SIR-M Epidemic Model: A SARS-CoV-2 Perspective

The outbreak of SARS-CoV-2 in November 2019 has been modeled into the Susceptible-Infectious-Recovery (SIR) model initially. The second wave outbreak of the mutant SARS-CoV-2 has statistically proved to hold an exponential growth of mortality rate, especially in India. The infection-recovery strategy observed could be easily modeled to the SIR(Susceptible-Infectious-Recovery) model. Also, the studies included the exposure to the virus resulting in SIER (Susceptible-Infection-Exposure-Recovery) model. The daily statistics published by the World Health Organization (WHO) also reveal unavoidable statistics that represent the count of deaths. As of May 30, 2021, India has reported 27 million total infected cases, and 32 hundred thousand deaths have been reported. This alarms that the spread of pandemics cannot be visualized as a simple SIR model. The significant ratio between the infected and the mortals leads to remodeling the SIR model as SIR-M(Susceptible-Infectious-Recovery-Mortality) model. This paper includes the death count into the model and remodels the SIR model as SIR-M(Susceptible-Infectious-Recovery-Mortality) model. Our proposed model includes a factor, namely δ, which primarily depends on the medical condition. This δ is the primary cause of the deaths in the SARS-Cov-2-affected patients. We have studied the causes of mortality in COVID-19 patients and have validated our model with the real-time COVID dataset. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Case report: New insights into persistent chronic pelvic pain syndrome with comorbid somatic symptom disorder.

Chronic pelvic pain syndrome (CPPS) is generally defined as pain in the pelvic area that persisted for 3-6 months or longer. The pain can be constant or episodic and functionally disabling. Any dysfunction of the central nervous system can lead to central sensitization, which enhances and maintains pain as well as other symptoms that are mediated by the central nervous system. It occurs in subgroups of nearly every chronic pain condition and is characterized by multifocal pain and co-occurring somatic symptoms. Somatic symptom disorder (SSD) is defined as a condition in which having one or more somatic symptoms, such as excessive worries, pressure, and catastrophic events. These symptoms can be very disruptive to a patient's life and can cause significant distress. SSD cases with severe symptoms frequently undergo repeated medical investigations and the symptoms often lead patients to seek emergency medical treatment and consult with specialists repeatedly, which is a source of frustration for patients and clinicians. Here we report a case that Asian female with persistent CPPS with comorbid SSD, who got in trouble for up to 8 years. This case reminds clinicians to pay excessive attention to the diagnosis of CPPS with comorbid SSD after recovery from acute COVID-19, with hope of raising awareness in the identification of SSD and present new insight into appropriate treatment for each woman who suffers from it.

Sulfated polysaccharides as multi target molecules to fight COVID 19 and comorbidities.

The majority of research to combat SARS-CoV-2 infection exploits the adaptive immune system, but innate immunity, the first line of defense against pathogenic microbes, is equally important in understanding and controlling infectious diseases. Various cellular mechanisms provide physiochemical barriers to microbe infection in mucosal membranes and epithelia, with extracellular polysaccharides, particularly sulfated polysaccharides, being among the most widespread and potent extracellular and secreted molecules blocking and deactivating bacteria, fungi, and viruses. New research reveals that a range of polysaccharides effectively inhibits COV-2 infection of mammalian cells in culture. This review provides an overview of sulfated polysaccharides nomenclature, its significance as immunomodulators, antioxidants, antitumors, anticoagulants, antibacterial, and as potent antivirals. It summarizes current research on various interactions of sulfated polysaccharide with a range of viruses, including SARS-CoV-2, and their application for potential treatments for COVID-19. These molecules interact with biochemical signaling in immune cell responses, by actions in oxidative reactions, cytokine signaling, receptor binding, and through antiviral and antibacterial toxicity. These properties provide the potential for the development of novel therapeutic treatments for SARS-CoV-2 and other infectious diseases from modified polysaccharides.

Adverse Effects of COVID-19 Vaccination: Machine Learning and Statistical Approach to Identify and Classify Incidences of Morbidity and Postvaccination Reactogenicity.

Good vaccine safety and reliability are essential for successfully countering infectious disease spread. A small but significant number of adverse reactions to COVID-19 vaccines have been reported. Here, we aim to identify possible common factors in such adverse reactions to enable strategies that reduce the incidence of such reactions by using patient data to classify and characterise those at risk. We examined patient medical histories and data documenting postvaccination effects and outcomes. The data analyses were conducted using a range of statistical approaches followed by a series of machine learning classification algorithms. In most cases, a group of similar features was significantly associated with poor patient reactions. These included patient prior illnesses, admission to hospitals and SARS-CoV-2 reinfection. The analyses indicated that patient age, gender, taking other medications, type-2 diabetes, hypertension, allergic history and heart disease are the most significant pre-existing factors associated with the risk of poor outcome. In addition, long duration of hospital treatments, dyspnoea, various kinds of pain, headache, cough, asthenia, and physical disability were the most significant clinical predictors. The machine learning classifiers that are trained with medical history were also able to predict patients with complication-free vaccination and have an accuracy score above 90%. Our study identifies profiles of individuals that may need extra monitoring and care (e.g., vaccination at a location with access to comprehensive clinical support) to reduce negative outcomes through classification approaches.

Clinical Characteristics and Outcomes of Patients with Acute Respiratory Failure Due to SARS-CoV-2 Interstitial Pneumonia Treated with CPAP in a Medical Intermediate Care Setting: A Retrospective Observational Study on Comparison of Four Waves.

BACKGROUND: In COVID-19 patients non-invasive-positive-pressure-ventilation (NIPPV) has held a challenging role to reduce mortality and the need for invasive mechanical ventilation (IMV). The aim of this study was to compare the characteristics of patients admitted to a Medical Intermediate Care Unit for acute respiratory failure due to SARS-CoV-2 pneumonia throughout four pandemic waves. METHODS: The clinical data of 300 COVID-19 patients treated with continuous positive airway pressure (CPAP) were retrospectively analysed, from March-2020 to April-2022. RESULTS: Non-survivors were older and more comorbid, whereas patients transferred to ICU were younger and had fewer pathologies. Patients were older (from 65 (29-91) years in I wave to 77 (32-94) in IV, p < 0.001) and with more comorbidities (from Charlson's Comorbidity Index = 3 (0-12) in I to 6 (1-12) in IV, p < 0.001). No statistical difference was found for in-hospital mortality (33.0%, 35.8%, 29.6% and 45.9% in I, II, III and IV, p = 0.216), although ICU-transfers rate decreased from 22.0% to 1.4%. CONCLUSIONS: COVID-19 patients have become progressively older and with more comorbidities even in critical care area; from risk class analyses by age and comorbidity burden, in-hospital mortality rates remain high and are thus consistent over four waves while ICU-transfers have significantly reduced. Epidemiological changes need to be considered to improve the appropriateness of care.

Identifying Risk Factors for Complication and Readmission with Same-Day Discharge Arthroplasty.

BACKGROUND: The COVID-19 pandemic caused a surge of same-day discharge (SDD) for total joint arthroplasty. However, SDD may not be beneficial for all patients. Therefore, continued investigation into the safety of SDD is necessary as well as risk stratification for improved patient outcomes. METHODS: This retrospective cohort study examined 31,851 elective SDD hip and knee arthroplasties from 2016 to 2020 in a large national database. Logistic regression models were used to identify patient variables and preoperative comorbidities that contribute to postoperative complication or readmission with SDD. Adjusted odds ratios (AOR) and 95% confidence intervals (CI) were calculated. RESULTS: SDD increased from 1.4% in 2016 to 14.6% in 2020. SDD is associated with lower odds of readmission (AOR: 0.994, CI: 0.992-0.996) and postoperative complications (AOR: 0.998, CI: 0.997-1.000). Patients who have preoperative dyspnea (AOR: 1.03, CI: 1.02-1.04, P < .001), chronic obstructive pulmonary disease (AOR: 1.02, CI: 1.01-1.03, P = .002), and hypoalbuminemia (AOR: 1.02, CI: 1.00-1.03, P < .001), had higher odds of postoperative complications. Patients who had preoperative dyspnea (AOR: 1.02, CI: 1.01-1.03), hypertension (AOR: 1.01, CI: 1.01-1.03, P = .003), chronic corticosteroid use (AOR: 1.02, CI: 1.01-1.03, P < .001), bleeding disorder (AOR: 1.02; CI: 1.01-1.03, P < .001), and hypoalbuminemia (AOR: 1.01, CI: 1.00-1.02, P = .038), had higher odds of readmission. CONCLUSION: SDD is safe with certain comorbidities. Preoperative screening for cardiopulmonary comorbidities (eg, dyspnea, hypertension, and chronic obstructive pulmonary disease), chronic corticosteroid use, bleeding disorder, and hypoalbuminemia may improve SDD outcomes.

Associations of socioeconomic status with infectious diseases mediated by lifestyle, environmental pollution and chronic comorbidities: a comprehensive evaluation based on UK Biobank.

BACKGROUND: Socioeconomic status (SES) inequity was recognized as a driver of some certain infectious diseases. However, few studies evaluated the association between SES and the burden of overall infections, and even fewer identified preventable mediators. This study aimed to assess the association between SES and overall infectious diseases burden, and the potential roles of factors including lifestyle, environmental pollution, chronic disease history. METHODS: We included 401,009 participants from the UK Biobank (UKB) and defined the infection status for each participant according to their diagnosis records. Latent class analysis (LCA) was used to define SES for each participant. We further defined healthy lifestyle score, environment pollution score (EPS) and four types of chronic comorbidities. We used multivariate logistic regression to test the associations between the four above covariates and infectious diseases. Then, we performed the mediation and interaction analysis to explain the relationships between SES and other variables on infectious diseases. Finally, we employed seven types of sensitivity analyses, including considering the Townsend deprivation index as an area level SES variable, repeating our main analysis for some individual or composite factors and in some subgroups, as well as in an external data from the US National Health and Nutrition Examination Survey, to verify the main results. RESULTS: In UKB, 60,771 (15.2%) participants were diagnosed with infectious diseases during follow-up. Lower SES [odds ratio (OR) = 1.5570] were associated with higher risk of overall infections. Lifestyle score mediated 2.9% of effects from SES, which ranged from 2.9 to 4.0% in different infection subtypes, while cardiovascular disease (CVD) mediated a proportion of 6.2% with a range from 2.1 to 6.8%. In addition, SES showed significant negative interaction with lifestyle score (OR = 0.8650) and a history of cancer (OR = 0.9096), while a significant synergy interaction was observed between SES and EPS (OR = 1.0024). In subgroup analysis, we found that males and African (AFR) with lower SES showed much higher infection risk. Results from sensitivity and validation analyses showed relative consistent with the main analysis. CONCLUSIONS: Low SES is shown to be an important risk factor for infectious disease, part of which may be mediated by poor lifestyle and chronic comorbidities. Efforts to enhance health education and improve the quality of living environment may help reduce burden of infectious disease, especially for people with low SES.

T Cell Response to SARS-CoV-2 Coinfection and Comorbidities.

For the past three years, COVID-19 has become an increasing global health issue. Adaptive immune cells, especially T cells, have been extensively investigated in regard to SARS-CoV-2 infection. However, human health and T cell responses are also impacted by many other pathogens and chronic diseases. We have summarized T cell performance during SARS-CoV-2 coinfection with other viruses, bacteria, and parasites. Furthermore, we distinguished if those altered T cell statuses under coinfection would affect their clinical outcomes, such as symptom severity and hospitalization demand. T cell alteration in diabetes, asthma, and hypertension patients with SARS-CoV-2 infection was also investigated in our study. We have summarized whether changes in T cell response influence the clinical outcome during comorbidities.

Two-year follow-up of the COVID-19 pandemic in Mexico.

Background: After the initial outbreak in China (December 2019), the World Health Organization declared COVID-19 a pandemic on March 11th, 2020. This paper aims to describe the first 2 years of the pandemic in Mexico. Design and methods: This is a population-based longitudinal study. We analyzed data from the national COVID-19 registry to describe the evolution of the pandemic in terms of the number of confirmed cases, hospitalizations, deaths and reported symptoms in relation to health policies and circulating variants. We also carried out logistic regression to investigate the major risk factors for disease severity. Results: From March 2020 to March 2022, the coronavirus disease 2019 (COVID-19) pandemic in Mexico underwent four epidemic waves. Out of 5,702,143 confirmed cases, 680,063 were hospitalized (11.9%), and 324,436 (5.7%) died. Even if there was no difference in susceptibility by gender, males had a higher risk of death (CFP: 7.3 vs. 4.2%) and hospital admission risk (HP: 14.4 vs. 9.5%). Severity increased with age. With respect to younger ages (0-17 years), the 60+ years or older group reached adjusted odds ratios of 9.63 in the case of admission and 53.05 (95% CI: 27.94-118.62) in the case of death. The presence of any comorbidity more than doubled the odds ratio, with hypertension-diabetes as the riskiest combination. While the wave peaks increased over time, the odds ratios for developing severe disease (waves 2, 3, and 4 to wave 1) decreased to 0.15 (95% CI: 0.12-0.18) in the fourth wave. Conclusion: The health policy promoted by the Mexican government decreased hospitalizations and deaths, particularly among older adults with the highest risk of admission and death. Comorbidities augment the risk of developing severe illness, which is shown to rise by double in the Mexican population, particularly for those reported with hypertension-diabetes. Factors such as the decrease in the severity of the SARS-CoV2 variants, changes in symptomatology, and advances in the management of patients, vaccination, and treatments influenced the decrease in mortality and hospitalizations.

One-year mortality in COVID-19 is associated with patients' comorbidities rather than pneumonia severity.

BACKGROUND: In patients with pneumonia or acute respiratory distress syndrome who survived hospitalization, one-year mortality can affect up to one third of discharged patients. Therefore, significant long-term mortality after COVID-19 respiratory failure could be expected. The primary outcome of the present study was one-year all-cause mortality in hospitalized COVID-19 patients. METHODS: Observational study of COVID-19 patients hospitalized at Papa Giovanni XXIII Hospital (Bergamo, Italy), during the first pandemic wave. RESULTS: A total of 1326 COVID-19 patients were hospitalized. Overall one-year mortality was 33.6% (N 446/1326), with the majority of deaths occurring during hospitalization (N=412, 92.4%). Thirty-four patients amongst the 914 discharged (3.7%) subsequentely died within one year. A third of these patients died for advanced cancer, while death without a cause other than COVID-19 was uncommon (8.8% of the overall post-discharge mortality). In-hospital late mortality (i.e. after 28 days of admission) interested a population with a lower age, and fewer comorbidities, more frequentely admitted in ICU. Independent predictors of post-discharge mortality were age over 65 years (HR 3.19; 95% CI 1.28-7.96, p-value=0.013), presence of chronic obstructive pulmonary disease (COPD) (HR 2.52; 95% CI 1.09-5.83, p-value=0.031) or proxy of cardiovascular disease (HR 4.93; 95% CI 1.45-16.75, p-value=0.010), and presence of active cancer (HR 3.64; 95% CI 1.50-8.84, p-value=0.004), but not pneumonia severity. CONCLUSIONS: One-year post-discharge mortality depends on underlying patients' comorbidities rather than COVID-19 pneumonia severity per se. Awareness among physicians of predictors of post-discharge mortality might be helpful in structuring a follow-up program for discharged patients.

High anti-SARS-CoV-2 seroprevalence among unvaccinated mother-child pairs from a rural setting of north-eastern Tanzania during the second wave of COVID-19.

Background: The reported infection rates, and the burden of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in low- and middle-income countries, including sub-Saharan Africa, are relatively low compared to Europe and America, partly due to limited testing capabilities. Unlike many countries, in Tanzania, neither mass screening nor restrictive measures such as lockdowns have been implemented to date. The prevalence of SARS-CoV-2 infection in rural mainland Tanzania is largely unknown. Methods: Between April and October 2021, we conducted a cross-sectional study to assess anti-SARS-CoV-2 seroprevalence among mother-child pairs (n=634 children, n=518 mothers) in a rural setting of north-eastern Tanzania. Findings: We found a very high prevalence of anti-SARS-CoV-2 antibody titres with seroprevalence rates ranging from 29% among mothers and 40% among children, with a dynamic peak in seropositivity incidence at the end of July/early in August being revealed. Significant differences in age, socioeconomic status and body composition were associated with seropositivity in mothers and children. No significant associations were observed between seropositivity and comorbidities, including anaemia, diabetes, malaria, and HIV. Interpretations: The SARS-CoV-2 transmission in a rural region of Tanzania during 2021 was high, indicating a much higher infection rate in rural Tanzania compared to that reported in the UK and USA during the same period. Ongoing immune surveillance may be vital to monitoring the burden of viral infection in rural settings without access to molecular genotyping where a load of communicable diseases may mask COVID-19. Surveillance could be implemented in tandem with the intensification of vaccination strategies.

Clinical characteristics and risk factors for mortality in patients with COVID-19: A retrospective nationwide study in Malaysia

Background: Age and multiple comorbidities have been reported to influence the case fatality rate of COVID-19 worldwide, so also in Malaysia;however, to date, no scientific study among the local population has been published to confirm this. This study aimed to determine the overall demographics and clinical characteristics of COVID-19 non-survivors in Malaysia, stratified by age (< 65 vs. >= 65 years old). The mortality was also compared between two half-year periods: March-August 2020 and September 2020-March 2021. Method(s): Daily reports containing demographics and medical history of COVID-19 non-survivors from March 2020 to March 2021 were obtained from the Malaysian Ministry of Health website. All information was extracted retrospectively and analysed using descriptive and inferential statistics with SPSS. Result(s): Of 1192 COVID-19 non-survivors, the overall mean (SD) age was 64.8 (15.7) years, with 64.7% male. Death was seen mostly among 50- to 64-year-olds (33.1%) and 65- to 74-year-olds (24.8%). The presence of underlying hypertension (61.8%) and diabetes mellitus (48.2%) were the most common comorbid diseases encountered in the COVID-19 non-survivors. Underlying hypertension, stroke, heart disease and dyslipidaemia were significantly higher among COVID-19 non-survivors who were >= 65 years old compared to those < 65 (p < 0.05). Mortality was a lot higher in September 2020-March 2021 compared to March 2020-August 2020 (91.3% vs. 8.3%). Conclusion(s): Older age, male gender and the presence of multimorbidity (hypertension, diabetes mellitus, stroke and heart disease) are risk factors that contribute to mortality due to COVID-19 in Malaysia, especially among those >= 65 years old. Copyright © The Author(s) 2022.

Testosterone in males with COVID-19: a 12-month cohort study.

BACKGROUND: Male patients with COVID-19 have been found with reduced serum total testosterone (tT) levels and with more severe clinical outcomes. OBJECTIVES: To assess total testosterone (tT) levels and the probability of recovering eugonadal tT levels during a minimum 12-month timespan in a cohort of men who have been followed over time after the recovery from laboratory-confirmed COVID-19. MATERIALS AND METHODS: Demographic, clinical and hormonal values were collected for the overall cohort. Hypogonadism was defined as tT ≤9.2 nmol/l. The Charlson Comorbidity Index was used to score health-significant comorbidities. Descriptive statistics was used to compare hormonal levels at baseline versus 7-month (FU1) versus 12-month (FU2) follow-up, respectively. Multivariate cox proportional hazards regression model was used to identify the potential predictors of eugonadism recovery over time among patients with hypogonadism at the time of infection. RESULTS: Of the original cohort of 286 patients, follow-up data were available for 121 (42.3%) at FU1 and 63 (22%) patients at FU2, respectively. Higher median interquartile range (IQR) tT levels were detected at FU2 (13.8 (12.3-15.3) nmol/L) versus FU1 (10.2 [9.3-10.9] nmol/L) and versus baseline (3.6 [3.02-4.02] nmol/L) (all p < 0.0001), whilst both LH and E2 levels significantly decreased over the same time frame (all p ≤ 0.01). Circulating IL-6 levels further decreased at FU2 compared to FU1 levels (19.3 vs. 72.8 pg/ml) (p = 0.02). At multivariable cox regression analyses, baseline tT level (HR 1.19; p = 0.03 [1.02-1.4]) was independently associated with the probability of tT level normalization over time, after adjusting for potential confounders. CONCLUSIONS: Circulating tT levels keep increasing over time in men after COVID-19. Still, almost 30% of men who recovered from COVID-19 had low circulating T levels suggestive for a condition of hypogonadism at a minimum 12-month follow-up.

Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa.

The outbreak of coronavirus in the year 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prompted widespread illness, death, and extended economic devastation worldwide. In response, numerous countries, including Botswana and South Africa, instituted various clinical public health (CPH) strategies to mitigate and control the disease. However, the emergence of variants of concern (VOC), vaccine hesitancy, morbidity, inadequate and inequitable vaccine supply, and ineffective vaccine roll-out strategies caused continuous disruption of essential services. Based on Botswana and South Africa hospitalization and mortality data, we studied the impact of age and gender on disease severity. Comparative analysis was performed between the two countries to establish a vaccination strategy that could complement the existing CPH strategies. To optimize the vaccination roll-out strategy, artificial intelligence was used to identify the population groups in need of insufficient vaccines. We found that COVID-19 was associated with several comorbidities. However, hypertension and diabetes were more severe and common in both countries. The elderly population aged ≥60 years had 70% of major COVID-19 comorbidities; thus, they should be prioritized for vaccination. Moreover, we found that the Botswana and South Africa populations had similar COVID-19 mortality rates. Hence, our findings should be extended to the rest of Southern African countries since the population in this region have similar demographic and disease characteristics.

'COVID Is Coming, and I'm Bloody Scared': How Adults with Co-Morbidities' Threat Perceptions of COVID-19 Shape Their Vaccination Decisions.

Adults with comorbidities have faced a high risk from COVID-19 infection. However, Western Australia experienced relatively few infections and deaths from 2020 until early 2022 compared with other OECD countries, as hard border policies allowed for wide-scale vaccination before mass infections began. This research investigated the thoughts, feelings, risk perceptions, and practices of Western Australian adults with comorbidities aged 18-60 years in regard to COVID-19 disease and COVID-19 vaccines. We conducted 14 in-depth qualitative interviews between January and April 2022, just as the disease was starting to circulate. We coded results inductively and deductively, combining the Extended Parallel Process Model (EPPM) and vaccine belief models. Non-hesitant participants believed COVID-19 vaccines were safe and effective at mitigating COVID-19's threat and subsequently got vaccinated. Vaccine hesitant participants were less convinced the disease was severe or that they were susceptible to it; they also did not consider the vaccines to be sufficiently safe. Yet, for some hesitant participants, the exogenous force of mandates prompted vaccination. This work is important to understand how people's thoughts and feelings about their comorbidities and risks from COVID-19 influence vaccine uptake and how mandatory policies can affect uptake in this cohort.

Inpatient Mortality in People With Type 2 Diabetes: A Cross-sectional Study

Objective: This study aimed to estimate inpatient mortality rate for diabetes and identify its associated factors. Material(s) and Method(s): This is a cross-sectional study. The population was comprised between January 1 and December 31, 2019 in 32 public hospitals in Portugal, using summary hospital discharge data. We used both the Disease-Related Diagnosis Groups and the Disease Staging. Patients were grouped into survivors and non-survivors, and inpatient mortality was compared using competing event regression. Result(s): A total of 7980 patients were admitted with type 2 diabetes mellitus, there were 747 (10.3%) non-survivors. The advanced age (OR = 1.772;95% CI 1.625-1.932), the stage (3) severity of type 2 diabetes mellitus (OR = 4.301;95% CI 2.564-7.215), comorbid lung, bronchial or mediastinal malignant neoplasm (OR = 5.118;95% CI 2.222-11.788), comorbid bacterial pneumonia (OR = 3.214;95% CI 2.539-4.070), other respiratory system disorders (OR = 2.187;95%CI1.645-2.909),comorbidrhino-,adeno-andcorona-virus infections (OR = 1.680;95% CI 1.135-2.488) were determinants for inpatient mortality. Conclusion(s): Elderly patients with diabetes with micro- and macrovascular complications of the disease, who have bacterial pneumonia and who enter the emergency department are those who have a lower survival rate. Copyright © 2022 Via Medica. All rights reserved.

The Impact of Comorbidities and Obesity on the Severity and Outcome of COVID-19 in Hospitalized Patients-A Retrospective Study in a Hungarian Hospital.

Patients with comorbidities and obesity are more likely to be hospitalized with coronavirus disease 2019 (COVID-19), to have a higher incidence of severe pneumonia and to also show higher mortality rates. Between 15 March 2020 and 31 December 2021, a retrospective, single-center, observational study was conducted among patients requiring hospitalization for COVID-19 infection. Our aim was to investigate the impact of comorbidities and lifestyle risk factors on mortality, the need for intensive care unit (ICU) admission and the severity of the disease among these patients. Our results demonstrated that comorbidities and obesity increased the risk for all investigated endpoints. Age over 65 years and male sex were identified as independent risk factors, and cardiovascular diseases, cancer, endocrine and metabolic diseases, chronic kidney disease and obesity were identified as significant risk factors. Obesity was found to be the most significant risk factor, associated with considerable odds of COVID-19 mortality and the need for ICU admission in the under-65 age group (aOR: 2.95; p < 0.001 and aOR: 3.49, p < 0.001). In our study, risk factors that increased mortality and morbidity among hospitalized patients were identified. Detailed information on such factors may support therapeutic decision making, the proper targeting of vaccination campaigns and the effective overall management of the COVID-19 epidemic, hence reducing the burden on the healthcare system.

Developing a mortality risk prediction model using data of 3663 hospitalized COVID-19 patients: a retrospective cohort study in an Egyptian University Hospital.

PURPOSE: Since the declaration of COVID-19 as a pandemic, a wide between-country variation was observed regarding in-hospital mortality and its predictors. Given the scarcity of local research and the need to prioritize the provision of care, this study was conducted aiming to measure the incidence of in-hospital COVID-19 mortality and to develop a simple and clinically applicable model for its prediction. METHODS: COVID-19-confirmed patients admitted to the designated isolation areas of Ain-Shams University Hospitals (April 2020-February 2021) were included in this retrospective cohort study (n = 3663). Data were retrieved from patients' records. Kaplan-Meier survival and Cox proportional hazard regression were used. Binary logistic regression was used for creating mortality prediction models. RESULTS: Patients were 53.6% males, 4.6% current smokers, and their median age was 58 (IQR 41-68) years. Admission to intensive care units was 41.1% and mortality was 26.5% (972/3663, 95% CI 25.1-28.0%). Independent mortality predictors-with rapid mortality onset-were age ≥ 75 years, patients' admission in critical condition, and being symptomatic. Current smoking and presence of comorbidities particularly, obesity, malignancy, and chronic haematological disorders predicted mortality too. Some biomarkers were also recognized. Two prediction models exhibited the best performance: a basic model including age, presence/absence of comorbidities, and the severity level of the condition on admission (Area Under Receiver Operating Characteristic Curve (AUC) = 0.832, 95% CI 0.816-0.847) and another model with added International Normalized Ratio (INR) value (AUC = 0.842, 95% CI 0.812-0.873). CONCLUSION: Patients with the identified mortality risk factors are to be prioritized for preventive and rapid treatment measures. With the provided prediction models, clinicians can calculate mortality probability for their patients. Presenting multiple and very generic models can enable clinicians to choose the one containing the parameters available in their specific clinical setting, and also to test the applicability of such models in a non-COVID-19 respiratory infection.

Sex-differences in COVID-19 diagnosis, risk factors and disease comorbidities: A large US-based cohort study.

Introduction: Morbidity and mortality from COVID-19 are higher among men, however, underlying pathways remain controversial. We aim to investigate sex-gender differences in COVID-19 in a large US-based cohort, namely COVID-19 Research Database. More specifically, the objectives are to explore the socio-economic characteristics of COVID-19 male and female patients and to examine potential sex differences in lifestyle factors and disease comorbidities among diagnosed patients. Methods: This is a retrospective cohort study contrasting male vs. female patients with test-confirmed COVID-19. The study used Healthjump electronic medical records (e.g., demographics, encounters, medical history, and vitals) extracted from January 2020 to December 2021 (N = 62,310). Results: Significant sociodemographic and comorbidity differences were observed between males and females (p < 0.05). For example, a significantly higher proportion of males (vs. females) were aged ≥70-year-old (17.04 vs. 15.01%) and smokers (11.04 vs. 9.24%, p < 0.0001). In addition, multiple logistic regression showed that hypertension and diabetes were significantly more frequent in males [adjusted odds ratio (ORa) = 66.19 and ORa = 22.90]. Conclusions: Understanding the differences in outcomes between male and female patients will inform gender equity responsive approach to COVID-19 and enhance the effectiveness of clinical practice, health policy and interventions.