Metabolic syndrome and clinical outcomes in patients infected with COVID-19: Does age, sex, and race of the patient with metabolic syndrome matter?

Obesity modifies the association of race and COVID-19 mortality: analysis of a retrospective cohort from Brazil

COVID-19 and obesity are two concurrent, interrelated pandemics that share similarities in their social causes, including racism. It is essential to understand how their characteristics are interrelated and the possible role of obesity in the association between race and COVID-19 mortality. We investigated the relationship between race and COVID-19 mortality and the modifying effect of obesity on this relationship. It is a retrospective cohort study. We analyzed data from 113,737 adults aged ≥ 19 years hospitalized for COVID-19 in Rio Grande do Sul, Brazil. The study outcome was in-hospital COVID-19 mortality. Exposures included race, analyzed as white, Brown, and Black individuals and as white vs. Brown and Black individuals, and obesity. The cumulative incidence of COVID-19 mortality was 33.46% (95% CI 33.18-33.74). Compared with white individuals, Brown individuals had a 39% higher likelihood of death from COVID-19 (95% CI 1.28-1.52), while Black individuals had a 30% higher likelihood (95% CI 1.20-1.41). Brown women with obesity had the greatest likelihood of COVID-19 mortality (1.64 [95% CI 1.27-2.13]) compared with all other groups. Obesity was an effect modifier of the association between race and COVID-19 mortality, increasing the likelihood of mortality in the group of Brown women.

Exploratory analysis of the variable response to an intensive lifestyle change program for metabolic syndrome

BACKGROUND

Substantial variability in response to lifestyle interventions has been recognized for many years, and researchers have begun to disentangle sources of error from inherent differences in individual responsiveness. The objective of this secondary analysis of an intensive lifestyle intervention (diet and exercise) for metabolic syndrome (MetS) was to identify potentially important differences among study completers grouped by treatment response as measured by change in a continuous metabolic syndrome score (Gurka/MetS).

METHODS

All study completers from a 12-month primary care study were categorized into one of five groups according to change in the Gurka/MetS score. A change of 0.4 in z-score defined clinically relevant change in line with results of previous studies. Repeated measures analysis of variance was used to examine cardiovascular disease risk and individual clinical indicators of MetS over 12 months, looking for differences in response over time by the five groups.

RESULTS

Of 176 participants, 50% (n = 88) had stable scores, 10% (n = 18) had relevant change scores in the first 3 months only and reverted toward baseline, 20% (n = 35) achieved meaningful change over the whole study, 11% (n = 20) had a delayed response at 3-12 months, and 9% (n = 15) demonstrated worsening scores. Significant differential patterns were noted for groups over the duration of the intervention (p < .001). Improvement in diet quality and fitness scores were similar across all groups. Other available variables were tested and did not account for the differences.

CONCLUSION

Work is needed to identify key factors that account for differences in responses to lifestyle interventions that can be used to guide treatment decisions for intensive lifestyle interventions for this common condition.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01616563; first registered June 12, 2012.

Exploring the Association of Metabolic Syndrome with In-Hospital Survival of Older Patients Hospitalized with COVID-19: Beyond Chronological Age

BACKGROUND

Despite the variability and complexity of geriatric conditions, few COVID-19 reports of clinical characteristic prognostication provide data specific to oldest-old adults (over age 85), and instead generally report broadly as 65 and older.

OBJECTIVE

To examine metabolic syndrome criteria in adults across 25 hospitals with variation in chronological age.

DESIGN AND PARTICIPANTS

This cohort study examined 39,564 hospitalizations of patients aged 18 or older with COVID-19 who received inpatient care between March 13, 2020, and February 28, 2022.

EXPOSURE

ICU admission and/or in-hospital mortality.

MAIN MEASURES

Metabolic syndrome criteria and patient demographics were examined as risk factors. The main outcomes were admission to ICU and hospital mortality.

KEY RESULTS

Oldest old patients (≥ 85 years) hospitalized with COVID-19 accounted for 7.0% (2758/39,564) of all adult hospitalizations. They had shorter ICU length of stay, similar overall hospitalization duration, and higher rates of discharge destinations providing healthcare services (i.e., home health, skilled nursing facility) compared to independent care. Chronic conditions varied by age group, with lower proportions of diabetes and uncontrolled diabetes in the oldest-old cohort compared with young-old (65-74 years) and middle-old (75-84 years) groups. Evaluations of the effect of metabolic syndrome and patient demographics (i.e., age, sex, race) on ICU admission demonstrate minimal change in the magnitude of effect for metabolic syndrome on ICU admission across the different models.

CONCLUSIONS

Metabolic syndrome measures are important individual predictors of COVID-19 outcomes. Building on prior examinations that metabolic syndrome is associated with death and ARDS across all ages, this analysis supports that metabolic syndrome criteria may be more relevant than chronological age as risk factors for poor outcomes attributed to COVID-19.

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.

Association Between Metabolic Syndrome and Outcomes in Complex Head and Neck Surgery

OBJECTIVES

We aim to evaluate the impact of MetS on the short-term postoperative outcomes of complex head and neck surgery patients.

METHODS

This is a retrospective cohort analysis of the 2005 to 2017 National Surgical Quality Improvement Program (NSQIP) database. NSQIP database was queried for 30-day outcomes of patients undergoing complex head and neck surgeries, defined as laryngectomy or mucosal resection followed by free tissue transfer, similar to prior NSQIP studies. Patients with hypertension, diabetes, and body mass index (BMI) >30 kg/m2 were defined as having MetS. Adverse events were defined as experiencing readmission, reoperation, surgical/medical complications, or mortality.

RESULTS

A total of 2764 patients (27.0% female) with a mean age of 62.0 ± 11.7 years were included. Patients with MetS (n = 108, 3.9%) were more likely to be female (P = .017) and have high ASA classification (P = .030). On univariate analysis, patients with MetS were more likely to require reoperation (25.9% vs 16.7%, P = .013) and experience medical complications (26.9% vs 15.4% P = .001) or any adverse events (61.1% vs 48.7%, P = .011) compared to patients without MetS. On multivariate logistic regression after adjusting for age, sex, race, ASA classification, and complex head and neck surgery type, MetS was an independent predictor of medical complications (odds ratio 2.34, 95% CI 1.28-4.27, P = .006).

CONCLUSION

Patients with MetS undergoing complex head and neck surgery are at increased risk of experiencing medical complications. Identifying patients with MetS can therefore aid surgeons in preoperative risk assessment and help improve postoperative management.

LEVEL OF EVIDENCE

N/A.

Insulin Resistance and Metabolic Syndrome as Risk Factors for Hospitalization in Patients with COVID-19: Pilot Study on the Use of Machine Learning

Aim: Conditions linked to metabolic syndrome, such as obesity, hypertension, insulin resistance, and dyslipidemia, are common in patients with severe coronavirus disease 2019 (COVID-19). These conditions can act synergistically to contribute to negative outcomes. We describe and analyze the relationship between metabolic syndrome and COVID-19 severity in terms of risk of hospitalization. Methods: We designed a retrospective, cross-sectional study, including patients with confirmed COVID-19 diagnosis. Clinical and laboratory parameters regarding metabolic syndrome were collected. The Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) was used to assess insulin resistance. The outcome was needed for hospitalization. Logistic regression was used to calculate odds ratios, and to determine the association between variables and risk of hospitalization. Advanced approaches using machine learning were also used to identify and interpret the effects of predictors on the proposed outcome. Results: We included 2716 COVID-19 patients with a mean age of 61.8 years. Of these, 48.9% were women, 28.9% had diabetes, and 50.6% were diagnosed with metabolic syndrome. Overall, 212 patients required hospitalization. Patients with metabolic syndrome had a 58% greater chance of hospitalization if they were men, 32% if they had metabolic syndrome, and 23% if they were obese. Machine learning methods identified body mass index, metabolic syndrome, systolic blood pressure, and HOMA-IR as the most relevant features for our predictive model. Conclusion: Metabolic syndrome and its related biomarkers increase the odds for a severe clinical course of COVID-19 and the need for hospitalization. Machine learning methods can aid understanding of the effects of single features when assessing risks for a given outcome.

Obesity as an independent risk factor for COVID-19 severity and mortality

BACKGROUND

Since December 2019, the world has struggled with the COVID-19 pandemic. Even after the introduction of various vaccines, this disease still takes a considerable toll. In order to improve the optimal allocation of resources and communication of prognosis, healthcare providers and patients need an accurate understanding of factors (such as obesity) that are associated with a higher risk of adverse outcomes from the COVID-19 infection.

OBJECTIVES

To evaluate obesity as an independent prognostic factor for COVID-19 severity and mortality among adult patients in whom infection with the COVID-19 virus is confirmed.

SEARCH METHODS

MEDLINE, Embase, two COVID-19 reference collections, and four Chinese biomedical databases were searched up to April 2021.

SELECTION CRITERIA

We included case-control, case-series, prospective and retrospective cohort studies, and secondary analyses of randomised controlled trials if they evaluated associations between obesity and COVID-19 adverse outcomes including mortality, mechanical ventilation, intensive care unit (ICU) admission, hospitalisation, severe COVID, and COVID pneumonia. Given our interest in ascertaining the independent association between obesity and these outcomes, we selected studies that adjusted for at least one factor other than obesity. Studies were evaluated for inclusion by two independent reviewers working in duplicate.  DATA COLLECTION AND ANALYSIS: Using standardised data extraction forms, we extracted relevant information from the included studies. When appropriate, we pooled the estimates of association across studies with the use of random-effects meta-analyses. The Quality in Prognostic Studies (QUIPS) tool provided the platform for assessing the risk of bias across each included study. In our main comparison, we conducted meta-analyses for each obesity class separately. We also meta-analysed unclassified obesity and obesity as a continuous variable (5 kg/m2 increase in BMI (body mass index)). We used the GRADE framework to rate our certainty in the importance of the association observed between obesity and each outcome. As obesity is closely associated with other comorbidities, we decided to prespecify the minimum adjustment set of variables including age, sex, diabetes, hypertension, and cardiovascular disease for subgroup analysis.  MAIN RESULTS: We identified 171 studies, 149 of which were included in meta-analyses.  As compared to 'normal' BMI (18.5 to 24.9 kg/m2) or patients without obesity, those with obesity classes I (BMI 30 to 35 kg/m2), and II (BMI 35 to 40 kg/m2) were not at increased odds for mortality (Class I: odds ratio [OR] 1.04, 95% confidence interval [CI] 0.94 to 1.16, high certainty (15 studies, 335,209 participants); Class II: OR 1.16, 95% CI 0.99 to 1.36, high certainty (11 studies, 317,925 participants)). However, those with class III obesity (BMI 40 kg/m2 and above) may be at increased odds for mortality (Class III: OR 1.67, 95% CI 1.39 to 2.00, low certainty, (19 studies, 354,967 participants)) compared to normal BMI or patients without obesity. For mechanical ventilation, we observed increasing odds with higher classes of obesity in comparison to normal BMI or patients without obesity (class I: OR 1.38, 95% CI 1.20 to 1.59, 10 studies, 187,895 participants, moderate certainty; class II: OR 1.67, 95% CI 1.42 to 1.96, 6 studies, 171,149 participants, high certainty; class III: OR 2.17, 95% CI 1.59 to 2.97, 12 studies, 174,520 participants, high certainty). However, we did not observe a dose-response relationship across increasing obesity classifications for ICU admission and hospitalisation.

AUTHORS' CONCLUSIONS

Our findings suggest that obesity is an important independent prognostic factor in the setting of COVID-19. Consideration of obesity may inform the optimal management and allocation of limited resources in the care of COVID-19 patients.

The effects of hypertension on the prognosis of coronavirus disease 2019: a systematic review and meta-analysis on the interactions with age and antihypertensive treatment

BACKGROUND

Hypertension and angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs) have been reported to be associated with the prognosis of COVID-19, but the findings remain controversial. Here, we conducted a systematic review to summarize the current evidence.

METHODS

We retrieved all the studies by MEDLINE via PubMed, CENTRAL, and Embase using the MeSH terms until 30 April 2021. A fixed or random effect model was applied to calculate pooled adjusted odds ratio (AOR) with 95% confidence interval (CI). Interactive analysis was performed to identify the interaction effect of hypertension and age on in-hospital mortality.

RESULTS

In total, 86 articles with 18 775 387 COVID-19 patients from 18 countries were included in this study. The pooled analysis showed that the COVID-19 patients with hypertension had increased risks of in-hospital mortality and other adverse outcomes, compared with those without hypertension, with an AOR (95% CI) of 1.36 (1.28-1.45) and 1.32 (1.24-1.41), respectively. The results were mostly repeated in countries with more than three independent studies. Furthermore, the effect of hypertension on in-hospital mortality is more evident in younger and older COVID-19 patients than in 60-69-year-old patients. ACEI/ARBs did not significantly affect the mortality and adverse outcomes of COVID-19 patients, compared with those receiving other antihypertensive treatments.

CONCLUSION

Hypertension is significantly associated with an increased risk of in-hospital mortality and adverse outcomes in COVID-19. The effect of hypertension on in-hospital mortality among consecutive age groups followed a U-shaped curve. ACEI/ARB treatments do not increase in-hospital mortality and other poor outcomes of COVID-19 patients with hypertension.

Correlation between Type I Interferon Associated Factors and COVID-19 Severity

Antiviral type I interferons (IFN) produced in the early phase of viral infections effectively inhibit viral replication, prevent virus-mediated tissue damages and promote innate and adaptive immune responses that are all essential to the successful elimination of viruses. As professional type I IFN producing cells, plasmacytoid dendritic cells (pDC) have the ability to rapidly produce waste amounts of type I IFNs. Therefore, their low frequency, dysfunction or decreased capacity to produce type I IFNs might increase the risk of severe viral infections. In accordance with that, declined pDC numbers and delayed or inadequate type I IFN responses could be observed in patients with severe coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as compared to individuals with mild or no symptoms. Thus, besides chronic diseases, all those conditions, which negatively affect the antiviral IFN responses lengthen the list of risk factors for severe COVID-19. In the current review, we would like to briefly discuss the role and dysregulation of pDC/type I IFN axis in COVID-19, and introduce those type I IFN-dependent factors, which account for an increased risk of COVID-19 severity and thus are responsible for the different magnitude of individual immune responses to SARS-CoV-2.

Pre-existing comorbidities shape the immune response associated with severe COVID-19

BACKGROUND

Comorbidities are risk factors for the development of severe COVID-19. However, to which extent an underlying comorbidity influences the immune response to SARS-CoV-2 remains unknown.

OBJECTIVE AND METHODS

High-throughput, high-dimensional single-cell-mapping of peripheral blood leukocytes and algorithm-guided analysis were employed to investigate the complex interrelations of comorbidities, the immune response and patient outcome in COVID-19.

RESULTS

We discovered characteristic immune signatures associated not only with severe COVID-19, but also with the underlying medical condition. Different factors of the metabolic syndrome (obesity-hypertension-diabetes) affected distinct immune populations, thereby additively increasing the immune dysregulatory effect when present in a single patient. Patients with disorders affecting the lung or heart together with factors of metabolic syndrome clustered together, while immune disorder and chronic kidney disease displayed a distinct immune profile in COVID-19. Particularly SARS-CoV-2-infected patients with pre-existing chronic kidney disease were characterized by the highest number of altered immune signatures of both lymphoid and myeloid immune branches. This overall major immune dysregulation could be the underlying mechanism for the estimated odds ratio of 16.3 for severe COVID-19 in this burdened cohort.

CONCLUSION

The combinatorial systematic analysis of COVID-19 patient immune signatures, comorbidities, and patient outcomes provides the mechanistic immunological underpinnings of comorbidity-driven patient risk and uncovered comorbidity-driven immune signatures.

Comparing body mass index and obesity-related comorbidities as predictors in hospitalized COVID-19 patients

The association between body mass index (BMI) and poor COVID-19 outcomes in patients has been demonstrated across numerous studies. However, obesity-related comorbidities have also been shown to be associated with poor outcomes. The purpose of this study was to determine whether BMI or obesity-associated comorbidities contribute to elevated COVID-19 severity in non-elderly, hospitalized patients with elevated BMI (≥25 kg/m2 ). This was a single-center, retrospective cohort study of 526 hospitalized, non-elderly adult (aged 18-64) COVID-19 patients with BMI ≥25 kg/m2 in suburban New York from March 6 to May 11, 2020. The Edmonton Obesity Staging System (EOSS) was used to quantify the severity of obesity-related comorbidities. EOSS was compared with BMI in multivariable regression analyses to predict COVID-19 outcomes. We found that higher EOSS scores were associated with poor outcomes after demographic adjustment, unlike BMI. Specifically, patients with increased EOSS scores had increased odds of acute kidney injury (adjusted odds ratio [aOR] = 6.40; 95% CI 3.71-11.05), intensive care unit admission (aOR = 10.71; 95% CI 3.23-35.51), mechanical ventilation (aOR = 3.10; 95% CI 2.01-4.78) and mortality (aOR = 5.05; 95% CI 1.83-13.90). Obesity-related comorbidity burden as determined by EOSS was a better predictor of poor COVID-19 outcomes relative to BMI, suggesting that comorbidity burden may be driving risk in those hospitalized with elevated BMI.

Impact of Metabolic Syndrome on Severity of COVID-19 Illness

Background: Hypertension, diabetes, and obesity are common comorbidities that portend worse outcomes due to coronavirus disease 2019 (COVID-19). Metabolic syndrome is the common denominator of these conditions. This study aims to characterize the association of metabolic syndrome and its surrogate biomarkers with severity of COVID-19 illness. Methods: This retrospective study included adult patients who tested for COVID-19 at an academic tertiary care institution between March 8, 2020, and May 17, 2020. Metabolic syndrome was defined by the modified World Health Organization criteria. Outcomes of hospitalization, intensive care unit (ICU) admission, and death were analyzed. Results: There were 23,282 patients who tested for COVID-19 and 3679 (15.8%) had a positive result. Of these, metabolic syndrome was present in 834 (39%) of 2139 patients with available data. Patients with metabolic syndrome tended to be older, male, African American, heavier, and with more comorbidities. Metabolic syndrome was associated with higher rates of hospital admission and death (P < 0.001). On multivariable analysis, patients with metabolic syndrome had an increased risk of 77% for hospitalization, 56% for ICU admission, and 81% for death (P < 0.001). High AST:ALT and TG:HDL-C ratios were associated with hospitalization and ICU admission, but not mortality. Conclusions: Patients with metabolic syndrome had significantly worse hospitalization and mortality rates due to COVID-19, even after adjusting for covariates. Targeting obesity, hyperglycemia, dyslipidemia, and hypertension could address modifiable risk factors to reduce mortality due to COVID-19.

Receptor Guanylyl Cyclase C and Cyclic GMP in Health and Disease: Perspectives and Therapeutic Opportunities

Receptor Guanylyl Cyclase C (GC-C) was initially characterized as an important regulator of intestinal fluid and ion homeostasis. Recent findings demonstrate that GC-C is also causally linked to intestinal inflammation, dysbiosis, and tumorigenesis. These advances have been fueled in part by identifying mutations or changes in gene expression in GC-C or its ligands, that disrupt the delicate balance of intracellular cGMP levels and are associated with a wide range of clinical phenotypes. In this review, we highlight aspects of the current knowledge of the GC-C signaling pathway in homeostasis and disease, emphasizing recent advances in the field. The review summarizes extra gastrointestinal functions for GC-C signaling, such as appetite control, energy expenditure, visceral nociception, and behavioral processes. Recent research has expanded the homeostatic role of GC-C and implicated it in regulating the ion-microbiome-immune axis, which acts as a mechanistic driver in inflammatory bowel disease. The development of transgenic and knockout mouse models allowed for in-depth studies of GC-C and its relationship to whole-animal physiology. A deeper understanding of the various aspects of GC-C biology and their relationships with pathologies such as inflammatory bowel disease, colorectal cancer, and obesity can be leveraged to devise novel therapeutics.

Association between metabolic syndrome and mortality in patients with COVID-19: A nationwide cohort study

OBJECTIVES

We investigated the association between metabolic syndrome (MetS) and mortality among coronavirus disease 2019 (COVID-19) patients in Korea.

METHODS

We analyzed 3876 individuals aged ≥ 20 years who were confirmed with COVID-19 from January 1 to June 4, 2020 based on the Korea National Health Insurance Service (NHIS)-COVID-19 database and had undergone health examination by NHIS between 2015 and 2017. Multivariable Cox proportional hazard regression analyses were performed.

RESULTS

Of total participants, the prevalence of MetS was 21.0% (n = 815). During 58.6 days of mean follow-up, 3.1 % (n = 120) of the participants died. Compared to individuals without MetS, COVID-19 patients with MetS had a significantly increased mortality risk after adjusting for confounders in total participants (hazard ratio [HR]: 1.68, 95 % confidence interval [CI]: 1.14-2.47) and women (HR: 2.41, 95 % CI: 1.17-4.96). A low high-density lipoprotein cholesterol level in total participants (HR: 1.63, 95 % CI: 1.12-2.37) and hyperglycemia in women (HR: 1.97, 95 % CI: 1.01-3.84) was associated with higher mortality risk. The mortality risk increased as the number of MetS components increased among total participants and women (P for trend = 0.009 and 0.016, respectively). In addition, MetS groups had higher mortality risk in aged ≥ 60 years (HR: 1.60, 95 % CI: 1.07-2.39), and never-smokers (2.08, 1.21-3.59).

CONCLUSIONS

The presence of MetS and greater number of its components were associated with increased mortality risks particularly in female patients with COVID-19. Managing MetS may contribute to better outcomes of COVID-19.

Incidence and risk factors of acute kidney injury in COVID-19 patients with and without acute respiratory distress syndrome (ARDS) during the first wave of COVID-19: a systematic review and Meta-Analysis

BACKGROUND

Acute kidney injury (AKI) is common among patients with COVID-19. However, AKI incidence may increase when COVID-19 patients develop acute respiratory distress syndrome (ARDS). Thus, this systematic review and meta-analysis aimed to assess the incidence and risk factors of AKI, need for kidney replacement therapy (KRT), and mortality rate among COVID-19 patients with and without ARDS from the first wave of COVID-19.

METHODS

The databases MEDLINE and EMBASE were searched using relevant keywords. Only articles available in English published between December 1, 2019, and November 1, 2020, were included. Studies that included AKI in COVID-19 patients with or without ARDS were included. Meta-analyses were conducted using random-effects models.

RESULTS

Out of 618 studies identified and screened, 31 studies met the inclusion criteria. A total of 27,500 patients with confirmed COVID-19 were included. The overall incidence of AKI in patients with COVID-19 was 26% (95% CI 19% to 33%). The incidence of AKI was significantly higher among COVID-19 patients with ARDS than COVID-19 patients without ARDS (59% vs. 6%, p < 0.001). Comparing ARDS with non-ARDS COVID-19 cohorts, the need for KRT was also higher in ARDS cohorts (20% vs. 1%). The mortality among COVID-19 patients with AKI was significantly higher (Risk ratio = 4.46; 95% CI 3.31-6; p < 0.00001) than patients without AKI.

CONCLUSION

This study shows that ARDS development in COVID-19-patients leads to a higher incidence of AKI and increased mortality rate. Therefore, healthcare providers should be aware of kidney dysfunction, especially among elderly patients with multiple comorbidities. Early kidney function assessment and treatments are vital in COVID-19 patients with ARDS.

Hill CA, Boman K, Deo N, Bansal V, Kumar VK, Walkey AJ, Kashyap R. Metabolic Syndrome and Acute Respiratory Distress Syndrome in Hospitalized Patients With COVID-19

IMPORTANCE

Obesity, diabetes, and hypertension are common comorbidities in patients with severe COVID-19, yet little is known about the risk of acute respiratory distress syndrome (ARDS) or death in patients with COVID-19 and metabolic syndrome.

OBJECTIVE

To determine whether metabolic syndrome is associated with an increased risk of ARDS and death from COVID-19.

DESIGN, SETTING, AND PARTICIPANTS

This multicenter cohort study used data from the Society of Critical Care Medicine Discovery Viral Respiratory Illness Universal Study collected from 181 hospitals across 26 countries from February 15, 2020, to February 18, 2021. Outcomes were compared between patients with metabolic syndrome (defined as ≥3 of the following criteria: obesity, prediabetes or diabetes, hypertension, and dyslipidemia) and a control population without metabolic syndrome. Participants included adult patients hospitalized for COVID-19 during the study period who had a completed discharge status. Data were analyzed from February 22 to October 5, 2021.

EXPOSURES

Exposures were SARS-CoV-2 infection, metabolic syndrome, obesity, prediabetes or diabetes, hypertension, and/or dyslipidemia.

MAIN OUTCOMES AND MEASURES

The primary outcome was in-hospital mortality. Secondary outcomes included ARDS, intensive care unit (ICU) admission, need for invasive mechanical ventilation, and length of stay (LOS).

RESULTS

Among 46 441 patients hospitalized with COVID-19, 29 040 patients (mean [SD] age, 61.2 [17.8] years; 13 059 [45.0%] women and 15713 [54.1%] men; 6797 Black patients [23.4%], 5325 Hispanic patients [18.3%], and 16 507 White patients [57.8%]) met inclusion criteria. A total of 5069 patients (17.5%) with metabolic syndrome were compared with 23 971 control patients (82.5%) without metabolic syndrome. In adjusted analyses, metabolic syndrome was associated with increased risk of ICU admission (adjusted odds ratio [aOR], 1.32 [95% CI, 1.14-1.53]), invasive mechanical ventilation (aOR, 1.45 [95% CI, 1.28-1.65]), ARDS (aOR, 1.36 [95% CI, 1.12-1.66]), and mortality (aOR, 1.19 [95% CI, 1.08-1.31]) and prolonged hospital LOS (median [IQR], 8.0 [4.2-15.8] days vs 6.8 [3.4-13.0] days; P < .001) and ICU LOS (median [IQR], 7.0 [2.8-15.0] days vs 6.4 [2.7-13.0] days; P < .001). Each additional metabolic syndrome criterion was associated with increased risk of ARDS in an additive fashion (1 criterion: 1147 patients with ARDS [10.4%]; P = .83; 2 criteria: 1191 patients with ARDS [15.3%]; P < .001; 3 criteria: 817 patients with ARDS [19.3%]; P < .001; 4 criteria: 203 patients with ARDS [24.3%]; P < .001).

CONCLUSIONS AND RELEVANCE

These findings suggest that metabolic syndrome was associated with increased risks of ARDS and death in patients hospitalized with COVID-19. The association with ARDS was cumulative for each metabolic syndrome criteria present.

Metabolic Syndrome and Its Components in Patients with COVID-19: Severe Acute Respiratory Syndrome (SARS) and Mortality. A Systematic Review and Meta-Analysis

Recent meta-analysis studies have reported that metabolic comorbidities such as diabetes, obesity, dyslipidaemia and hypertension are associated with higher risk of severe acute respiratory syndrome (SARS) and mortality in patients with COVID-19. This meta-analysis aims to investigate the relationship between metabolic syndrome (MetS) and its components with SARS and mortality in COVID-19 patients. Methods: A systematic search was conducted in the several databases up until 1 September 2021. Primary observational longitudinal studies published in peer review journals were selected. Two independent reviewers performed title and abstract screening, extracted data and assessed the risk of bias using the Newcastle–Ottawa Scale. Results: The random effects meta-analysis showed that MetS was significantly associated with SARS with a pooled OR (95% CI) of 3.21 (2.88–3.58) and mortality with a pooled OR (95% CI) of 2.32 (1.16–4.63). According to SARS, the pooled OR for MetS was 2.19 (1.71–2.67), p < 0.001; significantly higher than the hypertension component. With regard to mortality, although the pooled OR for MetS was greater than for its individual components, no significant differences were observed. Conclusions: this meta-analysis of cohort studies, showed that MetS is better associated to SARS and mortality in COVID-19 patients than its individual components.

The association of metabolic syndrome and COVID-19 deterioration

BACKGROUND AND AIMS

To evaluate the prevalence and prognostic value of metabolic syndrome (MetS) in patients admitted for coronavirus disease 2019 (COVID-19).

METHODS AND RESULTS

In this monocentric cohort retrospective study, we consecutively included all adult patients admitted to COVID-19 units between April 9 and May 29, 2020 and between February 1 and March 26, 2021. MetS was defined when at least three of the following components were met: android obesity, high HbA1c, hypertension, hypertriglyceridemia, and low HDL cholesterol. COVID-19 deterioration was defined as the need for nasal oxygen flow ≥6 L/min within 28 days after admission. We included 155 patients (55.5% men, mean age 61.7 years old, mean body mass index 29.8 kg/m²). Fifty-six patients (36.1%) had COVID-19 deterioration. MetS was present in 126 patients (81.3%) and was associated with COVID-19 deterioration (no-MetS vs MetS: 13.7% and 41.2%, respectively, p < 0.01). Logistic regression taking into account MetS, age, gender, ethnicity, period of inclusion, and Charlson Index showed that COVID-19 deterioration was 5.3 times more likely in MetS patients (95% confidence interval 1.3-20.2) than no-MetS patients.

CONCLUSIONS

Over 81.3% of patients hospitalized in COVID-19 units had MetS. This syndrome appears to be an independent risk factor of COVID-19 deterioration.

Prognostic Role of Metabolic Syndrome in COVID-19 Patients: A Systematic Review Meta-Analysis

BACKGROUND

The prevalence and prognostic implications of metabolic syndrome (MetS) in patients infected by the SARS-CoV-2 remain unclear. We performed a systematic review and meta-analysis of prevalence and mortality risk in COVID-19 patients with MetS.

METHODS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed in abstracting data and assessing validity. We searched MEDLINE and Scopus to locate every article published up to 1 September 2021, reporting data on MetS among COVID-19 patients. The pooled prevalence of MetS was calculated using a random effects model and presented using the related 95% confidence interval (CI), while the mortality risk was estimated using the Mantel-Haenszel random effects models with odds ratio (OR) and related 95% CI. Statistical heterogeneity was measured using the Higgins I2 statistic.

RESULTS

Six studies, enrolling 209.569 COVID-19 patients [mean age 57.2 years, 114.188 males (54.4%)] met the inclusion criteria and were included in the final analysis. The pooled prevalence of dyslipidaemia was 20.5% of cases (95% CI: 6.7-47.8%, p = 0.03), with high heterogeneity (I2 = 98.9%). Pre-existing MetS was significantly associated with higher risk of short-term mortality (OR: 2.30, 95% CI: 1.52-3.45, p < 0.001), with high heterogeneity (I2 = 89.4%). Meta-regression showed a direct correlation with male gender (p = 0.03), hypertension (p < 0.001), DM (p = 0.01) and hyperlipidaemia (p = 0.04), but no effect when considering age (p = 0.75) and chronic pulmonary disease (p = 0.86) as moderators.

CONCLUSIONS

MetS represents a major comorbidity in about 20% of COVID-19 patients and it is associated with a 230% increased risk of short-term mortality.

Statins and clinical outcomes in hospitalized COVID-19 patients with and without Diabetes Mellitus: a retrospective cohort study with propensity score matching

BACKGROUND

The pleiotropic effects of statins may reduce the severity of COVID-19 disease. This study aims to determine the association between inpatient statin use and severe disease outcomes among hospitalized COVID-19 patients, especially those with Diabetes Mellitus (DM).

RESEARCH DESIGN AND METHODS

A retrospective cohort study on hospitalized patients with confirmed COVID-19 diagnosis. The primary outcome was mortality during hospitalization. Patients were classified into statin and non-statin groups based on the administration of statins during hospitalization. Analysis included multivariable regression analysis adjusting for confounders and propensity score matching to achieve a 1:1 balanced cohort. Subgroup analyses based on presence of DM were conducted.

RESULTS

In the cohort of 922 patients, 413 had a history of DM. About 27.1% patients (n = 250) in the total cohort (TC) and 32.9% patients (n = 136) in DM cohort received inpatient statins. Atorvastatin (n = 205, 82%) was the most commonly prescribed statin medication in TC. On multivariable analysis in TC, inpatient statin group had reduced mortality compared to the non-statin group (OR, 0.61; 95% CI, 0.42-0.90; p = 0.01). DM modified this association between inpatient statins and mortality. Patients with DM who received inpatient statins had reduced mortality (OR, 0.35; 95% CI, 0.21-0.61; p < 0.001). However, no such association was noted among patients without DM (OR, 1.21; 95% CI, 0.67-2.17; p = 0.52). These results were further validated using propensity score matching.

CONCLUSIONS

Inpatient statin use was associated with significant reduction in mortality among COVID-19 patients especially those with DM. These findings support the pursuit of randomized clinical trials and inpatient statin use appears safe among COVID-19 patients.

Radiographic Hepatic Steatosis Is Not Associated With Key Clinical Outcomes Among Patients Hospitalized With COVID-19

Background

Metabolic syndrome increases adverse outcomes in coronavirus disease 2019 (COVID-19) infection. Hepatic steatosis may increase risk of COVID-19 severity. Current studies evaluating steatosis lack reliable definitions. We aimed to evaluate the association of radiographic hepatic steatosis and clinical outcomes of COVID-19 severity in a diverse cohort.

Methods

We retrospectively identified patients with COVID-19 infection admitted to two US academic hospitals. Outcomes were length of stay, intensive care unit use, mechanical ventilation, and in-hospital mortality. We used Mann-Whitney U-test for continuous measures and Chi-square or Fisher’s exact test for categorical measures. Multivariable linear and logistic regression analyses were used to adjust for confounders.

Results

Of the 319 patients, 14% had hepatic steatosis. There were no differences in length of stay (6 (4 - 16) vs. 9 (4 - 18) days, P = 0.6), intensive care unit (24% vs. 32%, P = 0.3), mechanical ventilation (28% vs. 38%, P = 0.32), or in-hospital mortality (7% vs. 17%, P = 0.12). After adjustment, there was no difference in length of stay (β: -14.37, 95% confidence interval (CI): -30.5 - 1.77, P = 0.08), intensive care unit (odds ratio (OR): 0.31, 95% CI: 0.03 - 1.09, P = 0.06), mechanical ventilation (OR: 0.13, 95% CI: 0.02 - 1.09, P = 0.06), or in-hospital mortality (OR: 0.27, 95% CI: 0.06 - 1.16, P = 0.08) among patients with hepatic steatosis.

Conclusion

Radiographic hepatic steatosis was not associated with worse outcomes among patients hospitalized with COVID-19.

Higher 90-Day Mortality after Surgery for Hip Fractures in Patients with COVID-19: A Case-Control Study from a Single Center in Italy

The mortality of hip fracture (HF) patients is increased by concomitant COVID-19; however, evidence is limited to only short follow-up. A retrospective matched case-control study was designed with the aim to report the 90-day mortality and determine the hazard ratio (HR) of concomitant HF and COVID-19 infection. Cases were patients hospitalized for HF and diagnosed with COVID-19. Controls were patients hospitalized for HF not meeting the criteria for COVID-19 diagnosis and were individually matched with each case through a case-control (1:3) matching algorithm. A total of 89 HF patients were treated during the study period, and 14 of them were diagnosed as COVID-19 positive (overall 15.7%). Patients' demographic, clinical, and surgical characteristics were similar between case and control groups. At 90 days after surgery, 5 deaths were registered among the 14 COVID-19 cases (35.7%) and 4 among the 42 HF controls (9.5%). COVID-19-positive cases had a higher risk of mortality at 30 days (HR = 4.51; p = 0.0490) and 90 days (HR = 4.50; p = 0.025) with respect to controls. Patients with concomitant HF and COVID-19 exhibit high perioperative mortality, which reaches a plateau of nearly 30-35% after 30 to 45 days and is stable up to 90 days. The mortality risk is more than four-fold higher in patients with COVID-19.

Letter to the editor: Vitamin D levels in acute illness and clinical severity in COVID-19 patients

We would like to comment on the recently published article titled: “Circulating Vitamin D levels status and clinical prognostic indices in COVID-19 patients” by Ricci et al. The authors grouped the patients into two groups according to the vitamin D levels measured at the time of admission into the hospital and reported that lower vitamin D levels are associated with elevated D-dimer and IL-6 levels, low CD4/CD8 ratio and compromised clinical findings with elevated LIPI and SOFA scores. However, review of recent literature shows this association to be debatable. The 25-hydroxyvitamin D levels in the initial phase of critical illness have been reported to drop rapidly and hence consideration of the time of measurement from symptom onset would have enhanced the clinical relevance of these findings. Inferred association between vitamin D levels and disease severity based on SOFA score in COVID-19 patients, needs to be further explored in the light of the recent literature which casts doubt on using SOFA score at admission to predict mortality in COVID-19.

Association between antecedent statin use and severe disease outcomes in COVID-19: A retrospective study with propensity score matching

Background

Statins have been associated with a reduction in inflammatory markers and improved endothelial function. Whether statins offer any benefit in COVID-19 needs to be elucidated.

Objective

To determine the association between antecedent statin use and severe disease outcomes among COVID-19 patients.

Methods

A retrospective cohort study on 1014 patients with confirmed COVID-19 diagnosis. Outcomes were mortality, need for mechanical ventilation, and intensive care admission. Patients were classified into statin-users vs statin non-users based on antecedent use of statins. Multivariable regression analysis was performed adjusting for confounders such as age, sex, race, BMI, smoking, insurance, and comorbidities. Propensity score matching was performed to achieve a 1:1 balanced cohort.

Results

A total of 1014 patients (Median age 65 (IQR 53–73); 530 (52.3%) males; 753 (74.3%) African Americans; median BMI 29.4 (IQR 25.1–35.9); 615 (60.7%) with Medicare insurance) were included in the study. About 454 patients (44.77%) were using statins as home medication. Antecedent statin use was associated with significant decrease in mortality in the total cohort (OR, 0.66; 95% CI, 0.46 – 0.95; p = 0.03). Among the propensity score matched (PSM) cohort of 466 patients (233 statin users and 233 statin non-users), all the baseline characteristics had similar distribution among the two groups. Statin users had significant reduction in mortality in the PSM cohort as well (OR, 0.56; 95% CI, 0.37 – 0.83; p = 0.004).

Conclusions

Statin use was associated with significant reduction in mortality among COVID-19 patients. These findings support the pursuit of randomized clinical trials to explore the possible benefits of statins in COVID-19.

Metabolic syndrome and clinical outcomes in patients infected with COVID-19: Does age, sex, and race of the patient with metabolic syndrome matter?

BACKGROUND

Metabolic syndrome (MetS) is highly prevalent worldwide, and its individual components obesity, diabetes, and hypertension have been identified as risk factors to develop severe coronavirus disease 2019 (COVID-19); however, data on MetS and clinical outcomes in COVID-19 are scarce. This study aims to determine association between MetS and severe disease outcomes, that is, mortality, need for mechanical ventilation, and intensive care unit (ICU) requirement among patients with COVID-19.

METHODS

This is a retrospective multihospital cohort study on 1871 patients with confirmed COVID-19 diagnosis. Patient data including demographics, comorbidities, body mass index (BMI), smoking, laboratory data, and the clinical course of hospitalization were collected. Multivariable regression was performed adjusting for age, sex, race, insurance, smoking, and comorbidities.

RESULTS

A total of 1871 patients (median age 66 [interquartile range, IQR 54-75]; 965 (51.6%) males; 1494 (80%) African Americans; median BMI 29.4 kg/m2 [IQR 25-35.8]; 573 (30.6%) patients with MetS) were included. Patients with MetS had increased mortality (odds ratio [OR], 1.40; 95% CI, 1.11-1.75; P = .004), higher ICU admission (OR, 1.68; 95% CI, 1.36-2.08; P < .001), and increased need for mechanical ventilation (OR, 1.90; 95% CI, 1.52-2.37; P < .001). Among individual comorbidities, diabetes had significant association with mortality (OR, 1.30; 95% CI, 1.05-1.63; P = 0.02), ICU admission (OR, 1.56; 95% CI, 1.27-1.93; P < .001), and need for mechanical ventilation (OR, 1.63; 95% CI, 1.30-2.03; P < .001).

CONCLUSIONS

MetS is a better prognostic indicator for severe disease outcomes in patients with COVID-19 than its individual components. Patients with MetS had significantly higher mortality, increased ICU admissions, and need for mechanical ventilation.