Risks and burdens of incident diabetes in long COVID: a cohort study

Structural basis of rosmarinic acid inhibitory mechanism on SARS-CoV-2 main protease

The SARS-CoV-2 coronavirus is characterized by high mutation rates and significant infectivity, posing ongoing challenges for therapeutic intervention. To address potential challenges in the future, the continued development of effective drugs targeting SARS-CoV-2 remains an important task for the scientific as well as the pharmaceutical community. The main protease (Mpro) of SARS-CoV-2 is an ideal therapeutic target for COVID-19 drug development, leading to the introduction of various inhibitors, both covalent and non-covalent, each characterized by unique mechanisms of action and possessing inherent strengths and limitations. Natural products, being compounds naturally present in the environment, offer advantages such as low toxicity and diverse activities, presenting a viable source for antiviral drug development. Here, we identified a natural compound, rosmarinic acid, which exhibits significant inhibitory effects on the Mpro of the SARS-CoV-2. Through detailed structural biology analysis, we elucidated the precise crystal structure of the complex formed between rosmarinic acid and SARS-CoV-2 Mpro, revealing the molecular basis of its inhibitory mechanism. These findings not only enhance our understanding of the antiviral action of rosmarinic acid, but also provide valuable structural information and mechanistic insights for the further development of therapeutic strategies against SARS-CoV-2.

Long COVID as a disease of accelerated biological aging: An opportunity to translate geroscience interventions

It has been four years since long COVID-the protracted consequences that survivors of COVID-19 face-was first described. Yet, this entity continues to devastate the quality of life of an increasing number of COVID-19 survivors without any approved therapy and a paucity of clinical trials addressing its biological root causes. Notably, many of the symptoms of long COVID are typically seen with advancing age. Leveraging this similarity, we posit that Geroscience-which aims to target the biological drivers of aging to prevent age-associated conditions as a group-could offer promising therapeutic avenues for long COVID. Bearing this in mind, this review presents a translational framework for studying long COVID as a state of effectively accelerated biological aging, identifying research gaps and offering recommendations for future preclinical and clinical studies.

Incidence of diabetes after SARS-CoV-2 infection in England and the implications of COVID-19 vaccination: a retrospective cohort study of 16 million people

BACKGROUND

Some studies have shown that the incidence of type 2 diabetes increases after a diagnosis of COVID-19, although the evidence is not conclusive. However, the effects of the COVID-19 vaccine on this association, or the effect on other diabetes subtypes, are not clear. We aimed to investigate the association between COVID-19 and incidence of type 2, type 1, gestational and non-specific diabetes, and the effect of COVID- 19 vaccination, up to 52 weeks after diagnosis.

METHODS

In this retrospective cohort study, we investigated the diagnoses of incident diabetes following COVID-19 diagnosis in England in a pre-vaccination, vaccinated, and unvaccinated cohort using linked electronic health records. People alive and aged between 18 years and 110 years, registered with a general practitioner for at least 6 months before baseline, and with available data for sex, region, and area deprivation were included. Those with a previous COVID-19 diagnosis were excluded. We estimated adjusted hazard ratios (aHRs) comparing diabetes incidence after COVID-19 diagnosis with diabetes incidence before or in the absence of COVID-19 up to 102 weeks after diagnosis. Results were stratified by COVID-19 severity (categorised as hospitalised or non-hospitalised) and diabetes type.

FINDINGS

16 669 943 people were included in the pre-vaccination cohort (Jan 1, 2020-Dec 14, 2021), 12 279 669 in the vaccinated cohort, and 3 076 953 in the unvaccinated cohort (both June 1-Dec 14, 2021). In the pre-vaccination cohort, aHRs for the incidence of type 2 diabetes after COVID-19 (compared with before or in the absence of diagnosis) declined from 4·30 (95% CI 4·06-4·55) in weeks 1-4 to 1·24 (1·14-1.35) in weeks 53-102. aHRs were higher in unvaccinated people (8·76 [7·49-10·25]) than in vaccinated people (1·66 [1·50-1·84]) in weeks 1-4 and in patients hospitalised with COVID-19 (pre-vaccination cohort 28·3 [26·2-30·5]) in weeks 1-4 declining to 2·04 [1·72-2·42] in weeks 53-102) than in those who were not hospitalised (1·95 [1·78-2·13] in weeks 1-4 declining to 1·11 [1·01-1·22] in weeks 53-102). Type 2 diabetes persisted for 4 months after COVID-19 in around 60% of those diagnosed. Patterns were similar for type 1 diabetes, although excess incidence did not persist beyond 1 year after a COVID-19 diagnosis.

INTERPRETATION

Elevated incidence of type 2 diabetes after COVID-19 is greater, and persists for longer, in people who were hospitalised with COVID-19 than in those who were not, and is markedly less apparent in people who have been vaccinated against COVID-19. Testing for type 2 diabetes after severe COVID-19 and the promotion of vaccination are important tools in addressing this public health problem.

FUNDING

UK National Institute for Health and Care Research, UK Research and Innovation (UKRI) Medical Research Council, UKRI Engineering and Physical Sciences Research Council, Health Data Research UK, Diabetes UK, British Heart Foundation, and the Stroke Association.

High Prevalence of Diabetes Among Hospitalized COVID-19 Minority Patients: Data from a Single Tertiary Hospital

BACKGROUND AND AIM

Type 2 diabetes mellitus (DM) is a common comorbidity in the minority population and is associated with poor outcomes in COVID-19 patients. We hypothesized that COVID-19 patients with pre-existing diabetes mellitus are prone to fatal outcomes compared to non-diabetic patients. We aimed to illustrate the characteristics and outcomes and identify the risk factors for in-hospital mortality of COVID-19 patients with DM.

METHODS

In this single-center retrospective study, electronic medical records of hospitalized patients with confirmed COVID-19 diagnosis at Howard University Hospital (HUH) from March 2020 to Dec 2021 were analyzed. Clinical, demographic, and serological information, as well as outcomes, were recorded and analyzed.

RESULTS

Among 463 COVID-19 patients, 66.3% (n = 307) were African Americans (AA) and 35.9% (n = 166) had diabetes, with a mean age of 64 years. The majority of the diabetic patients were AA (n = 123, 74.1%) and had a higher mortality rate (n = 26, 74.3%) compared to others. Length of stay in the hospital is significantly more for the diabetic than for the non-diabetic patients (11.3 vs. 8.3 days, p = 0.03). A higher proportion of ICU admission (32.3% vs. 17.9%, p =  < 0.001), intubation (17% vs. 11.7%, p = 0.04), and increased mortality (21.1% vs. 12.2%, p = 0.01) were identified in COVID-19 patients with DM than in those with no DM. Among DM patients, non-survivors were older (69.9 vs. 62.9 years). DM patients were more likely to have underlying hypertension (72.3% vs. 43.3%, p =  < 0.001), obesity (44.8% vs. 32.1%, p = 0.007), chronic kidney disease (23.6 vs. 11.8%, p = 0.001), and cardiovascular disease (29.5% vs. 14.3%, p = 0.001) than the non-DM patients. HbA1C above 9%, indicating poorly controlled hyperglycemia, was associated with poor outcome among the DM subjects. AST (23.5% vs. 31.3%) and creatinine (61.4% vs. 37.9%) were significantly more elevated in DM COVID-19 patients (all p-values < 0.05). The levels of serum troponin (42.5% vs. 30.9%, p = 0.03), interleukin-6 (67.2 vs. 50%, p = 0.04), ferritin (65.6% vs. 44.6%, p = 0.03), procalcitonin (58.1% vs. 46.1, p = 0.03), and D-dimers (92.8% vs. 86.5%, p = 0.04) were significantly higher in DM patients as compared to those in non-DM COVID-19 patients, indicating more susceptibility of diabetic COVID-19 patients to coagulation dysfunction and inflammatory storm.

CONCLUSION

The prevalence of DM is high among hospitalized COVID-19 patients in our cohort. While DM patients have a higher mortality rate and ICU admission than non-DM patients, other factors such as underlying comorbidities, old age, elevated creatinine, AST, serum inflammatory markers, and D-dimer are more significant predictors of fatal outcomes. DM patients had higher metabolic derangements, hypercoagulability, and severe inflammatory response. No significant difference of outcome was noted between DM patients of different races in our cohort. In the diabetic group, it appears that race may not significantly contribute to the observed mortality disparity. This could be attributed to the significant influence of diabetes, which acts as a major effector, potentially overshadowing the significance of race in this context.

The effect of long-term COVID-19 infection on maternal and fetal complications: a retrospective cohort study conducted at a single center in China

Investigate the effect of long-term COVID-19 on maternal and fetal complications. A retrospective cohort study was conducted. A total of 623 pregnant women who delivered in Kunming First People's Hospital from November 1, 2022 to July 31, 2023 were selected. By employing statistical methods, we compared the associations between maternal and fetal complications in pregnant women with acute COVID-19 during pregnancy, long-term COVID-19, and non-COVID-19 pregnant women. In the final 623 samples, there were 209 pregnant women with acute COVID-19, 72 pregnant women with long-term COVID-19, and 342 pregnant women without COVID-19. The epidemiological and clinical characteristics of all subjects were similar. Pregnant individuals who developed long-term COVID-19 during their pregnancy had an increased risk of experiencing gestational hypertension (OR 3.344, 95% CI 1.544-7.243), gestational diabetes mellitus (OR 2.301, 95% CI 1.290-4.102), and fetal intrauterine growth restriction (OR 2.817, 95% CI 1.385-5.952). Multivariate binary logistic regression analysis showed that this association remained consistent even after adjusting for confounders and performing subgroup analyses. Other maternal and fetal complications, such as premature rupture of membranes, preterm delivery, neonatal asphyxia, and transfer of neonates to NICU, did not exhibit statistically significant associations. After linear regression analysis, the platelet count (β: - 0.127, 95% CI - 0.001-0.000) of pregnant women with long-term COVID-19 was slightly lower than that of non-COVID-19 pregnant women, and the other coagulation parameters were not statistically significant. The incidence of gestational hypertension, gestational diabetes mellitus and fetal intrauterine growth restriction in pregnant women with long-term COVID-19 is significantly increased, but it does not further increase the coagulation status.

From bench to bedside: potential of translational research in COVID-19 and beyond

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease 2019 (COVID-19) have been around for more than 3 years now. However, due to constant viral evolution, novel variants are emerging, leaving old treatment protocols redundant. As treatment options dwindle, infection rates continue to rise and seasonal infection surges become progressively common across the world, rapid solutions are required. With genomic and proteomic methods generating enormous amounts of data to expand our understanding of SARS-CoV-2 biology, there is an urgent requirement for the development of novel therapeutic methods that can allow translational research to flourish. In this review, we highlight the current state of COVID-19 in the world and the effects of post-infection sequelae. We present the contribution of translational research in COVID-19, with various current and novel therapeutic approaches, including antivirals, monoclonal antibodies and vaccines, as well as alternate treatment methods such as immunomodulators, currently being studied and reiterate the importance of translational research in the development of various strategies to contain COVID-19.

Postacute Sequelae of SARS-CoV-2 Infection in the Pre-Delta, Delta, and Omicron Eras

BACKGROUND

Postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) can affect many organ systems. However, temporal changes during the coronavirus disease 2019 (Covid-19) pandemic, including the evolution of SARS-CoV-2, may have affected the risk and burden of PASC. Whether the risk and burden of PASC have changed over the course of the pandemic is unclear.

METHODS

We used health records of the Department of Veterans Affairs to build a study population of 441,583 veterans with SARS-CoV-2 infection between March 1, 2020, and January 31, 2022, and 4,748,504 noninfected contemporaneous controls. We estimated the cumulative incidence of PASC at 1 year after SARS-CoV-2 infection during the pre-delta, delta, and omicron eras of the Covid-19 pandemic.

RESULTS

Among unvaccinated persons infected with SARS-CoV-2, the cumulative incidence of PASC during the first year after infection was 10.42 events per 100 persons (95% confidence interval [CI], 10.22 to 10.64) in the pre-delta era, 9.51 events per 100 persons (95% CI, 9.26 to 9.75) in the delta era, and 7.76 events per 100 persons (95% CI, 7.57 to 7.98) in the omicron era (difference between the omicron and pre-delta eras, -2.66 events per 100 persons [95% CI, -2.93 to -2.36]; difference between the omicron and delta eras, -1.75 events per 100 persons [95% CI, -2.08 to -1.42]). Among vaccinated persons, the cumulative incidence of PASC at 1 year was 5.34 events per 100 persons (95% CI, 5.10 to 5.58) during the delta era and 3.50 events per 100 persons (95% CI, 3.31 to 3.71) during the omicron era (difference between the omicron and delta eras, -1.83 events per 100 persons; 95% CI, -2.14 to -1.52). Vaccinated persons had a lower cumulative incidence of PASC at 1 year than unvaccinated persons (difference during the delta era, -4.18 events per 100 persons [95% CI, -4.47 to -3.88]; difference during the omicron era, -4.26 events per 100 persons [95% CI, -4.49 to -4.05]). Decomposition analyses showed 5.23 (95% CI, 4.97 to 5.47) fewer PASC events per 100 persons at 1 year during the omicron era than during the pre-delta and delta eras combined; 28.11% of the decrease (95% CI, 25.57 to 30.50) was attributable to era-related effects (changes in the virus and other temporal effects), and 71.89% (95% CI, 69.50 to 74.43) was attributable to vaccines.

CONCLUSIONS

The cumulative incidence of PASC during the first year after SARS-CoV-2 infection decreased over the course of the pandemic, but the risk of PASC remained substantial even among vaccinated persons who had SARS-CoV-2 infection in the omicron era. (Supported by the Department of Veterans Affairs.).

Identification of risk factors of Long COVID and predictive modeling in the RECOVER EHR cohorts

BACKGROUND

SARS-CoV-2-infected patients may develop new conditions in the period after the acute infection. These conditions, the post-acute sequelae of SARS-CoV-2 infection (PASC, or Long COVID), involve a diverse set of organ systems. Limited studies have investigated the predictability of Long COVID development and its associated risk factors.

METHODS

In this retrospective cohort study, we used electronic healthcare records from two large-scale PCORnet clinical research networks, INSIGHT (~1.4 million patients from New York) and OneFlorida+ (~0.7 million patients from Florida), to identify factors associated with having Long COVID, and to develop machine learning-based models for predicting Long COVID development. Both SARS-CoV-2-infected and non-infected adults were analysed during the period of March 2020 to November 2021. Factors associated with Long COVID risk were identified by removing background associations and correcting for multiple tests.

RESULTS

We observed complex association patterns between baseline factors and a variety of Long COVID conditions, and we highlight that severe acute SARS-CoV-2 infection, being underweight, and having baseline comorbidities (e.g., cancer and cirrhosis) are likely associated with increased risk of developing Long COVID. Several Long COVID conditions, e.g., dementia, malnutrition, chronic obstructive pulmonary disease, heart failure, PASC diagnosis U099, and acute kidney failure are well predicted (C-index > 0.8). Moderately predictable conditions include atelectasis, pulmonary embolism, diabetes, pulmonary fibrosis, and thromboembolic disease (C-index 0.7-0.8). Less predictable conditions include fatigue, anxiety, sleep disorders, and depression (C-index around 0.6).

CONCLUSIONS

This observational study suggests that association patterns between investigated factors and Long COVID are complex, and the predictability of different Long COVID conditions varies. However, machine learning-based predictive models can help in identifying patients who are at risk of developing a variety of Long COVID conditions.

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.

MENSA, a Media Enriched with Newly Synthesized Antibodies, to Identify SARS-CoV-2 Persistence and Latent Viral Reactivation in Long-COVID

Post-acute sequelae of SARS-CoV-2 (SARS2) infection (PASC) is a heterogeneous condition, but the main viral drivers are unknown. Here, we use MENSA, Media Enriched with Newly Synthesized Antibodies, secreted exclusively from circulating human plasmablasts, to provide an immune snapshot that defines the underlying viral triggers. We provide proof-of-concept testing that the MENSA technology can capture the new host immune response to accurately diagnose acute primary and breakthrough infections when known SARS2 virus or proteins are present. It is also positive after vaccination when spike proteins elicit an acute immune response. Applying the same principles for long-COVID patients, MENSA is positive for SARS2 in 40% of PASC vs none of the COVID recovered (CR) patients without any sequelae demonstrating ongoing SARS2 viral inflammation only in PASC. Additionally, in PASC patients, MENSAs are also positive for Epstein-Barr Virus (EBV) in 37%, Human Cytomegalovirus (CMV) in 23%, and herpes simplex virus 2 (HSV2) in 15% compared to 17%, 4%, and 4% in CR controls respectively. Combined, a total of 60% of PASC patients have a positive MENSA for SARS2, EBV, CMV, and/or HSV2. MENSA offers a unique antibody snapshot to reveal the underlying viral drivers in long-COVID thus demonstrating the persistence of SARS2 and reactivation of viral herpes in 60% of PASC patients.

Diabetes Following COVID-19 Infection: Is It Common?

New-onset diabetes mellitus following COVID-19 infection has been frequently reported. This article will review the evidence that supports this observation and provide an opinion about its validity and relevance to insured cohorts.

Diabetes and infection: review of the epidemiology, mechanisms and principles of treatment

An association between diabetes and infection has been recognised for many years, with infection being an important cause of death and morbidity in people with diabetes. The COVID-19 pandemic has re-kindled an interest in the complex relationship between diabetes and infection. Some infections occur almost exclusively in people with diabetes, often with high mortality rates without early diagnosis and treatment. However, more commonly, diabetes is a complicating factor in many infections. A reciprocal relationship occurs whereby certain infections and their treatments may also increase the risk of diabetes. People with diabetes have a 1.5- to 4-fold increased risk of infection. The risks are the most pronounced for kidney infection, osteomyelitis and foot infection, but are also increased for pneumonia, influenza, tuberculosis, skin infection and general sepsis. Outcomes from infection are worse in people with diabetes, with the most notable example being a twofold higher rate of death from COVID-19. Hyperglycaemia has deleterious effects on the immune response. Vascular insufficiency and neuropathy, together with altered skin, mucosal and gut microbial colonisation, contribute to the increased risk of infection. Vaccination is important in people with diabetes although the efficacy of certain immunisations may be compromised, particularly in the presence of hyperglycaemia. The principles of treatment largely follow those of the general population with certain notable exceptions.

Virus-induced diabetes mellitus: revisiting infection etiology in light of SARS-CoV-2

Diabetes mellitus (DM) is comprised of two predominant subtypes: type 1 diabetes mellitus (T1DM), accounting for approximately 5 % of cases worldwide and resulting from autoimmune destruction of insulin-producing β-cells, and type 2 (T2DM), accounting for approximately 95 % of cases globally and characterized by the inability of pancreatic β-cells to meet the demand for insulin due to a relative β-cell deficit in the setting of peripheral insulin resistance. Both types of DM involve derangement of glucose metabolism and are metabolic diseases generally considered to be initiated by a combination of genetic and environmental factors. Viruses have been reported to play a role as infectious etiological factors in the initiation of both types of DM in predisposed individuals. Among the reported viral infections causing DM in humans, the most studied include coxsackie B virus, cytomegalovirus and hepatitis C virus. The recent COVID-19 pandemic has highlighted the diabetogenic potential of SARS-CoV-2, rekindling interest in the field of virus-induced diabetes (VID). This review discusses the reported mechanisms of viral-induced DM, addressing emerging concepts in VID, as well as highlighting areas where knowledge is lacking, and further investigation is warranted.

Prevalence of Post-COVID conditions among Mexican COVID-19 survivors: a nationwide cross-sectional study

BACKGROUND

There are limited population-representative data that describe the potential burden of Post-COVID conditions (PCC) in Mexico. We estimated the prevalence of PCC overall and by sociodemographic characteristics among a representative sample of adults previously diagnosed with COVID-19 in Mexico. We additionally, characterized the PCC symptoms, and estimated the association between diagnosed type-2 diabetes and hypertension with PCC.

METHODS

We used data from the 2021 National Health and Nutrition Survey in Mexico, a nationally and regionally representative survey, from August 1st to October 31st, 2021. Using the WHO definition, we estimated the prevalence of PCC by sociodemographics and prevalence of PCC symptoms. We fit multivariable log-binomial regression models to estimate the associations.

RESULTS

The prevalence of PCC was 37.0%. The most common persistent symptoms were fatigue (56.8%), myalgia or arthralgia (47.5%), respiratory distress and dyspnea (42.7%), headache (34.0%), and cough (25.7%). The prevalence was higher in older people, women, and individuals with low socioeconomic status. There was no significant association between hypertension and PCC or diabetes and PCC prevalence.

CONCLUSIONS

About one-third of the adult Mexican population who had COVID-19 in 2021 had Post-COVID conditions. Our population-based estimates can help assess potential priorities for PCC-related health services, which is critical in light of our weak health system and limited funding.

DYNamic assessment of multi-organ level dysfunction in patients recovering from COVID-19: DYNAMO COVID-19

We evaluated the impacts of COVID-19 on multi-organ and metabolic function in patients following severe hospitalised infection compared to controls. Patients (n = 21) without previous diabetes, cardiovascular or cerebrovascular disease were recruited 5-7 months post-discharge alongside controls (n = 10) with similar age, sex and body mass. Perceived fatigue was estimated (Fatigue Severity Scale) and the following were conducted: oral glucose tolerance (OGTT) alongside whole-body fuel oxidation, validated magnetic resonance imaging and spectroscopy during resting and supine controlled exercise, dual-energy X-ray absorptiometry, short physical performance battery (SPPB), intra-muscular electromyography, quadriceps strength and fatigability, and daily step-count. There was a greater insulin response (incremental area under the curve, median (inter-quartile range)) during the OGTT in patients [18,289 (12,497-27,448) mIU/min/L] versus controls [8655 (7948-11,040) mIU/min/L], P < 0.001. Blood glucose response and fasting and post-prandial fuel oxidation rates were not different. This greater insulin resistance was not explained by differences in systemic inflammation or whole-body/regional adiposity, but step-count (P = 0.07) and SPPB scores (P = 0.004) were lower in patients. Liver volume was 28% greater in patients than controls, and fat fraction adjusted liver T1, a measure of inflammation, was raised in patients. Patients displayed greater perceived fatigue scores, though leg muscle volume, strength, force-loss, motor unit properties and post-exercise muscle phosphocreatine resynthesis were comparable. Further, cardiac and cerebral architecture and function (at rest and on exercise) were not different. In this cross-sectional study, individuals without known previous morbidity who survived severe COVID-19 exhibited greater insulin resistance, pointing to a need for physical function intervention in recovery.

The relationship between SARS-CoV-2 infection and type 1 diabetes mellitus

Environmental factors, in particular viral infections, are thought to have an important role in the pathogenesis of type 1 diabetes mellitus (T1DM). The COVID-19 pandemic reinforced this hypothesis as many observational studies and meta-analyses reported a notable increase in the incidence of T1DM following infection with SARS-CoV-2 as well as an association between SARS-CoV-2 infection and the risk of new-onset T1DM. Experimental evidence suggests that human β-cells express SARS-CoV-2 receptors and that SARS-CoV-2 can infect and replicate in β-cells, resulting in structural or functional alterations of these cells. These alterations include reduced numbers of insulin-secreting granules, impaired pro-insulin (or insulin) secretion, and β-cell transdifferentiation or dedifferentiation. The inflammatory environment induced by local or systemic SARS-CoV-2 infection might result in a set of signals (such as pro-inflammatory cytokines) that lead to β-cell alteration or apoptosis or to a bystander activation of T cells and disruption of peripheral tolerance that triggers autoimmunity. Other mechanisms, such as viral persistence, molecular mimicry and activation of endogenous human retroviruses, are also likely to be involved in the pathogenesis of T1DM following SARS-CoV-2 infection. This Review addresses the issue of the involvement of SARS-CoV-2 infection in the development of T1DM using evidence from epidemiological, clinical and experimental studies.

Community-Based View on Diagnostic Imaging at the End of COVID-19 Pandemic: Online Survey-Assisted Study

(1) Background: An online survey-based observational cross-sectional study aimed at elucidating the experience and attitudes of an unstructured population regarding diagnostic imaging. (2) Methods: Invitations to participate were distributed using mixed-mode design to deidentified residents aged 18 years and older. Main outcome measures included morbidity structure and incidence of diagnostic imaging administrations. (3) Results: Respondents (n = 1069) aged 44.3 ± 14.4 years; 32.8% suffered from cardiovascular diseases (CVD); 9.5% had chronic respiratory pathology; 28.9% considered themselves healthy. Respondents with COVID-19 history (49.7%) reported higher rates of computed tomography (CT) (p < 0.0001), magnetic resonance imaging (MRI) (p < 0.001), and ultrasound (p < 0.05). COVID-19 history in CVD respondents shifted imaging administrations towards CT and MRI (p < 0.05). Every tenth respondent received MRI, CT, and ultrasound on a paid basis; 29.0% could not pay for diagnostic procedures; 13.1% reported unavailable MRI. Professional status significantly affected the pattern of diagnostic modalities (p < 0.05). MRI and CT availability differed between respondents in urban and rural areas (p < 0.0001). History of technogenic events predisposed responders to overestimate diagnostic value of fluorography (p < 0.05). (4) Conclusions: Preparedness to future pandemics requires the development of community-based outreach programs focusing on people's awareness regarding medical imaging safety and diagnostic value.

New insights into the pathogenesis of SARS-CoV-2 during and after the COVID-19 pandemic

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the respiratory distress condition known as COVID-19. This disease broadly affects several physiological systems, including the gastrointestinal, renal, and central nervous (CNS) systems, significantly influencing the patient's overall quality of life. Additionally, numerous risk factors have been suggested, including gender, body weight, age, metabolic status, renal health, preexisting cardiomyopathies, and inflammatory conditions. Despite advances in understanding the genome and pathophysiological ramifications of COVID-19, its precise origins remain elusive. SARS-CoV-2 interacts with a receptor-binding domain within angiotensin-converting enzyme 2 (ACE2). This receptor is expressed in various organs of different species, including humans, with different abundance. Although COVID-19 has multiorgan manifestations, the main pathologies occur in the lung, including pulmonary fibrosis, respiratory failure, pulmonary embolism, and secondary bacterial pneumonia. In the post-COVID-19 period, different sequelae may occur, which may have various causes, including the direct action of the virus, alteration of the immune response, and metabolic alterations during infection, among others. Recognizing the serious adverse health effects associated with COVID-19, it becomes imperative to comprehensively elucidate and discuss the existing evidence surrounding this viral infection, including those related to the pathophysiological effects of the disease and the subsequent consequences. This review aims to contribute to a comprehensive understanding of the impact of COVID-19 and its long-term effects on human health.

Prevalence and Incidence of Medication-Treated Diabetes and Pattern of Glucose-Lowering Treatment During the COVID-19 Pandemic: Real-World Data from the Electronic Greek Prescription Database

OBJECTIVES

This study aimed to investigate the prevalence and incidence of medication-treated diabetes mellitus and the evolving patterns of glucose-lowering treatments the year before and during the first two years of the coronavirus disease 2019 (COVID-19) pandemic.

METHODS

Data from the Greek electronic prescription database were analyzed for 2019, 2020, and 2021. The study population included individuals with active social security numbers. Prevalence and incidence rates were calculated based on the dispensing of glucose-lowering medications according to their unique anatomical therapeutic chemical (ATC) code.

RESULTS

The study population comprised 10,289,140 individuals in 2019, 10,630,726 in 2020, and 11,246,136 in 2021. Diabetes prevalence rates were 8.06%, 6.89%, and 7.91%, and incidence rates were 16.8/1000, 8.6/1000, and 13.4/1000 individuals, respectively. Metformin was the most prescribed medication, and newer classes, like sodium-glucose cotransporter-2 inhibitors 2 (SGLT-2) inhibitors and glucagon like peptide-1 (GLP-1) receptor agonists exhibited increasing trends.

CONCLUSIONS

The study identified a decrease in medication-prescribed diabetes prevalence and incidence during the initial year of the COVID-19 pandemic, attributed to healthcare access restrictions. Subsequently, figures returned close to baseline levels. Glucose-lowering medication trends reflected adherence to local and international guidelines, with metformin as the cornerstone, and increasing preference for newer classes such as GLP-1 receptor agonists and SGLT-2 inhibitors.

Risk factors for severe COVID-19 disease increase SARS-CoV-2 infectivity of endothelial cells and pericytes

Coronavirus disease 2019 (COVID-19) was initially considered a primarily respiratory disease but is now known to affect other organs including the heart and brain. A major route by which COVID-19 impacts different organs is via the vascular system. We studied the impact of apolipoprotein E (APOE) genotype and inflammation on vascular infectivity by pseudo-typed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viruses in mouse and human cultured endothelial cells and pericytes. Possessing the APOE4 allele or having existing systemic inflammation is known to enhance the severity of COVID-19. Using targeted replacement human APOE3 and APOE4 mice and inflammation induced by bacterial lipopolysaccharide (LPS), we investigated infection by SARS-CoV-2. Here, we show that infectivity was higher in murine cerebrovascular pericytes compared to endothelial cells and higher in cultures expressing APOE4. Furthermore, increasing the inflammatory state of the cells by prior incubation with LPS increased infectivity into human and mouse pericytes and human endothelial cells. Our findings provide insights into the mechanisms underlying severe COVID-19 infection, highlighting how risk factors such as APOE4 genotype and prior inflammation may exacerbate disease severity by augmenting the virus's ability to infect vascular cells.

Risk of Incident Thyroid Dysfunction in the Post-Acute Phase of COVID-19: A Population-Based Cohort Study in Hong Kong

OBJECTIVE

The evidence of thyroid dysfunction in the post-acute phase of SARS-CoV-2 infection is limited. This study aimed to evaluate the risk of incident thyroid dysfunction in the post-acute phase of COVID-19.

METHODS

This retrospective, propensity-score matched, population-based study included COVID-19 patients and non-COVID-19 individuals between January 2020 and March 2022, identified from the electronic medical records of the Hong Kong Hospital Authority. The cohort was followed up until the occurrence of outcomes, death, or 31 January 2023, whichever came first. Patients with COVID-19 were 1:1 matched to controls based on various variables. The primary outcome was a composite of thyroid dysfunction (hyperthyroidism, hypothyroidism, initiation of antithyroid drug or levothyroxine, and thyroiditis). Cox regression was employed to evaluate the risk of incident thyroid dysfunction during the post-acute phase.

RESULTS

A total of 84 034 COVID-19 survivors and 84 034 matched controls were identified. Upon a median follow-up of 303 days, there was no significant increase in the risk of diagnosed thyroid dysfunction in the post-acute phase of COVID-19 (hazard ratio [HR] 1.058, 95% confidence interval 0.979-1.144, P = .154). Regarding the secondary outcomes, patients with COVID-19 did not have increased risk of hyperthyroidism (HR 1.061, P = .345), hypothyroidism (HR 1.062, P = .255), initiation of antithyroid drug (HR 1.302, P = .070), initiation of levothyroxine (HR 1.086, P = .426), or thyroiditis (P = .252). Subgroup and sensitivity analyses were largely consistent with the main analyses.

CONCLUSION

Our population-based cohort study provided important reassuring data that COVID-19 was unlikely to be associated with persistent effects on thyroid function.

Three-year outcomes of post-acute sequelae of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes post-acute sequelae of coronavirus disease 2019 (COVID-19) (PASC) in many organ systems. Risks of these sequelae have been characterized up to 2 years after infection, but longer-term follow-up is limited. Here we built a cohort of 135,161 people with SARS-CoV-2 infection and 5,206,835 controls from the US Department of Veterans Affairs who were followed for 3 years to estimate risks of death and PASC. Among non-hospitalized individuals, the increased risk of death was no longer present after the first year of infection, and risk of incident PASC declined over the 3 years but still contributed 9.6 (95% confidence interval (CI): 0.4-18.7) disability-adjusted life years (DALYs) per 1,000 persons in the third year. Among hospitalized individuals, risk of death declined but remained significantly elevated in the third year after infection (incidence rate ratio: 1.29 (95% CI: 1.19-1.40)). Risk of incident PASC declined over the 3 years, but substantial residual risk remained in the third year, leading to 90.0 (95% CI: 55.2-124.8) DALYs per 1,000 persons. Altogether, our findings show reduction of risks over time, but the burden of mortality and health loss remains in the third year among hospitalized individuals.

Challenges of mesenchymal stem cells in the clinical treatment of COVID-19

The 2019 coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has brought an enormous public health burden to the global society. The duration of the epidemic, the number of infected people, and the widespread of the epidemic are extremely rare in modern society. In the initial stage of infection, people generally show fever, cough, and dyspnea, which can lead to pneumonia, acute respiratory syndrome, kidney failure, and even death in severe cases. The strong infectivity and pathogenicity of SARS-CoV-2 make it more urgent to find an effective treatment. Mesenchymal stem cells (MSCs) are a kind of pluripotent stem cells with the potential for self-renewal and multi-directional differentiation. They are widely used in clinical experiments because of their low immunogenicity and immunomodulatory function. Mesenchymal stem cell-derived exosomes (MSC-Exo) can play a physiological role similar to that of stem cells. Since the COVID-19 pandemic, a series of clinical trials based on MSC therapy have been carried out. The results show that MSCs are safe and can significantly improve patients' respiratory function and prognosis of COVID-19. Here, the effects of MSCs and MSC-Exo in the treatment of COVID-19 are reviewed, and the clinical challenges that may be faced in the future are clarified.

The prognostic significance of insulin resistance in COVID-19: a review

Objectives

Emerging publications indicate that diabetes predisposes patients with COVID-19 to more severe complications, which is partly attributed to inflammatory condition. In the current review, we reviewed recent published literature to provide evidence on the role of insulin resistance (IR) in diabetes, the association between diabetes and COVID-19 severity and mortality, the impact of COVID-19 infection on incident new-onset diabetes, mechanisms responsible for IR in COVID-19 patients, and the predictive value of different surrogates of IR in COVID-19.

Method

The literature search performs to find out studies that have assessed the association between IR surrogates and morbidity and mortality in patients with COVID-19.

Results

We showed that there is a bulk of evidence in support of the fact that diabetes is a potent risk factor for enhanced morbidity and mortality in COVID-19 patients. COVID-19 patients with diabetes are more prone to remarkable dysglycemia compared to those without diabetes, which is associated with an unfavourable prognosis. Furthermore, SARS-COV2 can make patients predispose to IR and diabetes via activating ISR, affecting RAAS signaling pathway, provoking inflammation, and changing the expression of PPARɣ and SREBP-1. Additionally, higher IR is associated with increased morbidity and mortality in COVID-19 patients and different surrogates of IR can be utilized as a prognostic biomarker for COVID-19 patients.

Conclusion

Different surrogates of IR can be utilized as predictors of COVID-19 complications and death.

A Comprehensive Review of the Global Epidemiology, Clinical Management, Socio-Economic Impacts, and National Responses to Long COVID with Future Research Directions

Background: Long COVID, characterized by a persistent symptom spectrum following SARS-CoV-2 infection, poses significant health, social, and economic challenges. This review aims to consolidate knowledge on its epidemiology, clinical features, and underlying mechanisms to guide global responses; Methods: We conducted a literature review, analyzing peer-reviewed articles and reports to gather comprehensive data on long COVID's epidemiology, symptomatology, and management approaches; Results: Our analysis revealed a wide array of long COVID symptoms and risk factors, with notable demographic variability. The current understanding of its pathophysiology suggests a multifactorial origin yet remains partially understood. Emerging diagnostic criteria and potential therapeutic strategies were identified, highlighting advancements in long COVID management; Conclusions: This review highlights the multifaceted nature of long COVID, revealing a broad spectrum of symptoms, diverse risk factors, and the complex interplay of physiological mechanisms underpinning the condition. Long COVID symptoms and disorders will continue to weigh on healthcare systems in years to come. Addressing long COVID requires a holistic management strategy that integrates clinical care, social support, and policy initiatives. The findings underscore the need for increased international cooperation in research and health planning to address the complex challenges of long COVID. There is a call for continued refinement of diagnostic and treatment modalities, emphasizing a multidisciplinary approach to manage the ongoing and evolving impacts of the condition.

Host factors of SARS-CoV-2 in infection, pathogenesis, and long-term effects

SARS-CoV-2 is the causative virus of the devastating COVID-19 pandemic that results in an unparalleled global health and economic crisis. Despite unprecedented scientific efforts and therapeutic interventions, the fight against COVID-19 continues as the rapid emergence of different SARS-CoV-2 variants of concern and the increasing challenge of long COVID-19, raising a vast demand to understand the pathomechanisms of COVID-19 and its long-term sequelae and develop therapeutic strategies beyond the virus per se. Notably, in addition to the virus itself, the replication cycle of SARS-CoV-2 and clinical severity of COVID-19 is also governed by host factors. In this review, we therefore comprehensively overview the replication cycle and pathogenesis of SARS-CoV-2 from the perspective of host factors and host-virus interactions. We sequentially outline the pathological implications of molecular interactions between host factors and SARS-CoV-2 in multi-organ and multi-system long COVID-19, and summarize current therapeutic strategies and agents targeting host factors for treating these diseases. This knowledge would be key for the identification of new pathophysiological aspects and mechanisms, and the development of actionable therapeutic targets and strategies for tackling COVID-19 and its sequelae.

Current landscape of long COVID clinical trials

Long COVID was reported as a multi-systemic condition after the infection of SARS-CoV-2, and more than 65 million people are suffering from this disease. It has been noted that around 10% of severe SARS-CoV-2 infected individuals are suffering from the enduring effects of long COVID. The symptoms of long COVID have also been noted in several mild or asymptomatic SARS-CoV-2 infected individuals. While limited reports on clinical trials investigating new therapeutics for long COVID exist, there is an abundance of scattered information available regarding these trials. This review explores the extensive literature search, and complete clinical trial database search to map the current status of long COVID clinical trials worldwide. The study listed about 110 long COVID clinical trials. In addition to conducting extensive long COVID clinical trials, we have comprehensively presented an overview of the condition, its symptoms, notable manifestations, associated clinical trials, the unique challenges it poses, and our recommendations for addressing long COVID.

Prevalence and risk factors for long COVID among adults in Scotland using electronic health records: a national, retrospective, observational cohort study

Background

Long COVID is a debilitating multisystem condition. The objective of this study was to estimate the prevalence of long COVID in the adult population of Scotland, and to identify risk factors associated with its development.

Methods

In this national, retrospective, observational cohort study, we analysed electronic health records (EHRs) for all adults (≥18 years) registered with a general medical practice and resident in Scotland between March 1, 2020, and October 26, 2022 (98-99% of the population). We linked data from primary care, secondary care, laboratory testing and prescribing. Four outcome measures were used to identify long COVID: clinical codes, free text in primary care records, free text on sick notes, and a novel operational definition. The operational definition was developed using Poisson regression to identify clinical encounters indicative of long COVID from a sample of negative and positive COVID-19 cases matched on time-varying propensity to test positive for SARS-CoV-2. Possible risk factors for long COVID were identified by stratifying descriptive statistics by long COVID status.

Findings

Of 4,676,390 participants, 81,219 (1.7%) were identified as having long COVID. Clinical codes identified the fewest cases (n = 1,092, 0.02%), followed by free text (n = 8,368, 0.2%), sick notes (n = 14,469, 0.3%), and the operational definition (n = 64,193, 1.4%). There was limited overlap in cases identified by the measures; however, temporal trends and patient characteristics were consistent across measures. Compared with the general population, a higher proportion of people with long COVID were female (65.1% versus 50.4%), aged 38-67 (63.7% versus 48.9%), overweight or obese (45.7% versus 29.4%), had one or more comorbidities (52.7% versus 36.0%), were immunosuppressed (6.9% versus 3.2%), shielding (7.9% versus 3.4%), or hospitalised within 28 days of testing positive (8.8% versus 3.3%%), and had tested positive before Omicron became the dominant variant (44.9% versus 35.9%). The operational definition identified long COVID cases with combinations of clinical encounters (from four symptoms, six investigation types, and seven management strategies) recorded in EHRs within 4-26 weeks of a positive SARS-CoV-2 test. These combinations were significantly (p < 0.0001) more prevalent in positive COVID-19 patients than in matched negative controls. In a case-crossover analysis, 16.4% of those identified by the operational definition had similar healthcare patterns recorded before testing positive.

Interpretation

The prevalence of long COVID presenting in general practice was estimated to be 0.02-1.7%, depending on the measure used. Due to challenges in diagnosing long COVID and inconsistent recording of information in EHRs, the true prevalence of long COVID is likely to be higher. The operational definition provided a novel approach but relied on a restricted set of symptoms and may misclassify individuals with pre-existing health conditions. Further research is needed to refine and validate this approach.

Funding

Chief Scientist Office (Scotland), Medical Research Council, and BREATHE.

COVID-19 infection and incident diabetes in American Indian and Alaska Native people: a retrospective cohort study

Background

Evidence suggests an increased risk of new-onset diabetes following COVID-19 infection. American Indian/Alaska Native (AI/AN) people were disparately impacted by the COVID-19 pandemic and historically have had higher diabetes incidence than other racial/ethnic groups in the US. We measured the association between COVID-19 infection and incident diabetes in AI/AN people.

Methods

We conducted a retrospective cohort study using de-identified patient data from the Indian Health Service's (IHS) National Patient Information Reporting System. We estimated age-adjusted diabetes incidence rates, incidence rate ratios, and adjusted hazard ratios among three cohorts spanning pre-pandemic (1/1/2018-2/28/2020) and pandemic (3/1/2020-12/31/2021) timeframes: 1) pre-pandemic cohort (1,503,085 individuals); 2) no-COVID-19 pandemic cohort (1,344,339 individuals); and 3) COVID-19 cohort (176,483 individuals).

Findings

The COVID-19 cohort had an increased hazard of diabetes compared to the no-COVID-19 group (adjusted hazard ratio (aHR) = 1.56; 95% CI: 1.50-1.62) and the pre-pandemic group (aHR = 1.27; 95% CI: 1.22-1.32). The association between COVID-19 infection and new-onset diabetes was stronger in those with severe COVID-19 illness. A sensitivity analysis comparing the COVID-19 cohort to members of other cohorts that had acute upper respiratory infections showed an attenuated but higher risk of new-onset diabetes in those with COVID-19.

Interpretation

AI/AN people diagnosed with COVID-19 had an elevated risk of a new diabetes diagnosis when compared to the no-COVID-19 group and the pre-pandemic group. The increased diabetes risk in the COVID-19 group remained in a sensitivity analysis that limited the comparator groups to individuals with an AURI diagnosis.

Funding

US National Institute of Diabetes and Digestive and Kidney Diseases.

Is Pollution the Primary Driver of Infectious Syndemics?

Syndemics, the adverse interaction of two or more coterminous diseases or other negative health conditions, have probably existed since human settlement, plant and animal domestication, urbanization, and the growth of social inequality beginning about 10-12,000 years ago. These dramatic changes in human social evolution significantly increased opportunities for the spread of zoonotic infectious diseases in denser human communities with increased sanitation challenges. In light of a growing body of research that indicates that anthropogenic air pollution causes numerous threats to health and is taking a far greater toll on human life and wellbeing than had been reported, this paper proposes the possibility that air pollution is now the primary driver of infectious disease syndemics. In support of this assertion, this paper reviews the growth and health impacts of air pollution, the relationship of air pollution to the development and spread of infectious diseases, and reported cases of air pollution-driven infectious disease syndemics, and presents public health recommendations for leveraging the biosocial insight of syndemic theory in responding to infectious disease.

Long-Term Impairment of Working Ability in Subjects under 60 Years of Age Hospitalised for COVID-19 at 2 Years of Follow-Up: A Cross-Sectional Study

Background: Coronavirus disease 2019 (COVID-19) can lead to persistent and debilitating symptoms referred to as Post-Acute sequelae of SARS-CoV-2 infection (PASC) This broad symptomatology lasts for months after the acute infection and impacts physical and mental health and everyday functioning. In the present study, we aimed to evaluate the prevalence and predictors of long-term impairment of working ability in non-elderly people hospitalised for COVID-19. Methods: This cross-sectional study involved 322 subjects hospitalised for COVID-19 from 1 March 2020 to 31 December 2022 in the University Hospital of Bari, Apulia, Italy, enrolled at the time of their hospital discharge and followed-up at a median of 731 days since hospitalization (IQR 466-884). Subjects reporting comparable working ability and those reporting impaired working ability were compared using the Mann-Whitney test (continuous data) and Fisher's test or Chi-Square test (categorical data). Multivariable analysis of impaired working ability was performed using a logistic regression model. Results: Among the 322 subjects who were interviewed, 184 reported comparable working ability (57.1%) and 134 reported impaired working ability (41.6%) compared to the pre-COVID-19 period. Multivariable analysis identified age at hospital admission (OR 1.02, 95% CI 0.99 to 1.04), female sex (OR 1.90, 95% CI 1.18 to 3.08), diabetes (OR 3.73, 95% CI 1.57 to 9.65), receiving oxygen during hospital stay (OR 1.76, 95% CI 1.01 to 3.06), and severe disease (OR 0.51, 95% CI 0.26 to 1.01) as independent predictors of long-term impaired working ability after being hospitalised for COVID-19. Conclusions: Our findings suggest that PASC promotes conditions that could result in decreased working ability and unemployment. These results highlight the significant impact of this syndrome on public health and the global economy, and the need to develop clinical pathways and guidelines for long-term care with specific focus on working impairment.

The Aftermath of COVID-19: Exploring the Long-Term Effects on Organ Systems

BACKGROUND

Post-acute sequelae of SARS-CoV-2 infection (PASC) is a complicated disease that affects millions of people all over the world. Previous studies have shown that PASC impacts 10% of SARS-CoV-2 infected patients of which 50-70% are hospitalised. It has also been shown that 10-12% of those vaccinated against COVID-19 were affected by PASC and its complications. The severity and the later development of PASC symptoms are positively associated with the early intensity of the infection.

RESULTS

The generated health complications caused by PASC involve a vast variety of organ systems. Patients affected by PASC have been diagnosed with neuropsychiatric and neurological symptoms. The cardiovascular system also has been involved and several diseases such as myocarditis, pericarditis, and coronary artery diseases were reported. Chronic hematological problems such as thrombotic endothelialitis and hypercoagulability were described as conditions that could increase the risk of clotting disorders and coagulopathy in PASC patients. Chest pain, breathlessness, and cough in PASC patients were associated with the respiratory system in long-COVID causing respiratory distress syndrome. The observed immune complications were notable, involving several diseases. The renal system also was impacted, which resulted in raising the risk of diseases such as thrombotic issues, fibrosis, and sepsis. Endocrine gland malfunction can lead to diabetes, thyroiditis, and male infertility. Symptoms such as diarrhea, nausea, loss of appetite, and taste were also among reported observations due to several gastrointestinal disorders. Skin abnormalities might be an indication of infection and long-term implications such as persistent cutaneous complaints linked to PASC.

CONCLUSIONS

Long-COVID is a multidimensional syndrome with considerable public health implications, affecting several physiological systems and demanding thorough medical therapy, and more study to address its underlying causes and long-term effects is needed.

Precision Phenotyping for Curating Research Cohorts of Patients with Post-Acute Sequelae of COVID-19 (PASC) as a Diagnosis of Exclusion

Scalable identification of patients with the post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms and the suboptimal accuracy, demographic biases, and underestimation of the PASC diagnosis code (ICD-10 U09.9). In a retrospective case-control study, we developed a precision phenotyping algorithm for identifying research cohorts of PASC patients, defined as a diagnosis of exclusion. We used longitudinal electronic health records (EHR) data from over 295 thousand patients from 14 hospitals and 20 community health centers in Massachusetts. The algorithm employs an attention mechanism to exclude sequelae that prior conditions can explain. We performed independent chart reviews to tune and validate our precision phenotyping algorithm. Our PASC phenotyping algorithm improves precision and prevalence estimation and reduces bias in identifying Long COVID patients compared to the U09.9 diagnosis code. Our algorithm identified a PASC research cohort of over 24 thousand patients (compared to about 6 thousand when using the U09.9 diagnosis code), with a 79.9 percent precision (compared to 77.8 percent from the U09.9 diagnosis code). Our estimated prevalence of PASC was 22.8 percent, which is close to the national estimates for the region. We also provide an in-depth analysis outlining the clinical attributes, encompassing identified lingering effects by organ, comorbidity profiles, and temporal differences in the risk of PASC. The PASC phenotyping method presented in this study boasts superior precision, accurately gauges the prevalence of PASC without underestimating it, and exhibits less bias in pinpointing Long COVID patients. The PASC cohort derived from our algorithm will serve as a springboard for delving into Long COVID's genetic, metabolomic, and clinical intricacies, surmounting the constraints of recent PASC cohort studies, which were hampered by their limited size and available outcome data.

Population Trends of New Prescriptions for Antihyperglycemics and Antihypertensives Between 2014 and 2022

BACKGROUND

In the wake of pandemic-related health decline and health care disruptions, there are concerns that previous gains for cardiovascular risk factors may have stalled or reversed. Population-level excess burden of drug-treated diabetes and hypertension during the pandemic compared with baseline is not well characterized. We evaluated the change in incident prescription claims for antihyperglycemics and antihypertensives before versus during the pandemic.

METHODS AND RESULTS

In this retrospective, serial, cross-sectional, population-based study, we used interrupted time series analyses to examine changes in the age- and sex-standardized monthly rate of incident prescriptions for antihyperglycemics and antihypertensives in patients aged ≥66 years in Ontario, Canada, before the pandemic (April 2014 to March 2020) compared with during the pandemic (July 2020 to November 2022). Incident claim was defined as the first prescription filled for any medication in these classes. The characteristics of patients with incident prescriptions of antihyperglycemics (n=151 888) or antihypertensives (n=368 123) before the pandemic were comparable with their pandemic counterparts (antihyperglycemics, n=97 015; antihypertensives, n=146 524). Before the pandemic, monthly rates of incident prescriptions were decreasing (-0.03 per 10 000 individuals [95% CI, -0.04 to -0.01] for antihyperglycemics; -0.14 [95% CI, -0.18 to -0.10] for antihypertensives). After July 2020, monthly rates increased (postinterruption trend 0.31 per 10 000 individuals [95% CI, 0.28-0.34] for antihyperglycemics; 0.19 [95% CI, 0.14-0.23] for antihypertensives).

CONCLUSIONS

Population-level increases in new antihyperglycemic and antihypertensive prescriptions during the pandemic reversed prepandemic declines and were sustained for >2 years. Our findings are concerning for current and future cardiovascular health.

Infection with SARS-CoV-2 can cause pancreatic impairment

Evidence suggests associations between COVID-19 patients or vaccines and glycometabolic dysfunction and an even higher risk of the occurrence of diabetes. Herein, we retrospectively analyzed pancreatic lesions in autopsy tissues from 67 SARS-CoV-2 infected non-human primates (NHPs) models and 121 vaccinated and infected NHPs from 2020 to 2023 and COVID-19 patients. Multi-label immunofluorescence revealed direct infection of both exocrine and endocrine pancreatic cells by the virus in NHPs and humans. Minor and limited phenotypic and histopathological changes were observed in adult models. Systemic proteomics and metabolomics results indicated metabolic disorders, mainly enriched in insulin resistance pathways, in infected adult NHPs, along with elevated fasting C-peptide and C-peptide/glucose ratio levels. Furthermore, in elder COVID-19 NHPs, SARS-CoV-2 infection causes loss of beta (β) cells and lower expressed-insulin in situ characterized by islet amyloidosis and necrosis, activation of α-SMA and aggravated fibrosis consisting of lower collagen in serum, an increase of pancreatic inflammation and stress markers, ICAM-1 and G3BP1, along with more severe glycometabolic dysfunction. In contrast, vaccination maintained glucose homeostasis by activating insulin receptor α and insulin receptor β. Overall, the cumulative risk of diabetes post-COVID-19 is closely tied to age, suggesting more attention should be paid to blood sugar management in elderly COVID-19 patients.

Using a data-driven approach to define post-COVID conditions in US electronic health record data

OBJECTIVE

To create a data-driven definition of post-COVID conditions (PCC) by directly measure changes in symptomatology before and after a first COVID episode.

MATERIALS AND METHODS

Retrospective cohort study using Optum® de-identified Electronic Health Record (EHR) dataset from the United States of persons of any age April 2020-September 2021. For each person with COVID (ICD-10-CM U07.1 "COVID-19" or positive test result), we selected up to 3 comparators. The final COVID symptom score was computed as the sum of new diagnoses weighted by each diagnosis' ratio of incidence in COVID group relative to comparator group. For the subset of COVID cases diagnosed in September 2021, we compared the incidence of PCC using our data-driven definition with ICD-10-CM code U09.9 "Post-COVID Conditions", first available in the US October 2021.

RESULTS

The final cohort contained 588,611 people with COVID, with mean age of 48 years and 38% male. Our definition identified 20% of persons developed PCC in follow-up. PCC incidence increased with age: (7.8% of persons aged 0-17, 17.3% aged 18-64, and 33.3% aged 65+) and did not change over time (20.0% among persons diagnosed with COVID in 2020 versus 20.3% in 2021). For cases diagnosed in September 2021, our definition identified 19.0% with PCC in follow-up as compared to 2.9% with U09.9 code in follow-up.

CONCLUSION

Symptom and U09.9 code-based definitions alone captured different populations. Maximal capture may consider a combined approach, particularly before the availability and routine utilization of specific ICD-10 codes and with the lack consensus-based definitions on the syndrome.

Incident allergic diseases in post-COVID-19 condition: multinational cohort studies from South Korea, Japan and the UK

As mounting evidence suggests a higher incidence of adverse consequences, such as disruption of the immune system, among patients with a history of COVID-19, we aimed to investigate post-COVID-19 conditions on a comprehensive set of allergic diseases including asthma, allergic rhinitis, atopic dermatitis, and food allergy. We used nationwide claims-based cohorts in South Korea (K-CoV-N; n = 836,164; main cohort) and Japan (JMDC; n = 2,541,021; replication cohort A) and the UK Biobank cohort (UKB; n = 325,843; replication cohort B) after 1:5 propensity score matching. Among the 836,164 individuals in the main cohort (mean age, 50.25 years [SD, 13.86]; 372,914 [44.6%] women), 147,824 were infected with SARS-CoV-2 during the follow-up period (2020-2021). The risk of developing allergic diseases, beyond the first 30 days of diagnosis of COVID-19, significantly increased (HR, 1.20; 95% CI, 1.13-1.27), notably in asthma (HR, 2.25; 95% CI, 1.80-2.83) and allergic rhinitis (HR, 1.23; 95% CI, 1.15-1.32). This risk gradually decreased over time, but it persisted throughout the follow-up period (≥6 months). In addition, the risk increased with increasing severity of COVID-19. Notably, COVID-19 vaccination of at least two doses had a protective effect against subsequent allergic diseases (HR, 0.81; 95% CI, 0.68-0.96). Similar findings were reported in the replication cohorts A and B. Although the potential for misclassification of pre-existing allergic conditions as incident diseases remains a limitation, ethnic diversity for evidence of incident allergic diseases in post-COVID-19 condition has been validated by utilizing multinational and independent population-based cohorts.

Long-COVID-19 autonomic dysfunction: An integrated view in the framework of inflammaging

The recently identified syndrome known as Long COVID (LC) is characterized by a constellation of debilitating conditions that impair both physical and cognitive functions, thus reducing the quality of life and increasing the risk of developing the most common age-related diseases. These conditions are linked to the presence of symptoms of autonomic dysfunction, in association with low cortisol levels, suggestive of reduced hypothalamic-pituitary-adrenal (HPA) axis activity, and with increased pro-inflammatory condition. Alterations of dopamine and serotonin neurotransmitter levels were also recently observed in LC. Interestingly, at least some of the proposed mechanisms of LC development overlap with mechanisms of Autonomic Nervous System (ANS) imbalance, previously detailed in the framework of the aging process. ANS imbalance is characterized by a proinflammatory sympathetic overdrive, and a concomitant decreased anti-inflammatory vagal parasympathetic activity, associated with reduced anti-inflammatory effects of the HPA axis and cholinergic anti-inflammatory pathway (CAP). These neuro-immune-endocrine system imbalanced activities fuel the vicious circle of chronic inflammation, i.e. inflammaging. Here, we refine our original hypothesis that ANS dysfunction fuels inflammaging and propose that biomarkers of ANS imbalance could also be considered biomarkers of inflammaging, recognized as the main risk factor for developing age-related diseases and the sequelae of viral infections, i.e. LC.

Precision nutrition to reset virus-induced human metabolic reprogramming and dysregulation (HMRD) in long-COVID

SARS-CoV-2, the etiological agent of COVID-19, is devoid of any metabolic capacity; therefore, it is critical for the viral pathogen to hijack host cellular metabolic machinery for its replication and propagation. This single-stranded RNA virus with a 29.9 kb genome encodes 14 open reading frames (ORFs) and initiates a plethora of virus-host protein-protein interactions in the human body. These extensive viral protein interactions with host-specific cellular targets could trigger severe human metabolic reprogramming/dysregulation (HMRD), a rewiring of sugar-, amino acid-, lipid-, and nucleotide-metabolism(s), as well as altered or impaired bioenergetics, immune dysfunction, and redox imbalance in the body. In the infectious process, the viral pathogen hijacks two major human receptors, angiotensin-converting enzyme (ACE)-2 and/or neuropilin (NRP)-1, for initial adhesion to cell surface; then utilizes two major host proteases, TMPRSS2 and/or furin, to gain cellular entry; and finally employs an endosomal enzyme, cathepsin L (CTSL) for fusogenic release of its viral genome. The virus-induced HMRD results in 5 possible infectious outcomes: asymptomatic, mild, moderate, severe to fatal episodes; while the symptomatic acute COVID-19 condition could manifest into 3 clinical phases: (i) hypoxia and hypoxemia (Warburg effect), (ii) hyperferritinemia ('cytokine storm'), and (iii) thrombocytosis (coagulopathy). The mean incubation period for COVID-19 onset was estimated to be 5.1 days, and most cases develop symptoms after 14 days. The mean viral clearance times were 24, 30, and 39 days for acute, severe, and ICU-admitted COVID-19 patients, respectively. However, about 25-70% of virus-free COVID-19 survivors continue to sustain virus-induced HMRD and exhibit a wide range of symptoms that are persistent, exacerbated, or new 'onset' clinical incidents, collectively termed as post-acute sequelae of COVID-19 (PASC) or long COVID. PASC patients experience several debilitating clinical condition(s) with >200 different and overlapping symptoms that may last for weeks to months. Chronic PASC is a cumulative outcome of at least 10 different HMRD-related pathophysiological mechanisms involving both virus-derived virulence factors and a multitude of innate host responses. Based on HMRD and virus-free clinical impairments of different human organs/systems, PASC patients can be categorized into 4 different clusters or sub-phenotypes: sub-phenotype-1 (33.8%) with cardiac and renal manifestations; sub-phenotype-2 (32.8%) with respiratory, sleep and anxiety disorders; sub-phenotype-3 (23.4%) with skeleto-muscular and nervous disorders; and sub-phenotype-4 (10.1%) with digestive and pulmonary dysfunctions. This narrative review elucidates the effects of viral hijack on host cellular machinery during SARS-CoV-2 infection, ensuing detrimental effect(s) of virus-induced HMRD on human metabolism, consequential symptomatic clinical implications, and damage to multiple organ systems; as well as chronic pathophysiological sequelae in virus-free PASC patients. We have also provided a few evidence-based, human randomized controlled trial (RCT)-tested, precision nutrients to reset HMRD for health recovery of PASC patients.

Healthcare workers' perspectives on barriers and facilitators to referral and recruitment to diabetes prevention programmes: a systematic review protocol

Background

Diabetes is a growing global health problem. International guidelines recommend identification, screening, and referral to behavioural programmes for those at high risk of developing type 2 diabetes. Diabetes prevention programmes (DPPs) can prevent type 2 diabetes in those at high risk, however many eligible participants are not referred to these programmes. Healthcare workers (HCWs) are pivotal to the referral and recruitment processes. This study aims to identify, appraise and synthesise the evidence on barriers and facilitators to referral and recruitment to DPPs from the perspective of HCWs.

Methods

A "best fit" framework synthesis method will synthesise qualitative, quantitative, and mixed methods evidence on factors that affect HCWs referral and recruitment to DPPs, with the Theoretical Domains Framework (TDF) as the a priori framework. MEDLINE, EMBASE, CINAHL, PsychINFO, Web of Science and Scopus will be searched for primary studies published in English. Year of publication will be restricted to the last 26 years (1997-2023). Quality will be assessed using the Mixed Methods Appraisal Tool. A mix of deductive coding using the TDF and inductive coding of data that does not fit the TDF will be synthesised into themes representing the whole dataset. The relationships between the final set of themes will be explored to create a new model to understand HCWs' perspectives on referral and recruitment to DPPs. Sensitivity analysis will be carried out on this conceptual model. Confidence in the synthesised findings will be assessed using the GRADE-CERQual approach. One author will screen, extract, appraise the literature while a second author will independently verify a 20% sample at each stage.

Discussion

Participation in DPPs is key for programme impact. HCWs typically identify those at risk and refer them to DPPs. Understanding HCWs' perspectives on the barriers and facilitators to referral and recruitment will inform future implementation of DPPs.

Long COVID: Long-Term Impact of SARS-CoV2

Four years post-pandemic, SARS-CoV-2 continues to affect many lives across the globe. An estimated 65 million people suffer from long COVID, a term used to encapsulate the post-acute sequelae of SARS-CoV-2 infections that affect multiple organ systems. Known symptoms include chronic fatigue syndrome, brain fog, cardiovascular issues, autoimmunity, dysautonomia, and clotting due to inflammation. Herein, we review long COVID symptoms, the proposed theories behind the pathology, diagnostics, treatments, and the clinical trials underway to explore treatments for viral persistence, autonomic and cognitive dysfunctions, sleep disturbances, fatigue, and exercise intolerance.

Long COVID's Impact on Patients, Workers, & Society: A review

The incidence of long COVID in adult survivors of an acute SARS-CoV-2 infection is approximately 11%. Of those afflicted, 26% have difficulty with day-to-day activities. The majority of long COIVD cases occur after mild or asymptomatic acute infection. Children can spread SARS-CoV-2 infections and can also develop long-term neurological, endocrine (type I diabetes), and immunological sequelae. Immunological hypofunction is exemplified by the recent large outbreaks of respiratory syncytial virus and streptococcal infections. Neurological manifestations are associated with anatomical brain damage demonstrated on brain scans and autopsy studies. The prefrontal cortex is particularly susceptible. Common symptoms include brain fog, memory loss, executive dysfunction, and personality changes. The impact on society has been profound. Fewer than half of previously employed adults who develop long COVID are working full-time, and 42% of patients reported food insecurity and 20% reported difficulties paying rent. Vaccination not only helps prevent severe COVID-19, but numerous studies have found beneficial effects in preventing and mitigating long COVID. There is also evidence that vaccination after an acute infection can lessen the symptoms of long COVID. Physical and occupational therapy can also help patients regain function, but the approach must be "low and slow." Too much physical or mental activity can result in post-exertional malaise and set back the recovery process by days or weeks. The complexity of long COVID presentations coupled with rampant organized disinformation, have caused significant segments of the public to ignore sound public health advice. Further research is needed regarding treatment and effective public communication.

Endothelial Extracellular Vesicles Enriched in microRNA-34a Predict New-Onset Diabetes in Coronavirus Disease 2019 (COVID-19) Patients: Novel Insights for Long COVID Metabolic Sequelae

Emerging evidence indicates that the relationship between coronavirus disease 2019 (COVID-19) and diabetes is 2-fold: 1) it is known that the presence of diabetes and other metabolic alterations poses a considerably high risk to develop a severe COVID-19; 2) patients who survived a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have an increased risk of developing new-onset diabetes. However, the mechanisms underlying this association are mostly unknown, and there are no reliable biomarkers to predict the development of new-onset diabetes. In the present study, we demonstrate that a specific microRNA (miR-34a) contained in circulating extracellular vesicles released by endothelial cells reliably predicts the risk of developing new-onset diabetes in COVID-19. This association was independent of age, sex, body mass index (BMI), hypertension, dyslipidemia, smoking status, and D-dimer. SIGNIFICANCE STATEMENT: We demonstrate for the first time that a specific microRNA (miR-34a) contained in circulating extracellular vesicles released by endothelial cells is able to reliably predict the risk of developing diabetes after having contracted coronavirus disease 2019 (COVID-19). This association was independent of age, sex, body mass index (BMI), hypertension, dyslipidemia, smoking status, and D-dimer. Our findings are also relevant when considering the emerging importance of post-acute sequelae of COVID-19, with systemic manifestations observed even months after viral negativization (long COVID).

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.

Diabetes care in the pandemic era in the Midwestern USA: a semi-structured interview study of the patient perspective

OBJECTIVES

To understand patients' experiences with diabetes care during the COVID-19 pandemic, with an emphasis on rural, medically underserved, and/or minoritised racial and ethnic groups in the Midwestern USA.

DESIGN

Community-engaged, semi-structured interviews were conducted by medical student researchers trained in qualitative interviewing. Transcripts were prepared and coded in the language in which the interview was conducted (English or Spanish). Thematic analysis was conducted, and data saturation was achieved.

SETTING

The study was conducted in communities in Eastern and Western Iowa.

PARTICIPANTS

Adults with diabetes (n=20) who were fluent in conversational English or Spanish were interviewed. One-third of participants were residents of areas designated as federal primary healthcare professional shortage areas and/or medically underserved areas, and more than half were recruited from medical clinics that offer care at no cost.

RESULTS

Themes across both English and Spanish transcripts included: (1) perspectives of diabetes, care providers and care management; (2) challenges and barriers affecting diabetes care; and (3) participant feedback and recommendations. Participants reported major constraints related to provider availability, costs of care, access to nutrition counselling and mental health concerns associated with diabetes care during the pandemic. Participants also reported a lack of shared decision-making regarding some aspects of care, including amputation. Finally, participants recognised systems-level challenges that affected both patients and providers and expressed a preference for proactive collaboration with healthcare teams.

CONCLUSIONS

These findings support enhanced engagement of rural, medically underserved and minoritised groups as stakeholders in diabetes care, diabetes research and diabetes provider education.

The knowns and unknowns of long COVID-19: from mechanisms to therapeutical approaches

The coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has been defined as the greatest global health and socioeconomic crisis of modern times. While most people recover after being infected with the virus, a significant proportion of them continue to experience health issues weeks, months and even years after acute infection with SARS-CoV-2. This persistence of clinical symptoms in infected individuals for at least three months after the onset of the disease or the emergence of new symptoms lasting more than two months, without any other explanation and alternative diagnosis have been named long COVID, long-haul COVID, post-COVID-19 conditions, chronic COVID, or post-acute sequelae of SARS-CoV-2 (PASC). Long COVID has been characterized as a constellation of symptoms and disorders that vary widely in their manifestations. Further, the mechanisms underlying long COVID are not fully understood, which hamper efficient treatment options. This review describes predictors and the most common symptoms related to long COVID's effects on the central and peripheral nervous system and other organs and tissues. Furthermore, the transcriptional markers, molecular signaling pathways and risk factors for long COVID, such as sex, age, pre-existing condition, hospitalization during acute phase of COVID-19, vaccination, and lifestyle are presented. Finally, recommendations for patient rehabilitation and disease management, as well as alternative therapeutical approaches to long COVID sequelae are discussed. Understanding the complexity of this disease, its symptoms across multiple organ systems and overlapping pathologies and its possible mechanisms are paramount in developing diagnostic tools and treatments.

Current clinical findings of acute neurological syndromes after SARS-CoV-2 infection

Neuro-COVID, a condition marked by persistent symptoms post-COVID-19 infection, notably affects various organs, with a particular focus on the central nervous system (CNS). Despite scant evidence of SARS-CoV-2 invasion in the CNS, the increasing incidence of Neuro-COVID cases indicates the onset of acute neurological symptoms early in infection. The Omicron variant, distinguished by heightened neurotropism, penetrates the CNS via the olfactory bulb. This direct invasion induces inflammation and neuronal damage, emphasizing the need for vigilance regarding potential neurological complications. Our multicenter study represents a groundbreaking revelation, documenting the definite presence of SARS-CoV-2 in the cerebrospinal fluid (CSF) of a significant proportion of Neuro-COVID patients. Furthermore, notable differences emerged between RNA-CSF-positive and negative patients, encompassing aspects such as blood-brain barrier integrity, extent of neuronal damage, and the activation status of inflammation. Despite inherent limitations, this research provides pivotal insights into the intricate interplay between SARS-CoV-2 and the CNS, underscoring the necessity for ongoing research to fully comprehend the virus's enduring effects on the CNS. The findings underscore the urgency of continuous investigation Neuro-COVID to unravel the complexities of this relationship, and pivotal in addressing the long-term consequences of COVID-19 on neurological health.

Long-Term Autoimmune Inflammatory Rheumatic Outcomes of COVID-19 : A Binational Cohort Study

BACKGROUND

Some data suggest a higher incidence of diagnosis of autoimmune inflammatory rheumatic diseases (AIRDs) among patients with a history of COVID-19 compared with uninfected patients. However, these studies had methodological shortcomings.

OBJECTIVE

To investigate the effect of COVID-19 on long-term risk for incident AIRD over various follow-up periods.

DESIGN

Binational, longitudinal, propensity-matched cohort study.

SETTING

Nationwide claims-based databases in South Korea (K-COV-N cohort) and Japan (JMDC cohort).

PARTICIPANTS

10 027 506 Korean and 12 218 680 Japanese patients aged 20 years or older, including those with COVID-19 between 1 January 2020 and 31 December 2021, matched to patients with influenza infection and to uninfected control patients.

MEASUREMENTS

The primary outcome was onset of AIRD (per appropriate codes from the International Classification of Diseases, 10th Revision) 1, 6, and 12 months after COVID-19 or influenza infection or the respective matched index date of uninfected control patients.

RESULTS

Between 2020 and 2021, among the 10 027 506 Korean participants (mean age, 48.4 years [SD, 13.4]; 50.1% men), 394 274 (3.9%) and 98 596 (0.98%) had a history of COVID-19 or influenza, respectively. After propensity score matching, beyond the first 30 days after infection, patients with COVID-19 were at increased risk for incident AIRD compared with uninfected patients (adjusted hazard ratio, 1.25 [95% CI, 1.18 to 1.31]) and influenza-infected control patients (adjusted hazard ratio, 1.30 [CI, 1.02 to 1.59]). The risk for incident AIRD was higher with more severe acute COVID-19. Similar patterns were observed in the Japanese cohort.

LIMITATIONS

Referral bias due to the pandemic; residual confounding.

CONCLUSION

SARS-CoV-2 infection was associated with increased risk for incident AIRD compared with matched patients without SARS-CoV-2 infection or with influenza infection. The risk for incident AIRD was higher with greater severity of acute COVID-19.

PRIMARY FUNDING SOURCE

National Research Foundation of Korea.