Predicting Mortality Due to SARS-CoV-2: A Mechanistic Score Relating Obesity and Diabetes to COVID-19 Outcomes in Mexico

Impact on Fatality Rates and Years of Life Lost During the COVID-19 Pandemic: The Experience of the Mexican Public Health Incident Management Command

BACKGROUND

The SARS-CoV-2 pandemic challenged health systems worldwide. In Mexico, the Public Health Incident Management Command (COISS) strategy was implemented to improve health care for patients with COVID-19 who required hospitalization.

AIM

To evaluate the impact of the COISS strategy on case fatality rates (CFR) and years of life lost (YLL) in hospitalized patients with COVID-19.

MATERIALS AND METHODS

The COISS strategy included eight actions implemented in states with high epidemic risk (COISS states). A secondary analysis of the public database from the Mexican Ministry of Health was performed considering patients with confirmed diagnoses of SARS-CoV-2 infection. The COISS strategy effectiveness was evaluated by its impact on in-hospital CFR and YLL at the beginning (T0) and end (T1) of the third wave, and at the end of the fourth wave (T2) and compared to states without intervention (non-COISS states).

RESULTS

At T0, COISS states showed a higher CFR for hospitalized patients than non-COISS states, which decreased after the strategy implementation. After correction for baseline conditions, lower relative CFR at T1 and T2, compared to T0, and a protective effect in different age groups, especially in those ≥65 years, were found in hospitalized patients in COISS states. The COISS strategy was associated with lower CFR in hospitalized patients with COVID-19 at both T1 and T2. At T0, YLLs were higher in COISS states, but there were no significant differences at T1 and T2.

CONCLUSIONS

COISS interventions effectively reduced CFR in hospitalized patients with COVID-19, providing protection to vulnerable patients and reducing the YLL gap.

Impact of comorbidities on COVID-19 mortality in hospitalized women: Insights from the metropolitan area of the Valley of Mexico from 2020 to 2022

Objectives

This research summarizes the impact of the major comorbidities impacting hospitalized women with COVID-19 and their relation to death.

Methods

Public data from national databases (2020-2022) for hospitalized women, including identification data, hospitalization time, comorbidities, and intensive care unit (ICU) admissions, were analyzed. Women were stratified by age (split at 50 years). Binary regression models determined the correlation between comorbidities and COVID-19 with mortality, expressed as odds ratios.

Results

A total of 46,492 women were hospitalized, with 70.1% aged above 50 years. A total of 17,728 fatalities occurred, with 86.5% in the older age group. A total of 5.82% women required intensive care. The common comorbidities were pneumonia, hypertension, diabetes, obesity, and intubation. A total of 56.6% died within the 1st week; in the ICU, 65.7% died by week 2. In the logistic regression, diabetes and chronic kidney disease (CKD) were initially significant, followed by pneumonia and CKD (days 8-14), intubation and, ICU stay (beyond the 15th day). In the ICU, intubation impact worsened over time.

Conclusions

Our study highlights the significant impact of comorbidities on COVID-19 mortality in women in the Valley of Mexico. Pneumonia, diabetes, CKD, and intubation were notably prevalent and correlated strongly with death in older women. Timely intubation improves survival, whereas delayed intubation increases mortality risk, particularly, in the ICU. Urgent targeted interventions are required, especially for older hospitalized women.

Metabolic health is more strongly associated with the severity and mortality of coronavirus disease 2019 than obesity

BACKGROUND

Obesity has been suggested to be associated with the coronavirus disease 2019 (COVID-19); however, it is unclear whether obesity or metabolic abnormalities accompanied by obesity have a stronger association with COVID-19 risk.

METHODS

This study used the Korea Disease Control and Prevention Agency database, which includes information about the COVID-19 diagnosis and mortality dates of the entire Korean population between October 2020 and December 2021 (for diagnosis) or March 2022 (for mortality). A total of 24,310,283 adults were included and classified into four metabolic obesity phenotypes: (1) metabolically healthy and normal weight (MHNW), (2) metabolically unhealthy and normal weight (MUNW), (3) metabolically healthy and obese (MHO), and (4) metabolically unhealthy and obese (MUO). COVID-19 mortality and severity were compared according to metabolic obesity phenotypes in the total population and in each age group (20-<50 years, 50-<70 years, and ≥ 70 years). Additionally, major adverse cardiovascular events (MACE) after COVID-19 infection were compared according to metabolic obesity phenotypes.

RESULTS

A total of 3, 956, 807 participants (16.3%) were diagnosed with COVID-19 during the study period. Among them, metabolically unhealthy subjects had higher mortality rates than metabolically healthy subjects (0.81% for MUNW, 0.40% for MUO, 0.23% for MHNW, and 0.19% for MHO). The rates of severe hospitalized disease were also higher in metabolically unhealthy subjects than in healthy subjects (0.59% for MUNW, 0.55% for MUO, 0.19% for MHNW, and 0.31% for MHO). In the subgroup analyses by age, similar trends were observed in subjects aged 20-50 and 50-70 years, respectively. Additionally, the incidence of total MACE was increased in metabolically unhealthy individuals.

CONCLUSIONS

The study shows that metabolic health is more strongly associated with COVID-19 mortality and severity than obesity, particularly in adults aged < 70 years.

Bariatric Metabolic Surgery Might be More of a Benefit than a Risk During a Pandemic Outbreak

Introduction: This report aimed to analyze the outcomes of patients with obesity who were on a bariatric program during the SARS-Cov-2 pandemic outbreak and compare those who received surgery with the ones who were not operated on. Methods: This was a retrospective study between 2020 and 2021. Patients were divided into two groups: those who underwent surgery (O) and those who were not operated (NO). The evolution of the risk factors identified for severe COVID infection and death was studied (ASMBS criteria). For this study, a follow-up period of 12 months was initiated. Results: In the O group, 83 patients were included and 99 were in the NO group. In the O group, patients with body mass index (BMI) > 35 Kg/m2 before surgery resolved the condition in 73.5% (61) cases, and this was done in the first 30 days by 38 (45.7%). Type 2 diabetes mellitus remission was documented in 18 patients (85.7%) of the O group, and the mean time elapsed for remission was 102.2 days (P < .01). Hypertension remitted in 66.7% (20) of the patients in group O in 82.4 days (P < .01). The subgroup of patients with obesity and one high-risk associated condition (30.2%, 25) resolved both in 44% (11) cases and one in 48% (12) cases. In the group of patients with obesity and two high-risk associated conditions (15.6%, 13), 47% (6) patients resolved the three conditions, 38% (5) resolved two conditions, and 15% (2) resolved one condition. Among the NO group, no comorbidity resolutions were recorded (P < .01). Admission because of COVID infection was necessary for 7.1% of NO and 1.2% of O (P = .04). Conclusion: Bariatric metabolic surgery would not increase the risk of COVID infection or of suffering serious complications resulting from it. Patients undergoing bariatric metabolic surgery rapidly resolved high-risk comorbidities and had less need for hospitalization because of SARS-CoV-2 infection.

Interplay between Comorbidities and Long COVID: Challenges and Multidisciplinary Approaches

Long COVID, a name often given to the persistent symptoms following acute SARS-CoV-2 infection, poses a multifaceted challenge for health. This review explores the intrinsic relationship between comorbidities and autoimmune responses in shaping the trajectory of long COVID. Autoantibodies have emerged as significant players in COVID-19 pathophysiology, with implications for disease severity and progression. Studies show immune dysregulation persisting months after infection, marked by activated innate immune cells and high cytokine levels. The presence of autoantibodies against various autoantigens suggests their potential as comorbid factors in long COVID. Additionally, the formation of immune complexes may lead to severe disease progression, highlighting the urgency for early detection and intervention. Furthermore, long COVID is highly linked to cardiovascular complications and neurological symptoms, posing challenges in diagnosis and management. Multidisciplinary approaches, including vaccination, tailored rehabilitation, and pharmacological interventions, are used for mitigating long COVID's burden. However, numerous challenges persist, from evolving diagnostic criteria to addressing the psychosocial impact and predicting disease outcomes. Leveraging AI-based applications holds promise in enhancing patient management and improving our understanding of long COVID. As research continues to unfold, unravelling the complexities of long COVID remains paramount for effective intervention and patient care.

Development and validation of a prediction model for mortality in critically ill COVID-19 patients

Background

Early prediction of prognosis may help early treatment measures to reduce mortality in critically ill coronavirus disease (COVID-19) patients. The study aimed to develop a mortality prediction model for critically ill COVID-19 patients.

Methods

This retrospective study analyzed the clinical data of critically ill COVID-19 patients in an intensive care unit between April and June 2022. Propensity matching scores were used to reduce the effect of confounding factors. A predictive model was built using logistic regression analysis and visualized using a nomogram. Calibration and receiver operating characteristic (ROC) curves were used to estimate the accuracy and predictive value of the model. Decision curve analysis (DCA) was used to examine the value of the model for clinical interventions.

Results

In total, 137 critically ill COVID-19 patients were enrolled; 84 survived, and 53 died. Univariate and multivariate logistic regression analyses revealed that aspartate aminotransferase (AST), creatinine, and myoglobin levels were independent prognostic factors. We constructed logistic regression prediction models using the seven least absolute shrinkage and selection operator regression-selected variables (hematocrit, red blood cell distribution width-standard deviation, procalcitonin, AST, creatinine, potassium, and myoglobin; Model 1) and three independent factor variables (Model 2). The calibration curves suggested that the actual predictions of the two models were similar to the ideal predictions. The ROC curve indicated that both models had good predictive power, and Model 1 had better predictive power than Model 2. The DCA results suggested that the model intervention was beneficial to patients and patients benefited more from Model 1 than from Model 2.

Conclusion

The predictive model constructed using characteristic variables screened using LASSO regression can accurately predict the prognosis of critically ill COVID-19 patients. This model can assist clinicians in implementing early interventions. External validation by prospective large-sample studies is required.

Serendipitous Adrenal Hyperplasia in Patients Admitted to the Emergency Department for Suspected SARS-CoV-2 Infection is Linked to Increased Mortality

BACKGROUND

Few data are available on adrenal morphology in patients with acute diseases, although it is known that endogenous glucocorticoids are essential for survival under stress conditions and that an adequate response is driven by activation of the hypothalamic-pituitary-adrenal (HPA) axis.

AIMS

The aim of this study was to assess adrenal morphology in patients with acute disease compared with patients with non-acute disease.

METHODS

This cross-sectional study included: 402 patients admitted to the emergency department (ED) for suspected SARS-CoV-2 infection (March-May, 2020) [main cohort]; 200 patients admitted to the ED for acute conditions (December 2018-February 2019) [control group A]; 200 outpatients who underwent radiological evaluation of non-acute conditions (January-February 2019) [control group B]. Chest and/or abdominal CT scans were reviewed to identify adrenal nodules or hyperplasia.

RESULTS

In the main cohort, altered adrenal morphology was found in 24.9% of the patients (15.4% adrenal hyperplasia; 9.5% adrenal nodules). The frequency of adrenal hyperplasia was higher both in the main cohort (15.4%) and control group A (15.5%) compared to control group B (8.5%; p = 0.02 and p = 0.03, respectively). In the main cohort, 14.9% patients died within 30 d. According to a multivariate analysis, adrenal hyperplasia was an independent risk factor for mortality (p = 0.04), as were older age (p <0.001) and active cancer (p = 0.01).

CONCLUSIONS

The notable frequency of adrenal hyperplasia in patients with acute diseases suggests an exaggerated activation of the HPA axis due to stressful conditions. The increased risk of short-term mortality found in patients with adrenal hyperplasia suggests that it may be a possible hallmark of worse prognosis.

Clinical outcomes of multidimensional association of type 2 diabetes mellitus, COVID-19 and sarcopenia: an algorithm and scoping systematic evaluation

BACKGROUND

The aim of this study was to provide a scoping and comprehensive review for the clinical outcomes from the cross-link of Type 2 diabetes mellitus (T2DM), COVID-19, and sarcopenia.

METHODS

By using PRISMA guidelines and searching through different databases that could provide findings of evidence on the association of T2DM, COVID-19, and sarcopenia.

RESULTS

Thirty-three studies reported a relationship between sarcopenia with T2DM, twenty-one studies reported the prognosis COVID-19 in patients with T2DM, ten studies reported the prognosis of COVID-19 in patients with sarcopenia, five studies discussed the outcomes of sarcopenia in patients with COVID-19, and one study reported sarcopenia outcomes in the presence of T2DM and COVID-19.

CONCLUSION

There is an obvious multidimensional relationship between T2DM, COVID-19 and sarcopenia which can cause prejudicial effects, poor prognosis, prolonged hospitalisation, lowered quality of life and a higher mortality rate during the current COVID-19 pandemic.

[Impact of the COVID-19 pandemic on cardiovascular disease mortality trends in Mexico, 2000-2022]

OBJECTIVE

To estimate the impact of the COVID-19 pandemic on cardiovascular disease (CVD) mortality trends in Mexico.

METHODS

An ecological study was conducted where deaths from CVD reported in Mexico under the ICD-10 classification with codes I10 to I99 for the period 2000-2022 were analyzed. Age-standardized mortality rates were calculated at the national and state levels, then the annual percentage variation was estimated using joinpoint analysis to know the changes in the mortality trend in the period studied.

RESULTS

There was an increase of 27.96 deaths per 100,000 inhabitants from 2000 to 2022 in Mexico. The joinpoint analysis shows in the period 2019-2021 an annual percentage change at the national level of 17,398 and subsequently a negative trend is presented between the years 2021-2022. The states of Guanajuato, Tlaxcala and Querétaro showed the largest increases in CVD mortality trends during the COVID-19 pandemic.

CONCLUSIONS

The trend in CVD mortality in Mexico increased significantly during the COVID-19 pandemic.

Obesity fosters severe disease outcomes in a mouse model of coronavirus infection associated with transcriptomic abnormalities

Obesity has been identified as an independent risk factor for severe outcomes in humans with coronavirus disease 2019 (COVID-19) and other infectious diseases. Here, we established a mouse model of COVID-19 using the murine betacoronavirus, mouse hepatitis virus 1 (MHV-1). C57BL/6 and C3H/HeJ mice exposed to MHV-1 developed mild and severe disease, respectively. Obese C57BL/6 mice developed clinical manifestations similar to those of lean controls. In contrast, all obese C3H/HeJ mice succumbed by 8 days postinfection, compared to a 50% mortality rate in lean controls. Notably, both lean and obese C3H/HeJ mice exposed to MHV-1 developed lung lesions consistent with severe human COVID-19, with marked evidence of diffuse alveolar damage (DAD). To identify early predictive biomarkers of worsened disease outcomes in obese C3H/HeJ mice, we sequenced RNA from whole blood 2 days postinfection and assessed changes in gene and pathway expression. Many pathways uniquely altered in obese C3H/HeJ mice postinfection aligned with those found in humans with severe COVID-19. Furthermore, we observed altered gene expression related to the unfolded protein response and lipid metabolism in infected obese mice compared to their lean counterparts, suggesting a role in the severity of disease outcomes. This study presents a novel model for studying COVID-19 and elucidating the mechanisms underlying severe disease outcomes in obese and other hosts.

A Critical Review on the Long-Term COVID-19 Impacts on Patients With Diabetes

BACKGROUND

The world is currently grappling with the potentially life-threatening coronavirus disease 2019 (COVID-19), marking it as the most severe health crisis in the modern era. COVID-19 has led to a pandemic, with the World Health Organization (WHO) predicting that individuals with diabetes are at a higher risk of contracting the virus compared to the general population. This review aims to provide a practical summary of the long-term impacts of COVID-19 on patients with diabetes. Specifically, it focuses on the effects of SARS-CoV-2 on different types of diabetic patients, the associated mortality rate, the underlying mechanisms, related complications, and the role of vitamin D and zinc in therapeutic and preventive approaches.

METHODS

Relevant literature was identified through searches on PubMed, Web of Science, and Science Direct in English, up to April 2023.

RESULTS

COVID-19 can lead to distressing symptoms and pose a significant challenge for individuals living with diabetes. Older individuals and those with pre-existing conditions such as diabetes, coronary illness, and asthma are more susceptible to COVID-19 infection. Managing COVID-19 in individuals with diabetes presents challenges, as it not only complicates the fight against the infection but also potentially prolongs the recovery time. Moreover, the virus may thrive in individuals with high blood glucose levels. Various therapeutic approaches, including antidiabetic drugs, are available to help prevent COVID-19 in diabetic patients.

CONCLUSIONS

Diabetes increases the morbidity and mortality risk for patients with COVID-19. Efforts are globally underway to explore therapeutic interventions aimed at reducing the impact of diabetes on COVID-19.

Physical activity patterns among obese adults attending rural primary health care units, Ismailia Governorate, Egypt: A case-control study

Obesity is an ignored health problem in all countries; there are a lot of health problems related directly or indirectly to overweight and obesity. The incidence of COVID-19 with social isolation and technological development in recent years strongly contributed to a progressive increase in obesity. . Assess the pattern of the 3 divisions of physical activity and sedentary behaviors in obese patients. Physical inactivity is a significant concern, especially among individuals with obesity and certain demographic characteristics. Addressing these factors and promoting physical activity interventions tailored to specific populations is essential in combating sedentary behavior and its associated health implications.This case-control study included 350 adult obese patients (BMI ≥ 30) and 75 people with normal BMI (18.5-24.9). Their sociodemographic data were analyzed and their pattern of physical activity related to work, movement to and from places for 10 minutes, and pattern of recreational activity were assessed, in addition to the assessment of the sedentary behaviors. The mean age of the study group was 34 years, the majority were females, educated, and working. Forty five percent of the total sample were physically inactive; the pattern of activity during travel to and from places (10 min) was lower in obese patients. Recreational activities were low in the studied population, in the present study the time spent sitting or reclining (except sleeping) was significantly higher among obese participants than controls (P ≤ .001). Obesity, urban residence, unemployment and illiteracy were independent risk factors for physical inactivity.

Sex differences in systemic inflammation and immune function in diet-induced obesity rodent models: A systematic review

Understanding sex differences in immunological responses in the context of obesity is important to improve health outcomes. This systematic review aimed to investigate sex differences in systemic inflammation, immune cell phenotype, and function in diet-induced obesity (DIO) animal models. A systematic search in Medline, Embase, and CINAHL from inception to April 2023 was conducted, using a combination of the following concepts: sex, obesity, cytokines, and immune cell phenotypes/function. Forty-one publications reporting on systemic inflammation (61%), cell phenotype (44%), and/or function (7%) were included. Females had lower systemic inflammation compared with males in response to DIO intervention and a higher proportion of macrophage (M)2-like cells compared with males that had a higher proportion of M1-like in adipose tissue. Although there were no clear sex differences in immune function, high-fat DIO intervention remains an important factor in the development of immune dysfunction in both males and females, including disturbances in cytokine production, proliferation, and migration of immune cells. Yet, the mechanistic links between diet and obesity on such immune dysfunction remain unclear. Future studies should investigate the role of diet and obesity in the functionality of immune cells and employ adequate methods for a high-quality investigation of sex differences in this context.

Association of obesity on the outcome of critically ill patients affected by COVID-19

OBJECTIVE

To evaluate the impact of obesity on ICU mortality.

DESIGN

Observational, retrospective, multicentre study.

SETTING

Intensive Care Unit (ICU).

PATIENTS

Adults patients admitted with COVID-19 and respiratory failure.

INTERVENTIONS

None.

PRIMARY VARIABLES OF INTEREST

Collected data included demographic and clinical characteristics, comorbidities, laboratory tests and ICU outcomes. Body mass index (BMI) impact on ICU mortality was studied as (1) a continuous variable, (2) a categorical variable obesity/non-obesity, and (3) as categories defined a priori: underweight, normal, overweight, obesity and Class III obesity. The impact of obesity on mortality was assessed by multiple logistic regression and Smooth Restricted cubic (SRC) splines for Cox hazard regression.

RESULTS

5,206 patients were included, 20 patients (0.4%) as underweight, 887(17.0%) as normal, 2390(46%) as overweight, 1672(32.1) as obese and 237(4.5%) as class III obesity. The obesity group patients (n = 1909) were younger (61 vs. 65 years, p < 0.001) and with lower severity scores APACHE II (13 [9-17] vs. 13[10-17, p < 0.01) than non-obese. Overall ICU mortality was 28.5% and not different for obese (28.9%) or non-obese (28.3%, p = 0.65). Only Class III obesity (OR = 2.19, 95%CI 1.44-3.34) was associated with ICU mortality in the multivariate and SRC analysis.

CONCLUSIONS

COVID-19 patients with a BMI > 40 are at high risk of poor outcomes in the ICU. An effective vaccination schedule and prolonged social distancing should be recommended.

It is not just about prescription. A cohort study of the impact of enteral nutrition on mortality of hospitalized patients with COVID-19

Introduction

Introduction: during COVID-19 pandemic, international societies released guidelines and recommendations for patients requiring nutritional support according to previous similar respiratory diseases. Objectives: the aim of the study was to evaluate the nutritional support provided by enteral nutrition (EN) in patients with COVID-19 infection, identify if the recommendations from international societies were met and their impact on mortality rate. Methods: a cohort study was conducted on adult patients with COVID-19 admitted to a tertiary hospital. Demographic, clinical, biochemical, and nutritional variables were obtained. A random-effect parametric survival-time model was performed to quantify the risk of death for each variable, and the Hausman test was used to confirm the model. Results: two hundred and twenty-nine patients were enrolled. The delivered energy was > 80 % of adequacy in the first two days, as suggested by international guidelines (11.7 ± 4.9 kcal/kg); however, an adequacy rate less than 60 % was achieved on day 14 (25.4 ± 7.4 kcal/kg). The protein adequacy was > 75 % on the first days of infusion (1.3 ± 0.3 g/kg); however, the infusion was < 50 % (1.5 ± 0.4 g/kg) after being extubated. Age, sex, and nutritional risk were related to higher mortality in patients with EN, whereas the infused energy and protein, the percentage of protein adequacy, arginine, and n-3 PUFA were associated with lower mortality. Conclusion: achieving at least 80 % of the energy and protein requirements, as well as n-3 PUFA and arginine supplementation could be associated with lower mortality in COVID-19 patients. More studies are needed to confirm the role of these nutrients on the mortality rate.

Prevalence and determinants of post-acute sequelae after SARS-CoV-2 infection (Long COVID) among adults in Mexico during 2022: a retrospective analysis of nationally representative data

Background

Post-acute sequelae after SARS-CoV-2 infection (PASC) remains a concerning long-term complication of COVID-19. Here, we aimed to characterize the epidemiology of PASC in Mexico during 2022 and identify potential associations of covariates with PASC prevalence using nationally representative data.

Methods

We analyzed data from the 2022 Mexican National Health and Nutrition Survey (ENSANUT) from 24,434 participants, representing 85,521,661 adults ≥20 years. PASC was defined using both the National Institute for Health and Care Excellence (NICE) definition and a PASC score ≥12. Estimates of PASC prevalence were stratified by age, sex, rural vs. urban setting, social lag quartiles, number of reinfections, vaccination status and periods of predominance of SARS-CoV-2 circulating variants. Determinants of PASC were assessed using log-binomial regression models adjusted by survey weights.

Findings

Persistent symptoms after SARS-CoV-2 infection were reported by 12.44% (95% CI 11.89-12.99) of adults ≥20 years in Mexico in 2022. The most common persistent symptoms were fatigue, musculoskeletal pain, headache, cough, loss of smell or taste, fever, post-exertional malaise, brain fog, anxiety, and chest pain. PASC was present in 21.21% (95% CI 19.74-22.68) of subjects with previously diagnosed COVID-19. Over 28.6% of patients with PASC reported symptoms persistence ≥6 months and 14.05% reported incapacitating symptoms. Higher PASC prevalence was associated with SARS-CoV-2 reinfections, depressive symptoms and living in states with high social lag. PASC prevalence, particularly its more severe forms, decreased with COVID-19 vaccination and for infections during periods of Omicron variant predominance.

Interpretation

PASC remains a significant public health burden in Mexico as the COVID-19 pandemic transitions into endemic. Promoting SARS-CoV-2 reinfection prevention and booster vaccination may be useful in reducing PASC burden.

Funding

This research was supported by Instituto Nacional de Geriatría in Mexico.

The impact of body mass index on long-term survival after ICU admission due to COVID-19: A retrospective multicentre study

Objective

The impact of obesity on long-term survival after intensive care unit (ICU) admission with severe coronavirus disease 2019 (COVID-19) is unclear. We aimed to quantify the impact of obesity on time to death up to two years in patients admitted to Australian and New Zealand ICUs.

Design

Retrospective multicentre study.

Setting

92 ICUs between 1st January 2020 through to 31st December 2020 in New Zealand and 31st March 2022 in Australia with COVID-19, reported in the Australian and New Zealand Intensive Care Society adult patient database.

Participants

All patients with documented height and weight to estimate the body mass index (BMI) were included. Obesity was classified patients according to the World Health Organization recommendations.

Interventions and main outcome measures

The primary outcome was survival time up to two years after ICU admission. The effect of obesity on time to death was assessed using a Cox proportional hazards model. Confounders were acute illness severity, sex, frailty, hospital type and jurisdiction for all patients.

Results

We examined 2,931 patients; the median BMI was 30.2 (IQR 25.6-36.0) kg/m2. Patients with a BMI ≥30 kg/m2 were younger (median [IQR] age 57.7 [46.2-69.0] vs. 63.0 [50.0-73.6]; p < 0.001) than those with a BMI <30 kg/m2. Most patients (76.6%; 2,244/2,931) were discharged alive after ICU admission. The mortality at two years was highest for BMI categories <18.5 kg/m2 (35.4%) and 18.5-24.9 kg/m2 (31.1%), while lowest for BMI ≥40 kg/m2 (14.5%). After adjusting for confounders and with BMI 18.5-24.9 kg/m2 category as a reference, only the BMI ≥40 kg/m2 category patients had improved survival up to 2 years (hazard ratio = 0.51; 95%CI: 0.34-0.76).

Conclusions

The obesity paradox appears to exist beyond hospital discharge in critically ill patients with COVID-19 admitted in Australian and New Zealand ICUs. A BMI ≥40 kg/m2 was associated with a higher survival time of up to two years.

Association between nirmatrelvir plus ritonavir and the outcomes of non-hospitalized obese patients with COVID-19

OBJECTIVE

To investigate the association between nirmatrelvir plus ritonavir (NMV-r) and the outcomes of non-hospitalized obese patients with coronavirus disease 2019 (COVID-19).

METHODS

This retrospective cohort study used the TriNetX research network to identify non-hospitalized obese adult patients with COVID-19 between 1 January 2022 and 30 June 2023. Propensity score matching was used to match patients receiving NMV-r (NMV-r group) with those not receiving NMV-r (control group). The primary outcome was the compositive outcome of all-cause emergency department (ED) visits, hospitalization or death during the 30-day follow-up period.

RESULTS

Using propensity score matching methods, two cohorts of 30,969 patients each with balanced baseline characteristics were identified. During the follow-up period, the NMV-r group had a lower risk of all-cause ED visits, hospitalization or death [4.80% (n=1489) vs 5.50% (n=1705); hazard ratio (HR) 0.900, 95% confidence interval (CI) 0.839-0.965]. Compared with the control group, the NMV-r group had a lower risk of all-cause ED visits (HR 0.812, 95% CI 0.740-0.891) and all-cause mortality (HR 0.089, 95% CI 0.027-0.288). The lower risk in the NMV-r group compared with the control group was observed consistently in most subgroup analyses according to body mass index (30.0-34.9 kg/m2: HR 0.68, 95% CI 0.55-0.82; 35.0-39.9 kg/m2: HR 0.67, 95% CI 0.52-0.87), age (4-64 years: HR 0.83, 95% CI 0.75-0.92; ≥65 years: HR 0.88, 95% CI 0.79-0.98), sex (men: HR 0.69, 95% CI 0.60-0.79; women: HR 0.69, 95% CI 0.63-0.76) and vaccination status (unvaccinated: HR 0.75, 95% CI 0.70-0.81).

CONCLUSION

NMV-r is associated with reduced risk of all-cause ED visits, hospitalization and death for non-hospitalized obese patients with COVID-19. Accordingly, these findings support the use of NMV-r in obese patients.

Obesity as a Neuroendocrine Disorder

Obesity is one of the most prevalent diseases in the world. Based on hundreds of clinical and basic investigations, its etiopathogenesis goes beyond the simple imbalance between energy intake and expenditure. The center of the regulation of appetite and satiety lies in the nuclei of the hypothalamus where peripheral signals derived from adipose tissue (e.g., leptin), the gastrointestinal tract, the pancreas, and other brain structures, arrive. These signals are part of the homeostatic control system (eating to survive). Additionally, a hedonic or reward system (eating for pleasure) is integrated into the regulation of appetite. This reward system consists of a dopaminergic circuit that affects eating-related behaviors influencing food preferences, food desires, gratification when eating, and impulse control to avoid compulsions. These systems are not separate. Indeed, many of the hormones that participate in the homeostatic system also participate in the regulation of the hedonic system. In addition, factors such as genetic and epigenetic changes, certain environmental and sociocultural elements, the microbiota, and neuronal proinflammatory effects of high-energy diets also contribute to the development of obesity. Therefore, obesity can be considered a complex neuroendocrine disease, and all of the aforementioned components should be considered for the management of obesity.

Frequency of dysnatremia in patients admitted with COVID-19 infection and its prognostic implication

OBJECTIVE

We aimed to investigate the frequency of dysnatremia among patients admitted with COVID-19 infection and its association with inpatient mortality.

METHODS

This retrospective longitudinal study was conducted for 12 weeks. Serum sodium levels were recorded at admission, during the hospital stay, and within 48 hours of discharge or death. Logistic regression was used to determine the predictors of mortality.

RESULTS

This study included 574 patients (69.7% men, age 55.6 ± 14.4 years). On admission, mean sodium was 135.9 ± 6.4 mEq/L; 39% had hyponatremia and 4.7% had hypernatremia. During admission, hypernatremia increased to 18.8%; maximum sodium in patients who survived was 140.6 ± 5.0 mEq/L versus 151.0 ± 9.9 mEq/L in those who died. The final sodium was 145.4 ± 9.4 mEq/L in patients who died versus 137.7 ± 3.7 mEq/L in those who survived (odds ratio [OR]: 1.22, 95% confidence interval [CI]: 1.13-1.32). Other predictors of mortality included ischemic heart disease (OR: 3.65, 95% CI: 1.39-9.61), acute kidney injury (OR: 6.07, 95% CI: 2.39-15.42), invasive ventilation (OR: 28.4, 95% CI: 11.14-72.40), and length of stay (OR: 0.91, 95% CI: 0.86-0.97).

CONCLUSION

Hypernatremia was frequently observed in patients who were critically ill and died and may be considered a predictor of mortality in COVID-19 infection.

Moderate physical activity is associated with lower depression, anxiety and stress in health-care workers during the COVID-19 pandemic

OBJECTIVE

Health-care workers are in high risk for COVID-19 and may experience associated mental health disturbances. Although physical activity (PA) has positive effects on mental disturbances, it has not been fully investigated in health-team during COVID-19 pandemic. Therefore, we analyzed depression, anxiety and stress in health-care workers, and their relationship with PA before and during a COVID-19 peak.

METHODS

Retrospective cohort study. PA (IPAQ short-form) evaluated and associated with depression, anxiety and stress (DAAS-21) at the beginning of COVID-19 first wave in Mexico (April 2020) in 1146 workers of a tertiary-care hospital, and in a subsequent occasion at the first wave peak (July-August/2020) in 311 workers (from the first ones). Data collected from routine surveillance.

RESULTS

Depression increased 9%, anxiety 15%, and stress 10% at the pandemic peak. Subjects with higher frequency of baseline moderate PA showed lower severity of depression, anxiety and stress at the peak (p < 0.05). At the pandemic peak, female sex (OR = 2.42, 95%CI 1.14-5.13), diabetes (OR = 21.9, 95%CI 2.09-221) and baseline depression (OR = 8.86, 95%CI 4.30-18.2) predicted depression; baseline anxiety (OR = 5.52, 95%CI 3.01-10.1), working in COVID-19 area (OR = 4.14, 95%CI 1.99-8.64), and baseline moderate PA (OR = 0.35, 95%CI 0.16-0.73) predicted anxiety; and baseline stress (OR = 8.64, 95%CI 4.11-18.2), and moderate PA (OR = 0.35, 95%CI 0.15-0.82) predicted stress.

CONCLUSION

Depression, stress, and particularly anxiety, increased in health-care workers from the beginning to the COVID-19 pandemic peak, and were predicted by the presence of the corresponding baseline mental alterations, and in the case of anxiety and stress, by the lower frequency of moderate PA.

Prevalence of overweight and obesity and their effect on COVID-19 severity and hospitalization among younger than 50 years versus older than 50 years population: A systematic review and meta-analysis

Cohort studies have shown that both overweight and obesity have their impact by increasing hospitalization with COVID-19. We conducted a systematic literature search in PubMed, Google Scholar, and MedRxiv databases following the PRISMA guidelines. Statistical analyses were performed using STATA software version 16 MP (Stata Corp, College Station, TX, USA) and Med Calc software version 22.009(Med Calc software Ltd, Ostend, Belgium). The primary outcome was to measure the prevalence of overweight and obesity and their impact on the risk of hospitalization among COVID-19 patients under and above 50 years of age. In total, 184 studies involving 2,365,377 patients were included. The prevalence of overweight was highest among those younger than 50 years of age over those older than 50 years of age, (26.33% vs. 30.46%), but there was no difference in obesity (36.30% vs. 36.02%). Overall, the pooled prevalence of overweight and obesity among hospitalized COVID-19 patients was 31.0% and 36.26%, respectively. Compared with normal weight, the odds of hospitalization with overweight (odds ratio [OR] 2.186, 95% confidence interval [CI] [1.19, 3.99], p < 0.01) and obesity (OR 3.069, 95% CI [1.67, 5.61], p < 0.001) in those younger than 50 years and obesity (OR 3.977, 95% CI [2.75, 5.73], p < 0.001) in the older than 50 years age group were significantly high. The increased prevalence of overweight and obesity among the under 50 years age group and obesity among the older than 50 years age group significantly increased the rate of COVID-19 infections, severity and hospitalization.

Characteristics of COVID-19 and mortality-associated factors during the first year of the pandemic in southeast Mexico

Aim: The present study was designed to evaluate the clinical characteristics of COVID-19 and mortality-associated factors during the first year of the pandemic in patients from southeastern Mexico. Patient & methods: A total of 953 records from patients with COVID-19 were cross-sectionally studied in a primary care hospital in southeast Mexico between 2020 and 2021. Results: The prevalent symptoms were fever (78.6%), cough (80.5%) and headache (82.8%) and dyspnea reached 13.5%. The mortality rate was 7.63% and the clinical variables associated with it were age >60 years, hypertension, severe disease, radiographic pneumonia, days to diagnosis and having two Mayan surnames. Conclusion: Future health strategies should consider age, comorbidities, disease severity, clinical manifestations and possessing ethnicity of risk (i.e., Mayan genetic background).

The Effect of Comorbidities and Complications on COVID-19 Mortality: A Detailed Retrospective Study in Western Romania

COVID-19 continues to impact global health systems even after being declared over, with some patients exhibiting severe complications linked to pre-existing conditions. This study aimed to investigate the association between comorbidities, complications, and survival outcomes among COVID-19 survivors in Western Romania. Our hypothesis posited that comorbidities and complications significantly influence survival rates. We conducted a retrospective analysis of 1948 COVID-19 survivors admitted from January to December 2021, with 192 selected for detailed analysis based on inclusion and exclusion criteria. The severity of COVID-19 was classified according to WHO guidelines, and conditions like hypertension and obesity were defined using criteria from the European Society of Hypertension (ESH), the European Society of Cardiology (ESC), and WHO, respectively. Among the 192 patients, 33 had mild, 62 had moderate, and 97 had severe COVID-19. The median age across the severity groups was 63.2 years. Patients undergoing tracheostomy had a mortality rate of 83.3% versus 22.2% for non-tracheostomy patients (p < 0.001) and presented with significantly higher lung injury, hospitalization duration, and complications. Remarkably, tracheostomized patients were 17.50 times more likely to succumb to the disease (95% CI 4.39-116.91, p < 0.001). Furthermore, pneumothorax increased the mortality risk significantly (OR 22.11, 95% CI 5.72-146.03, p < 0.001). Intriguingly, certain conditions like grade I hypertension and grade II obesity showed a protective effect against mortality, whereas type 2 diabetes mellitus increased mortality risk (univariate OR 2.89, p = 0.001). The presence of certain comorbidities and complications significantly impacts the survival rates of COVID-19 patients in Western Romania. Notably, tracheostomy, pneumothorax, and T2DM were associated with increased mortality. This study underscores the importance of personalized patient care and provides insights for healthcare policymakers in Western Romania to improve clinical management strategies.

Exploring disparities and novel insights into metabolic and cardiovascular comorbidities among COVID-19 patients in Mexico

Introduction

The COVID-19 pandemic, especially its early stages, sparked extensive discussions regarding the potential impact of metabolic and cardiovascular comorbidities on the severity and fatality of SARS-CoV-2 infection, yielding inconclusive outcomes. In this study, we delve into the prevalence of metabolic and cardiovascular comorbidities within COVID-19 patients in Mexico.

Methods

Employing a retrospective observational study design, we collected data from official databases encompassing COVID-19 patients admitted to both public and private hospitals in Mexico City.

Results

Our investigation unveiled a noteworthy incongruity in the prevalence of metabolic and cardiovascular comorbidities among COVID-19 patients, with a particular emphasis on obesity, hypertension, and diabetes. This incongruity manifests as location-dependent phenomena, where the prevalence of these comorbidities among COVID-19 patients significantly deviates from the reported values for the general population in each specific location.

Discussion

These findings underscore the critical importance of screening for metabolic and cardiovascular comorbidities in COVID-19 patients and advocate for the necessity of tailored interventions for this specific population. Furthermore, our study offers insights into the intricate interplay between COVID-19 and metabolic and cardiovascular comorbidities, serving as a valuable foundation for future research endeavors and informing clinical practice.

Validation of a risk prediction model for COVID-19: the PERIL prospective cohort study

Aim: This study aims to perform an external validation of a recently developed prognostic model for early prediction of the risk of progression to severe COVID-19. Patients & methods/materials: Patients were recruited at their initial diagnosis at two facilities within Hamad Medical Corporation in Qatar. 356 adults were included for analysis. Predictors for progression of COVID-19 were all measured at disease onset and first contact with the health system. Results: The C statistic was 83% (95% CI: 78%-87%) and the calibration plot showed that the model was well-calibrated. Conclusion: The published prognostic model for the progression of COVID-19 infection showed satisfactory discrimination and calibration and the model is easy to apply in clinical practice.d.

Prediction of prognosis in COVID-19 patients using machine learning: A systematic review and meta-analysis

BACKGROUND

Accurate prediction of prognostic outcomes in patients with COVID-19 could facilitate clinical decision-making and medical resource allocation. However, little is known about the ability of machine learning (ML) to predict prognosis in COVID-19 patients.

OBJECTIVE

This study aimed to systematically examine the prognostic value of ML in patients with COVID-19.

METHODS

A systematic search was conducted in PubMed, Web of Science, Embase, Cochrane Library, and IEEE Xplore up to December 15, 2021. Studies predicting the prognostic outcomes of COVID-19 patients using ML were eligible for inclusion. Risk of bias was evaluated by a tailored checklist based on Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Pooled sensitivity, specificity, and area under the receiver operating curve (AUC) were calculated to evaluate model performance.

RESULTS

A total of 33 studies that described 35 models were eligible for inclusion, with 27 models presenting mortality, four intensive care unit (ICU) admission, and four use of ventilation. For predicting mortality, ML gave a pooled sensitivity of 0.86 (95% CI, 0.79-0.90), a specificity of 0.87 (95% CI, 0.80-0.92), and an AUC of 0.93 (95% CI, 0.90-0.95). For the prediction of ICU admission, ML had a sensitivity of 0.86 (95% CI, 0.78-0.92), a specificity of 0.81 (95% CI, 0.66-0.91), and an AUC of 0.91 (95% CI, 0.88-0.93). For the prediction of ventilation, ML had a sensitivity of 0.81 (95% CI, 0.68-0.90), a specificity of 0.78 (95% CI, 0.66-0.87), and an AUC of 0.87 (95% CI, 0.83-0.89). Meta-regression analyses indicated that algorithm, population, study design, and source of dataset influenced the pooled estimate.

CONCLUSION

This meta-analysis demonstrated the satisfactory performance of ML in predicting prognostic outcomes in patients with COVID-19, suggesting the potential value of ML to support clinical decision-making. However, improvements to methodology and validation are still necessary before its application in routine clinical practice.

Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19

BACKGROUND

During the fifth wave of the coronavirus disease 2019 (COVID-19) pandemic in Japan, which took place between June and September 2021, a significant number of COVID-19 cases with deterioration occurred in unvaccinated individuals < 65 years old. However, the risk factors for COVID-19 deterioration in this specific population have not yet been determined. This study developed a prediction method to identify COVID-19 patients < 65 years old who are at a high risk of deterioration.

METHODS

This retrospective study analyzed data from 1,675 patients < 65 years old who were admitted to acute care institutions in Fukushima with mild-to-moderate-1 COVID-19 based on the Japanese disease severity criteria prior to the fifth wave. For validation, 324 similar patients were enrolled from 3 hospitals in Yamagata. Logistic regression analyses using cluster-robust variance estimation were used to determine predictors of disease deterioration, followed by creation of risk prediction scores. Disease deterioration was defined as the initiation of medication for COVID-19, oxygen inhalation, or mechanical ventilation starting one day or later after admission.

RESULTS

The patients whose condition deteriorated (8.6%) tended to be older, male, have histories of smoking, and have high body temperatures, low oxygen saturation values, and comorbidities, such as diabetes/obesity and hypertension. Stepwise variable selection using logistic regression to predict COVID-19 deterioration retained comorbidities of diabetes/obesity (DO), age (A), body temperature (T), and oxygen saturation (S). Two predictive scores were created based on the optimism-corrected regression coefficients: the DOATS score, including all of the above risk factors, and the DOAT score, which was the DOATS score without oxygen saturation. In the original cohort, the areas under the receiver operating characteristic curve (AUROCs) of the DOATS and DOAT scores were 0.81 (95% confidence interval [CI] 0.77-0.85) and 0.80 (95% CI 0.76-0.84), respectively. In the validation cohort, the AUROCs for each score were both 0.76 (95% CI 0.69-0.83), and the calibration slopes were both 0.80. A decision curve analysis confirmed the clinical practicability of both scores in the validation cohort.

CONCLUSIONS

We established two prediction scores that can quickly evaluate the risk of COVID-19 deterioration in mild/moderate patients < 65 years old.

Risk phenotypes of diabetes and association with COVID-19 severity and death: an update of a living systematic review and meta-analysis

AIMS/HYPOTHESIS

To provide a systematic overview of the current body of evidence on high-risk phenotypes of diabetes associated with COVID-19 severity and death.

METHODS

This is the first update of our recently published living systematic review and meta-analysis. Observational studies investigating phenotypes in individuals with diabetes and confirmed SARS-CoV-2 infection with regard to COVID-19-related death and severity were included. The literature search was conducted from inception up to 14 February 2022 in PubMed, Epistemonikos, Web of Science and the COVID-19 Research Database and updated using PubMed alert to 1 December 2022. A random-effects meta-analysis was used to calculate summary relative risks (SRRs) with 95% CIs. The risk of bias was evaluated using the Quality in Prognosis Studies (QUIPS) tool and the certainty of evidence using the GRADE approach.

RESULTS

A total of 169 articles (147 new studies) based on approximately 900,000 individuals were included. We conducted 177 meta-analyses (83 on COVID-19-related death and 94 on COVID-19 severity). Certainty of evidence was strengthened for associations between male sex, older age, blood glucose level at admission, chronic insulin use, chronic metformin use (inversely) and pre-existing comorbidities (CVD, chronic kidney disease, chronic obstructive pulmonary disease) and COVID-19-related death. New evidence with moderate to high certainty emerged for the association between obesity (SRR [95% CI] 1.18 [1.04, 1.34], n=21 studies), HbA1c (53-75 mmol/mol [7-9%]: 1.18 [1.06, 1.32], n=8), chronic glucagon-like peptide-1 receptor agonist use (0.83 [0.71, 0.97], n=9), pre-existing heart failure (1.33 [1.21, 1.47], n=14), pre-existing liver disease (1.40 [1.17, 1.67], n=6), the Charlson index (per 1 unit increase: 1.33 [1.13, 1.57], n=2), high levels of C-reactive protein (per 5 mg/l increase: 1.07 [1.02, 1.12], n=10), aspartate aminotransferase level (per 5 U/l increase: 1.28 [1.06, 1.54], n=5), eGFR (per 10 ml/min per 1.73 m2 increase: 0.80 [0.71, 0.90], n=6), lactate dehydrogenase level (per 10 U/l increase: 1.03 [1.01, 1.04], n=7) and lymphocyte count (per 1×109/l increase: 0.59 [0.40, 0.86], n=6) and COVID-19-related death. Similar associations were observed between risk phenotypes of diabetes and severity of COVID-19, with some new evidence on existing COVID-19  vaccination status (0.32 [0.26, 0.38], n=3), pre-existing hypertension (1.23 [1.14, 1.33], n=49), neuropathy and cancer, and high IL-6 levels. A limitation of this study is that the included studies are observational in nature and residual or unmeasured confounding cannot be ruled out.

CONCLUSIONS/INTERPRETATION

Individuals with a more severe course of diabetes and pre-existing comorbidities had a poorer prognosis of COVID-19 than individuals with a milder course of the disease.

REGISTRATION

PROSPERO registration no. CRD42020193692.

PREVIOUS VERSION

This is a living systematic review and meta-analysis. The previous version can be found at https://link.springer.com/article/10.1007/s00125-021-05458-8 FUNDING: The German Diabetes Center (DDZ) is funded by the German Federal Ministry of Health and the Ministry of Culture and Science of the State North Rhine-Westphalia. This study was supported in part by a grant from the German Federal Ministry of Education and Research to the German Center for Diabetes Research (DZD).

Diabetes Mellitus and Its Association with Adverse In-Hospital Outcomes in Patients with COVID-19-A Nationwide Study

BACKGROUND

Diabetes mellitus (DM) represents a relevant risk factor regarding morbidity and mortality worldwide. However, only limited data exist regarding the impact of DM on the clinical outcome of patients with COVID-19 infection.

METHODS

All hospitalized patients with confirmed COVID-19-infection (ICD-code U07.1) during the year 2020 in Germany were included in the present study. Patients were stratified regarding the co-prevalence of DM (ICD-codes E10-E14), and the impact of DM on in-hospital case fatality and in-hospital adverse events was analyzed.

RESULTS

Overall, 176,137 hospitalizations with confirmed COVID-19 infection were documented; of these, 45,232 (25.7%) patients had an additional diagnosis of DM. Diabetic patients with COVID-19 were more often of male sex and 7 years older (median 76.0 (IQR: 66.0-83.0) vs. 69.0 (52.0-81.0) years, p < 0.001). COVID-19 patients with DM demonstrated an aggravated comorbidity profile, as reflected by a higher Charlson comorbidity index (6.0 (IQR: 4.0-8.0) vs. 3.0 (1.0-5.0), p < 0.001). Risk for pneumonia (OR 1.38 (95% CI: 1.35-1.41), p < 0.001), acute respiratory distress syndrome (OR 1.53 (95% CI: 1.47-1.60), p < 0.001), and need for intensive care (21.3% vs. 13.3%, p < 0.001) were increased in DM patients. DM was an independent risk factor for acute kidney failure (OR 1.49 (95% CI: 1.44-1.53), p < 0.001), dialysis (OR 1.56 (95% CI: 1.47-1.66), p < 0.001), mechanical ventilation (OR: 1.49 (95% CI: 1.43-1.56), p < 0.001), extracorporeal membrane oxygenation (OR 1.44 (95% CI: 1.27-1.62), p < 0.001), major adverse cardiac and cerebrovascular events (OR: 1.24 (95% CI: 1.20-1.27), p < 0.001), and in-hospital mortality (OR: 1.26 (95% CI: 1.22-1.30), p < 0.001).

CONCLUSIONS

In patients with COVID-19-infection, DM is a relevant risk factor for adverse events, including mortality. The vulnerable patient group of diabetics with COVID-19 requires intense medical care and monitoring during hospitalization.

Obesity Is Associated with an Impaired Baseline Repertoire of Anti-Influenza Virus Antibodies

Obesity is a risk factor for severe disease and mortality for both influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. While previous studies show that individuals with obesity generate antibody responses following influenza vaccination, infection rates within the obese group were twice as high as those in the healthy-weight group. The repertoire of antibodies raised against influenza viruses following previous vaccinations and/or natural exposures is referred to here as baseline immune history (BIH). To investigate the hypothesis that obesity impacts immune memory to infections and vaccines, we profiled the BIH of obese and healthy-weight adults vaccinated with the 2010-2011 seasonal influenza vaccine in response to conformational and linear antigens. Despite the extensive heterogeneity of the BIH profiles in both groups, there were striking differences between obese and healthy subjects, especially with regard to A/H1N1 strains and the 2009 pandemic virus (Cal09). Individuals with obesity had lower IgG and IgA magnitude and breadth for a panel of A/H1N1 whole viruses and hemagglutinin proteins from 1933 to 2009 but increased IgG magnitude and breadth for linear peptides from the Cal09 H1 and N1 proteins. Age was also associated with A/H1N1 BIH, with young individuals with obesity being more likely to have reduced A/H1N1 BIH. We found that individuals with low IgG BIH had significantly lower neutralizing antibody titers than individuals with high IgG BIH. Taken together, our findings suggest that increased susceptibility of obese participants to influenza infection may be mediated in part by obesity-associated differences in the memory B-cell repertoire, which cannot be ameliorated by current seasonal vaccination regimens. Overall, these data have vital implications for the next generation of influenza virus and SARS-CoV-2 vaccines. IMPORTANCE Obesity is associated with increased morbidity and mortality from influenza and SARS-CoV-2 infection. While vaccination is the most effective strategy for preventing influenza virus infection, our previous studies showed that influenza vaccines fail to provide optimal protection in obese individuals despite reaching canonical correlates of protection. Here, we show that obesity may impair immune history in humans and cannot be overcome by seasonal vaccination, especially in younger individuals with decreased lifetime exposure to infections and seasonal vaccines. Low baseline immune history is associated with decreased protective antibody responses. Obesity potentially handicaps overall responses to vaccination, biasing it toward responses to linear epitopes, which may reduce protective capacity. Taken together, our data suggest that young obese individuals are at an increased risk of reduced protection by vaccination, likely due to altered immune history biased toward nonprotective antibody responses. Given the worldwide obesity epidemic coupled with seasonal respiratory virus infections and the inevitable next pandemic, it is imperative that we understand and improve vaccine efficacy in this high-risk population. The design, development, and usage of vaccines for and in obese individuals may need critical evaluation, and immune history should be considered an alternate correlate of protection in future vaccine clinical trials.

Protection of hybrid immunity against SARS-CoV-2 reinfection and severe COVID-19 during periods of Omicron variant predominance in Mexico

Background

With the widespread transmission of the Omicron SARS-CoV-2 variant, reinfections have become increasingly common. Here, we explored the role of immunity, primary infection severity, and variant predominance in the risk of reinfection and severe COVID-19 during Omicron predominance in Mexico.

Methods

We analyzed reinfections in Mexico in individuals with a primary infection separated by at least 90 days from reinfection using a national surveillance registry of SARS-CoV-2 cases from March 3rd, 2020, to August 13th, 2022. Immunity-generating events included primary infection, partial or complete vaccination, and booster vaccines. Reinfections were matched by age and sex with controls with primary SARS-CoV-2 infection and negative RT-PCR or antigen test at least 90 days after primary infection to explore reinfection and severe disease risk factors. We also compared the protective efficacy of heterologous and homologous vaccine boosters against reinfection.

Results

We detected 231,202 SARS-CoV-2 reinfections in Mexico, most occurring in unvaccinated individuals (41.55%). Over 207,623 reinfections occurred during periods of Omicron (89.8%), BA.1 (36.74%), and BA.5 (33.67%) subvariant predominance and a case-fatality rate of 0.22%. Vaccination protected against reinfection, without significant influence of the order of immunity-generating events and provided >90% protection against severe reinfections. Heterologous booster schedules were associated with ~11% and ~ 54% lower risk for reinfection and reinfection-associated severe COVID-19, respectively, modified by time-elapsed since the last immunity-generating event, when compared against complete primary schedules.

Conclusion

SARS-CoV-2 reinfections increased during Omicron predominance. Hybrid immunity provides protection against reinfection and associated severe COVID-19, with potential benefit from heterologous booster schedules.

Clan loyalty and COVID-19 diffusion: Evidence from China

This paper addresses the substantial role of clan loyalty in promoting COVID-19 diffusion in China. Using a city-date panel dataset of observations from 183 cities (prefecture-level and above) in the period of the special long holiday of Chinese New Year in 2020 (January 24-March 1), we find that regions with higher clan loyalty have more COVID-19 cases than regions with lower clan loyalty. A one standard deviation increase in clan loyalty is associated with an 8.1% increase in COVID-19 cases. We further document that clan loyalty drives COVID-19 cases by promoting mass gatherings, exploiting a staggered difference-in-differences (DID) regression based on city community-management policy shocks. Our paper provides novel evidence of one negative public health consequence of clan loyalty, namely, its aggravation of COVID-19 cases.

Effectiveness of a nationwide COVID-19 vaccination program in Mexico against symptomatic COVID-19, hospitalizations, and death: a retrospective analysis of national surveillance data

OBJECTIVES

Vaccination has been effective in ameliorating the impact of COVID-19. Here, we report vaccine effectiveness (VE) of the nationally available COVID-19 vaccines in Mexico.

METHODS

Retrospective analysis of a COVID-19 surveillance system to assess the VE of the BNT162b2, messenger RNA (mRNA)-12732, Gam-COVID-Vac, Ad5-nCoV, Ad26.COV2.S, ChAdOx1, and CoronaVac vaccines against SARS-CoV-2 infection, COVID-19 hospitalization, and death in Mexico. The VE was estimated using time-varying Cox proportional hazard models in vaccinated and unvaccinated adults, adjusted for age, sex, and comorbidities. VE was also estimated for adults with diabetes, aged ≥60 years, and comparing the predominance of SARS-CoV-2 variants B.1.1.519 and B.1.617.2.

RESULTS

We assessed 793,487 vaccinated and 4,792,338 unvaccinated adults between December 24, 2020 and September 27, 2021. The VE against SARS-CoV-2 infection was the highest for fully vaccinated individuals with mRNA-12732 (91.5%, 95% confidence interval [CI] 90.3-92.4) and Ad26.COV2.S (82.2%, 95% CI 81.4-82.9); for COVID-19 hospitalization, BNT162b2 (84.3%, 95% CI 83.6-84.9) and Gam-COVID-Vac (81.4% 95% CI 79.5-83.1), and for mortality, BNT162b2 (89.8%, 95% CI 89.2-90.2) and mRNA-12732 (93.5%, 95% CI 86.0-97.0). The VE decreased for all vaccines in adults aged ≥60 years, people with diabetes, and periods of Delta variant predominance.

CONCLUSION

All the vaccines implemented in Mexico were effective against SARS-CoV-2 infection, COVID-19 hospitalization, and death. Mass vaccination with multiple vaccines is useful to maximize vaccination coverage.

Application of C5.0 Algorithm for the Assessment of Perceived Stress in Healthcare Professionals Attending COVID-19

Coronavirus disease (COVID-19) represents one of the greatest challenges to public health in modern history. As the disease continues to spread globally, medical and allied healthcare professionals have become one of the most affected sectors. Stress and anxiety are indirect effects of the COVID-19 pandemic. Therefore, it is paramount to understand and categorize their perceived levels of stress, as it can be a detonating factor leading to mental illness. Here, we propose a computer-based method to better understand stress in healthcare workers facing COVID-19 at the beginning of the pandemic. We based our study on a representative sample of healthcare professionals attending to COVID-19 patients in the northeast region of Mexico, at the beginning of the pandemic. We used a machine learning classification algorithm to obtain a visualization model to analyze perceived stress. The C5.0 decision tree algorithm was used to study datasets. We carried out an initial preprocessing statistical analysis for a group of 101 participants. We performed chi-square tests for all questions, individually, in order to validate stress level calculation (p < 0.05) and a calculated Cronbach's alpha of 0.94 and McDonald's omega of 0.95, demonstrating good internal consistency in the dataset. The obtained model failed to classify only 6 out of the 101, missing two cases for mild, three for moderate and one for severe (accuracy of 94.1%). We performed statistical correlation analysis to ensure integrity of the method. In addition, based on the decision tree model, we concluded that severe stress cases can be related mostly to high levels of xenophobia and compulsive stress. Thus, showing that applied machine learning algorithms represent valuable tools in the assessment of perceived stress, which can potentially be adapted to other areas of the medical field.

Evaluation of Glycemic Control and Predictors of Severe Illness and Death in Patients with Diabetes Hospitalized With COVID-19

Objectives

To identify risk factors for severe disease and death among patients with diabetes and coronavirus disease 2019 (COVID-19) infection.

Methods

This retrospective cohort study conducted at three hospitals included 733 consecutive patients with DM admitted with confirmed COVID-19 (March 1 - December 31, 2020). Multivariable logistic regression was performed to identify predictors of severe disease and death.

Results

The mean age was 67.4 ± 14.3 years, 46.9% were males and 61.5% were African American. Among all patients, 116 (15.8%) died in the hospital. A total of 317 (43.2%) patients developed severe disease, 183 (25%) were admitted to an ICU and 118 (16.1%) required invasive mechanical ventilation. Increasing BMI (OR, 1.13; 95% CI, 1.02-1.25), history of chronic lung disease (OR, 1.49; 95% CI, 1.05-2.10) and increasing time since the last HbA1c test (OR, 1.25; 95% CI, 1.05-1.49) were the preadmission factors associated with increased odds of severe disease. Preadmission use of metformin (OR, 0.67; 95% CI, 0.47-0.95) or GLP-1 agonists (OR, 0.49; 95% CI, 0.27-0.87) was associated with decreased odds of severe disease. Increasing age (OR, 1.21; 95% CI, 1.09-1.34), co-existing chronic kidney disease greater than stage 3 (OR, 3.38; 95% CI, 1.67-6.84), ICU admission (OR, 2.93; 95% CI, 1.28-6.69) and use of invasive mechanical ventilation (OR, 8.67, 95% CI, 3.88-19.39) were independently associated with greater odds of in-hospital death.

Conclusion

Several clinical characteristics were identified to be predictive of severe disease and in-hospital death among patients with underlying diabetes hospitalized with COVID-19.

The intersection of obesity and (long) COVID-19: Hypoxia, thrombotic inflammation, and vascular endothelial injury

The role of hypoxia, vascular endothelial injury, and thrombotic inflammation in worsening COVID-19 symptoms has been generally recognized. Damaged vascular endothelium plays a crucial role in forming in situ thrombosis, pulmonary dysfunction, and hypoxemia. Thrombotic inflammation can further aggravate local vascular endothelial injury and affect ventilation and blood flow ratio. According to the results of many studies, obesity is an independent risk factor for a variety of severe respiratory diseases and contributes to high mechanical ventilation rate, high mortality, and slow recovery in COVID-19 patients. This review will explore the mechanisms by which obesity may aggravate the acute phase of COVID-19 and delay long COVID recovery by affecting hypoxia, vascular endothelial injury, and thrombotic inflammation. A systematic search of PubMed database was conducted for papers published since January 2020, using the medical subject headings of "COVID-19" and "long COVID" combined with the following keywords: "obesity," "thrombosis," "endothelial injury," "inflammation," "hypoxia," "treatment," and "anticoagulation." In patients with obesity, the accumulation of central fat restricts the expansion of alveoli, exacerbating the pulmonary dysfunction caused by SARS-CoV-2 invasion, inflammatory damage, and lung edema. Abnormal fat secretion and immune impairment further aggravate the original tissue damage and inflammation diffusion. Obesity weakens baseline vascular endothelium function leading to an early injury and pre-thrombotic state after infection. Enhanced procoagulant activity and microthrombi promote early obstruction of the vascular. Obesity also prolongs the duration of symptoms and increases the risk of sequelae after hospital discharge. Persistent viral presence, long-term inflammation, microclots, and hypoxia may contribute to the development of persistent symptoms, suggesting that patients with obesity are uniquely susceptible to long COVID. Early interventions, including supplemental oxygen, comprehensive antithrombotic therapy, and anti-inflammatory drugs, show effectiveness in many studies in the prevention of serious hypoxia, thromboembolic events, and systemic inflammation, and are therefore recommended to reduce intensive care unit admission, mortality, and sequelae.

Deep Learning-Based Time-to-Death Prediction Model for COVID-19 Patients Using Clinical Data and Chest Radiographs

Accurate estimation of mortality and time to death at admission for COVID-19 patients is important and several deep learning models have been created for this task. However, there are currently no prognostic models which use end-to-end deep learning to predict time to event for admitted COVID-19 patients using chest radiographs and clinical data. We retrospectively implemented a new artificial intelligence model combining DeepSurv (a multiple-perceptron implementation of the Cox proportional hazards model) and a convolutional neural network (CNN) using 1356 COVID-19 inpatients. For comparison, we also prepared DeepSurv only with clinical data, DeepSurv only with images (CNNSurv), and Cox proportional hazards models. Clinical data and chest radiographs at admission were used to estimate patient outcome (death or discharge) and duration to the outcome. The Harrel's concordance index (c-index) of the DeepSurv with CNN model was 0.82 (0.75-0.88) and this was significantly higher than the DeepSurv only with clinical data model (c-index = 0.77 (0.69-0.84), p = 0.011), CNNSurv (c-index = 0.70 (0.63-0.79), p = 0.001), and the Cox proportional hazards model (c-index = 0.71 (0.63-0.79), p = 0.001). These results suggest that the time-to-event prognosis model became more accurate when chest radiographs and clinical data were used together.

Probiotic induced synthesis of microbiota polyamine as a nutraceutical for metabolic syndrome and obesity-related type 2 diabetes

The gut microbiota regulates multiple facets of host metabolism and immunity through the production of signaling metabolites, such as polyamines which are small organic compounds that are essential to host cell growth and lymphocyte activation. Polyamines are most abundant in the intestinal lumen, where their synthesis by the gut microbiota is influenced by microbiome composition and host diet. Disruption of the host gut microbiome in metabolic syndrome and obesity-related type 2 diabetes (obesity/T2D) results in potential dysregulation of polyamine synthesis. A growing body of evidence suggests that restoration of the dysbiotic gut microbiota and polyamine synthesis is effective in ameliorating metabolic syndrome and strengthening the impaired immune responses of obesity/T2D. In this review, we discuss existing studies on gut microbiome determinants of polyamine synthesis, polyamine production in obesity/T2D, and evidence that demonstrates the potential of polyamines as a nutraceutical in obesity/T2D hosts.

Lethality risk markers by sex and age-group for COVID-19 in Mexico: a cross-sectional study based on machine learning approach

BACKGROUND

Mexico ranks fifth worldwide in the number of deaths due to COVID-19. Identifying risk markers through easily accessible clinical data could help in the initial triage of COVID-19 patients and anticipate a fatal outcome, especially in the most socioeconomically disadvantaged regions. This study aims to identify markers that increase lethality risk in patients diagnosed with COVID-19, based on machine learning (ML) methods. Markers were differentiated by sex and age-group.

METHODS

A total of 11,564 cases of COVID-19 in Mexico were extracted from the Epidemiological Surveillance System for Viral Respiratory Disease. Four ML classification methods were trained to predict lethality, and an interpretability approach was used to identify those markers.

RESULTS

Models based on Extreme Gradient Boosting (XGBoost) yielded the best performance in a test set. This model achieved a sensitivity of 0.91, a specificity of 0.69, a positive predictive value of 0.344, and a negative predictive value of 0.965. For female patients, the leading markers are diabetes and arthralgia. For males, the main markers are chronic kidney disease (CKD) and chest pain. Dyspnea, hypertension, and polypnea increased the risk of death in both sexes.

CONCLUSIONS

ML-based models using an interpretability approach successfully identified risk markers for lethality by sex and age. Our results indicate that age is the strongest demographic factor for a fatal outcome, while all other markers were consistent with previous clinical trials conducted in a Mexican population. The markers identified here could be used as an initial triage, especially in geographic areas with limited resources.

Chronic diseases and mortality among hospitalised COVID-19 patients at Bafoussam Regional Hospital in the West region of Cameroon

Reducing mortality among COVID-19 cases is a major challenge for most health systems worldwide. Estimating the risk of preexisting comorbidities on COVID-19 mortality may promote the importance of targeting at-risk populations to improve survival through primary and secondary prevention. This study was conducted to explore the contribution of exposure to some chronic diseases on the mortality of COVID-19. This was a case control study. The data were collected from the records of all patients hospitalised at Bafoussam Regional Hospital (BRH) from March 2020 to December 2021. A grid was used to extract data on patient history, case management and outcome of hospitalised patients. We estimated the frequency of each common chronic disease and assessed the association between suffering from all and each chronic disease (Diabetes or/and Hypertension, immunodeficiency condition, obesity, tuberculosis, chronic kidney disease) and fatal outcome of hospitalised patients by estimating crude and adjusted odd ratios and their corresponding 95% confidence intervals (CI) using time to symptom onset and hospital admission up to three days, age range 65 years and above, health professional worker and married status as confounder's factors. Of 645 included patients, 120(20.23%) deaths were recorded. Among these 645 patients, 262(40.62%) were males, 128(19.84%) aged 65 years and above. The mean length of stay was 11.07. On admission, 204 (31.62%) patients presented at least one chronic disease. The most common chronic disease were hypertension (HBP) 73(11.32%), followed by diabetes + HBP 62 (9.61%), by diabetes 55(8.53%) and Immunodeficiency condition 14(2.17%). Diabetes and Diabetes + HBP were associated with a higher risk of death respectively aOR = 2.71[95%CI = 1.19-6.18] and aOR = 2.07[95% CI = 1.01-4.23] but HBP did not significantly increased the risk of death. These results suggest that health authorities should prioritize these specific group to adopt primary and secondary preventive interventions against SARS-CoV-2 infection.

Predictors of mortality and ICU requirement in hospitalized COVID-19 patients with diabetes: A multicentre study

AIM

This study aimed to identify the predictors of mortality and ICU requirements in hospitalized COVID-19 Patients with Diabetes.

DESIGN

Cross-sectional study.

METHODS

It was a retrospective study of patients hospitalized with COVID-19 infection from October 2020-February 2021 in four hospitals in Sylhet, Bangladesh. Logistic regression analysis was applied to explore the predictors of ICU requirement and in-hospital mortality.

RESULTS

In the whole cohort (n = 500), 11% of patients died and 24% of patients required intensive care unit (ICU) support. Non-survivors had significantly higher prevalence of lymphopenia, thrombocytopenia and leukocytosis. Significant predictors of in-hospital mortality were older age, neutrophil count, platelet count and admission peripheral capillary oxygen saturation (SpO2). Older age, ischemic heart disease, WBC count, D-dimer and admission SpO2 were identified as significant predictors for ICU requirement.

PATIENT OR PUBLIC CONTRIBUTION

No.

Association of hypernatremia with outcomes of COVID-19 patients: A protocol for systematic review and meta-analysis

BACKGROUND

This systematic review and meta-analysis aimed to assess the association of hypernatremia with the outcomes of COVID-19 patients.

METHODS

We performed a systematic literature search on PubMed, Google Scholar, and Science Direct until October 2021 and found a total of 131 papers. With meticulous screening finally, 17 papers met the inclusion criteria. COVID-19 patients with sodium levels greater than the reference level were the study population and the outcome of interest was the poor outcome; such as mortality, mechanical ventilation, intensive care unit (ICU) admission, and prolonged hospital stay. The pooled estimate was calculated as the odds ratio (OR).

RESULTS

There were 19,032 patients with hypernatremia in the 17 studies included. An overall random effect meta-analysis showed that hypernatremia was associated with mortality (OR: 3.18 [1.61, 6.28], P < .0001, I2 = 91.99%), prolong hospitalization (OR: 1.97 [1.37, 2.83], P < .001, I2 = 0.00%) and Ventilation (OR: 5.40 [1.89, 15.42], P < .001, I2 = 77.35%), ICU admission (OR: 3.99 [0.89, 17.78], P = .07, I2 = 86.79%). Meta-regression analysis showed the association of age with the ICU outcome of hypernatremia patients. Whereas, other parameters like male, hypertension, chronic kidney disease, and diabetes mellitus did not significantly influence the odds ratio.

CONCLUSION

Hypernatremia was markedly associated with poor outcomes in patients with COVID-19. Hence, a blood ionogram is warranted and special attention must be given to hypernatremia COVID-19 patients.

Low muscle strength and low phase angle predicts greater risk to mortality than severity scales (APACHE, SOFA, and CURB-65) in adults hospitalized for SARS-CoV-2 pneumonia

Introduction

The acute physiology and chronic health evaluation (APACHE), sepsis-related organ failure assessment (SOFA), score for pneumonia severity (CURB-65) scales, a low phase angle (PA) and low muscle strength (MS) have demonstrated their prognostic risk for mortality in hospitalized adults. However, no study has compared the prognostic risk between these scales and changes in body composition in a single study in adults with SARS-CoV-2 pneumonia. The great inflammation and complications that this disease presents promotes immobility and altered nutritional status, therefore a low PA and low MS could have a higher prognostic risk for mortality than the scales. The aim of the present study was to evaluate the prognostic risk for mortality of PA, MS, APACHE, SOFA, and CURB-65 in adults hospitalized with SARS-CoV-2 pneumonia.

Methodology

This was a longitudinal study that included n = 104 SARS-CoV-2-positive adults hospitalized at General Hospital Penjamo, Guanajuato, Mexico, the PA was assessed using bioelectrical impedance and MS was measured with manual dynamometry. The following disease severity scales were applied as well: CURB-65, APACHE, and SOFA. Other variables analyzed were: sex, age, CO-RADS index, fat mass index, body mass index (BMI), and appendicular muscle mass index. A descriptive analysis of the study variables and a comparison between the group that did not survive and survived were performed, as well as a Cox regression to assess the predictive risk to mortality.

Results

Mean age was 62.79 ± 15.02 years (31-96). Comparative results showed a mean PA of 5.43 ± 1.53 in the group that survived vs. 4.81 ± 1.72 in the group that died, p = 0.030. The mean MS was 16.61 ± 10.39 kg vs. 9.33 ± 9.82 in the group that died, p = 0.001. The cut-off points for low PA was determined at 3.66° and ≤ 5.0 kg/force for low grip strength. In the Cox multiple regression, a low PA [heart rate (HR) = 2.571 0.726, 95% CI = 1.217-5.430] and a low MS (HR = 4.519, 95% CI = 1.992-10.252) were associated with mortality.

Conclusion

Phase angle and MS were higher risk predictors of mortality than APACHE, SOFA, and CURB-65 in patients hospitalized for COVID-19. It is important to include the assessment of these indicators in patients positive for SARS-CoV-2 and to be able to implement interventions to improve them.

Body Mass Index and Clinical Outcomes in Adult COVID-19 Patients of Diverse Ethnicities

(1) Background: Body mass index (BMI) was observed to affect COVID-19 outcomes; however, the complete spectrum of clinical outcomes concerning BMI remains unexplored. The current study aimed to investigate the correlation between BMI and the severity and mortality of COVID-19, as well as ICU admission, radiological findings, clinical presentation, and time to viral clearance. (2) Methods: This retrospective study included 1796 multiethnic patients with COVID-19 treated at NMC Royal Hospital, Abu Dhabi, UAE. (3) Results: COVID-19’s adjusted odds of severity increased by 3.7- and 21.5-fold in classes I and III, respectively (p = 0.001). The odds of mortality were not significantly different after adjustment for age, sex, and race. The adjusted odds of ICU admission increased significantly by 3-fold and non-significantly by 4-fold in obesity classes I and II, respectively. Pneumonia was significantly higher in patients who were overweight and class I, II, and III obese. Furthermore, class III obese patients had a greater risk of presenting with combined respiratory and gastrointestinal manifestations (p < 0.001). The median time to viral clearance with a BMI > 40 kg/m2 was moderately higher than that with a BMI < 40 kg/m2. (4) Conclusions: High BMI was associated with pneumonia, ICU admission, severity, and mortality due to COVID-19.

Predicting COVID-19 prognosis in the ICU remained challenging: external validation in a multinational regional cohort

OBJECTIVES

Many prediction models for coronavirus disease 2019 (COVID-19) have been developed. External validation is mandatory before implementation in the intensive care unit (ICU). We selected and validated prognostic models in the Euregio Intensive Care COVID (EICC) cohort.

STUDY DESIGN AND SETTING

In this multinational cohort study, routine data from COVID-19 patients admitted to ICUs within the Euregio Meuse-Rhine were collected from March to August 2020. COVID-19 models were selected based on model type, predictors, outcomes, and reporting. Furthermore, general ICU scores were assessed. Discrimination was assessed by area under the receiver operating characteristic curves (AUCs) and calibration by calibration-in-the-large and calibration plots. A random-effects meta-analysis was used to pool results.

RESULTS

551 patients were admitted. Mean age was 65.4 ± 11.2 years, 29% were female, and ICU mortality was 36%. Nine out of 238 published models were externally validated. Pooled AUCs were between 0.53 and 0.70 and calibration-in-the-large between -9% and 6%. Calibration plots showed generally poor but, for the 4C Mortality score and Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC) score, moderate calibration.

CONCLUSION

Of the nine prognostic models that were externally validated in the EICC cohort, only two showed reasonable discrimination and moderate calibration. For future pandemics, better models based on routine data are needed to support admission decision-making.

Diabetes-Related Excess Mortality in Mexico: A Comparative Analysis of National Death Registries Between 2017-2019 and 2020

OBJECTIVE

To estimate diabetes-related mortality in Mexico in 2020 compared with 2017-2019 after the onset of the coronavirus disease 2019 (COVID-19) pandemic.

RESEARCH DESIGN AND METHODS

This retrospective, state-level study used national death registries of Mexican adults aged ≥20 years for the 2017-2020 period. Diabetes-related death was defined using ICD-10 codes listing diabetes as the primary cause of death, excluding certificates with COVID-19 as the primary cause of death. Spatial and negative binomial regression models were used to characterize the geographic distribution and sociodemographic and epidemiologic correlates of diabetes-related excess mortality, estimated as increases in diabetes-related mortality in 2020 compared with average 2017-2019 rates.

RESULTS

We identified 148,437 diabetes-related deaths in 2020 (177 per 100,000 inhabitants) vs. an average of 101,496 deaths in 2017-2019 (125 per 100,000 inhabitants). In-hospital diabetes-related deaths decreased by 17.8% in 2020 versus 2017-2019, whereas out-of-hospital deaths increased by 89.4%. Most deaths were attributable to type 2 diabetes (130 per 100,000 inhabitants). Compared with 2018-2019 data, hyperglycemic hyperosmolar state and diabetic ketoacidosis were the two contributing causes with the highest increase in mortality (128% and 116% increase, respectively). Diabetes-related excess mortality clustered in southern Mexico and was highest in states with higher social lag, rates of COVID-19 hospitalization, and prevalence of HbA1c ≥7.5%.

CONCLUSIONS

Diabetes-related deaths increased among Mexican adults by 41.6% in 2020 after the onset of the COVID-19 pandemic, occurred disproportionately outside the hospital, and were largely attributable to type 2 diabetes and hyperglycemic emergencies. Disruptions in diabetes care and strained hospital capacity may have contributed to diabetes-related excess mortality in Mexico during 2020.

Predicting COVID-19 progression in hospitalized patients in Belgium from a multi-state model

Objectives

To adopt a multi-state risk prediction model for critical disease/mortality outcomes among hospitalised COVID-19 patients using nationwide COVID-19 hospital surveillance data in Belgium.

Materials and methods

Information on 44,659 COVID-19 patients hospitalised between March 2020 and June 2021 with complete data on disease outcomes and candidate predictors was used to adopt a multi-state, multivariate Cox model to predict patients' probability of recovery, critical [transfer to intensive care units (ICU)] or fatal outcomes during hospital stay.

Results

Median length of hospital stay was 9 days (interquartile range: 5-14). After admission, approximately 82% of the COVID-19 patients were discharged alive, 15% of patients were admitted to ICU, and 15% died in the hospital. The main predictors of an increased probability for recovery were younger age, and to a lesser extent, a lower number of prevalent comorbidities. A patient's transition to ICU or in-hospital death had in common the following predictors: high levels of c-reactive protein (CRP) and lactate dehydrogenase (LDH), reporting lower respiratory complaints and male sex. Additionally predictors for a transfer to ICU included middle-age, obesity and reporting loss of appetite and staying at a university hospital, while advanced age and a higher number of prevalent comorbidities for in-hospital death. After ICU, younger age and low levels of CRP and LDH were the main predictors for recovery, while in-hospital death was predicted by advanced age and concurrent comorbidities.

Conclusion

As one of the very few, a multi-state model was adopted to identify key factors predicting COVID-19 progression to critical disease, and recovery or death.

Excess Mortality in California by Education During the COVID-19 Pandemic

INTRODUCTION

Understanding educational patterns in excess mortality during the coronavirus disease 2019 (COVID-19) pandemic may help to identify strategies to reduce disparities. It is unclear whether educational inequalities in COVID-19 mortality have persisted throughout the pandemic, spanned the full range of educational attainment, or varied by other demographic indicators of COVID-19 risks, such as age or occupation.

METHODS

This study analyzed individual-level California Department of Public Health data on deaths occurring between January 2016 and February 2021 among individuals aged ≥25 years (1,502,202 deaths). Authors applied ARIMA (autoregressive integrated moving average) models to subgroups defined by the highest level of education and other demographics (age, sex, race/ethnicity, U.S. nativity, occupational sector, and urbanicity). Authors estimated excess deaths (the number of observed deaths minus the number of deaths expected to occur under the counterfactual of no pandemic) and excess deaths per 100,000 individuals.

RESULTS

Educational inequalities in excess mortality emerged early in the pandemic and persisted throughout the first year. The greatest per-capita excess occurred among people without high-school diplomas (533 excess deaths/100,000), followed by those with a high-school diploma but no college (466/100,000), some college (156/100,000), and bachelor's degrees (120/100,000), and smallest among people with graduate/professional degrees (101/100,000). Educational inequalities occurred within every subgroup examined. For example, per-capita excess mortality among Latinos with no college experience was 3.7 times higher than among Latinos with at least some college experience.

CONCLUSIONS

Pervasive educational inequalities in excess mortality during the pandemic suggest multiple potential intervention points to reduce disparities.