most common comorbidities. A high occurrence of DDIs was observed, and clinically significant DDIs that may hamper response to treatment represented 40.3% of cases on admission, 21% during hospitalization, and 40.7% upon discharge. Polypharmacy and comorbidities were associated with a higher prevalence of DDIs in a statistically significant way (p < 0.05, 95% CI). Clinically significant DDIs and increased C-reactive protein values upon admission were associated with prolonged hospitalization. The results reveal that patients admitted due to COVID-19 in Greece often have an additional burden of DDIs that healthcare teams should approach and resolve.

COVID-19 vaccine booster significantly decreases the risk of intensive care unit hospitalization in heart failure patients during the Omicron variant wave: A population-based study

Background

Heart failure (HF) patients are at higher risk of severe coronavirus disease 2019 (COVID-19). The Omicron variant has many novel mutations including those in the spike protein, leading to questions about vaccine effectiveness. The aim of this analysis was to evaluate the effectiveness of the COVID-19 vaccine with or without a booster (i.e., after the third dose) during the Omicron variant wave.

Methods

Chronic heart failure patients in the Czech Republic were included in the analysis. COVID-19 infection was monitored from January 1st 2022 to March 31st 2022. The analysis was conducted on data collected in the National Health Information System. Vaccine effectiveness of vaccinated (with or without booster) vs. unvaccinated patients was analyzed for incidence of COVID-19, COVID-19-related hospitalizations, COVID-19 related intensive care unit admissions, and COVID-19 related mechanical ventilation/extracorporeal membrane oxygenation treatment.

Findings

From a total 165,453 HF patients in the Czech Republic, 9,728 contracted COVID-19 (22.9% of them not vaccinated, 23.2% vaccinated and 53.8% vaccinated and boosted). Risk of intensive care unit (ICU) hospitalization was 7.6% in the unvaccinated group, 4.8% in the vaccinated group and 2.9% in the boosted group. The calculated effectiveness of the COVID-19 vaccine in prevention of ICU hospitalization in the vaccinated group was 41.9 and 76.6% in the boosted group.

Interpretation

The results demonstrated moderate vaccine effectiveness in the prevention of severe COVID-19 in vaccinated but not boosted HF patients. Much stronger effectiveness was found in those who were vaccinated and boosted.

COVID-19 outcomes in patients taking cardioprotective medications

Introduction

The coronavirus disease 2019 (COVID-19) caused a worldwide pandemic and has led to over five million deaths. Many cardiovascular risk factors (e.g. obesity or diabetes) are associated with an increased risk of adverse outcomes in COVID-19. On the other hand, it has been suggested that medications used to treat cardiometabolic conditions may have protective effects for patients with COVID-19.

Objectives

To determine whether patients taking four classes of cardioprotective medications—aspirin, metformin, renin angiotensin aldosterone system inhibitors (RAASi) and statins–have a lower risk of adverse outcomes of COVID-19.

Methods

We conducted a retrospective cohort study of primary care patients at a large integrated healthcare delivery system who had a positive COVID-19 test between March 2020 and March 2021. We compared outcomes of patients who were taking one of the study medications at the time of the COVID-19 test to patients who took a medication from the same class in the past (to minimize bias by indication). The following outcomes were compared: a) hospitalization; b) ICU admission; c) intubation; and d) death. Multivariable analysis was used to adjust for patient demographics and comorbidities.

Results

Among 13,585 study patients, 1,970 (14.5%) were hospitalized; 763 (5.6%) were admitted to an ICU; 373 (2.8%) were intubated and 720 (5.3%) died. In bivariate analyses, patients taking metformin, RAASi and statins had lower risk of hospitalization, ICU admission and death. However, in multivariable analysis, only the lower risk of death remained statistically significant. Patients taking aspirin had a significantly higher risk of hospitalization in both bivariate and multivariable analyses.

Conclusions

Cardioprotective medications were not associated with a consistent benefit in COVID-19. As vaccination and effective treatments are not yet universally accessible worldwide, research should continue to determine whether affordable and widely available medications could be utilized to decrease the risks of this disease.

Diabetes and COVID-19 testing, positivity, and mortality: A population-wide study in Northern Italy

AIMS

To assess if patients with type 2 diabetes mellitus (DM2) are: a) at excess risk of undergoing testing, contracting, and dying from SARS-CoV-2 infection compared to the general population; b) whether cardiovascular diseases (CAVDs) contribute to COVID-19-related death; and c) what is the effect of DM2 duration and control on COVID-19-related death.

METHODS

This population-based study involved all 449,440 adult residents of the Reggio Emilia province, Italy. DM2 patients were divided in groups by COVID testing, presence of CAVDs and COVID death. Several mediation analyses were performed.

RESULTS

Patients with DM2 had an increased likelihood of being tested (Odds ratio, OR 1.27 95 %CI 1.23-1.30), testing positive (OR 1.21 95 %CI 1.16-1.26) and dying from COVID-19 (OR 1.75 95 %CI 1.54-2.00). COVID-19-related death was almost three times higher among obese vs non-obese patients with DM2 (OR 4.3 vs 1.6, respectively). For COVID-19 death, CAVDs mediated a) just 5.1 % of the total effect of DM2, b) 40 % of the effect of DM2 duration, and c) did not mediate the effect of glycemic control.

CONCLUSIONS

For COVID-19-related deaths in DM2 patients, the effect is mostly direct, obesity amplifies it, DM2 control and duration are important predictors, while CAVDs only slightly mediates it.

Risk Factors Associated with Mortality in COVID-19 Hospitalized Patients: Data from the Middle East

This study aimed to assess the risk factors for COVID-19 mortality among hospitalized patients in Jordan. All COVID-19 patients admitted to a tertiary hospital in Jordan from September 20, 2020, to August 8, 2021, were included in this study. Demographics, clinical characteristics, comorbidities, and laboratory results were extracted from the patients' electronic records. Multivariable logistic and machine learning (ML) methods were used to study variable importance. Out of 1,613 COVID-19 patients, 1,004 (62.2%) were discharged from the hospital (survived), while 609 (37.8%) died. Patients who were of elderly age (>65 years) (OR, 2.01; 95% CI, 1.28-3.16), current smokers (OR, 1.61; 95%CI, 1.17-2.23), and had severe or critical illness at admission ((OR, 1.56; 95%CI, 1.05-2.32) (OR, 2.94; 95%CI, 2.02-4.27); respectively), were at higher risk of mortality. Comorbidities including chronic kidney disease (OR, 2.90; 95% CI, 1.90-4.43), deep venous thrombosis (OR, 2.62; 95% CI, 1.08-6.35), malignancy (OR, 2.22; 95% CI, 1.46-3.38), diabetes (OR, 1.31; 95% CI, 1.04-1.65), and heart failure (OR, 1.51; 95% CI, 1.02-2.23) were significantly associated with increased risk of mortality. Laboratory abnormalities associated with mortality included hypernatremia (OR, 11.37; 95% CI, 4.33-29.81), elevated aspartate aminotransferase (OR, 1.81; 95% CI, 1.42-2.31), hypoalbuminemia (OR, 1.75; 95% CI, 1.37-2.25), and low platelets level (OR, 1.43; 95% CI, 1.05-1.95). Several demographic, clinical, and laboratory risk factors for COVID-19 mortality were identified. This study is the first to examine the risk factors associated with mortality using ML methods in the Middle East. This will contribute to a better understanding of the impact of the disease and improve the outcome of the pandemic worldwide.