New-onset Diseases Research Articles

Cardiometabolic index and the risk of new-onset chronic diseases: results of a national prospective longitudinal study.

The cardiometabolic index (CMI) has emerged as a novel marker for evaluating the distribution and dysfunction of visceral adipose tissue, yet its correlation with numerous diseases, particularly new-onset chronic conditions, remains underexplored. Therefore, we aim to explore the association of cardiometabolic index (CMI) and new-onset chronic diseases. The analysis utilized data from the China Health and Retirement Longitudinal Study, with a baseline in 2011 and follow-ups biennially until 2020. Fourteen new-onset chronic diseases were diagnosed based on self-report, and separate cohorts were created for each disease. CMI was calculated as triglycerides/high-density lipoprotein cholesterol multiplied by the waist-to-height ratio. Cox proportional hazards models were used to assess the association between CMI and new-onset chronic diseases, while restricted cubic spline (RCS) models were employed to explore potential nonlinear effects. Additional and sensitivity analyses included Kaplan-Meier survival curves, subgroup analyses, multiple imputations, and exclude outcome events at the first follow-up. Higher levels of CMI were associated with an increased risk of new-onset hypertension (HR=1.05, 95% CI=1.04-1.06, P<0.001), diabetes (HR=1.08, 95% CI=1.06-1.09, P<0.001), dyslipidemia (HR=1.07, 95% CI=1.06-1.09, P<0.001), liver disease (HR=1.05, 95% CI=1.03-1.07, P<0.003), and stroke (HR=1.04, 95% CI=1.02-1.06, P<0.001), although the association with stroke was not significant after adjusting for confounders (HR=1.02, 95% CI=1.00-1.05, P=0.054). Participants in the highest quartile of CMI had a significantly higher risk of these diseases compared to those in the lowest quartile. RCS analyses showed a significant nonlinear relationship between CMI and the risk of these diseases above. CMI showed a significant positive association with the risk of new-onset chronic diseases such as hypertension, diabetes, dyslipidemia, and liver disease. Future applications of CMI hold promise as an effective marker for early identification of chronic disease risk.

The Interplay between nighttime/midday sleep duration and the number of new-onset chronic diseases: A decade-long prospective study in China

ObjectiveTo investigate the interplay between individual nighttime and midday sleep duration and the number of new-onset chronic diseases and determine the optimal sleep duration associated with lowest number of new-onset chronic diseases. MethodsWe used data from the China Health and Retirement Longitudinal Study (CHARLS) covering a decade and involving 10,828 participants. A random intercept cross-lagged model was used to explore the interplay between nighttime/midday sleep durations and new-onset chronic diseases at both the within-individual and between-individual levels, followed by a dose–response analysis at the between-individual level to determine the optimal sleep duration. New-onset chronic diseases include 14 types of self-reported diseases diagnosed by doctors. ResultsWithin-individual analysis revealed that increased nighttime/midday sleep duration led to a higher number of new-onset chronic diseases, and an increased number of new-onset chronic diseases resulted in decreased nighttime sleep duration. Between nighttime and midday sleep, one type of sleep duration increase was likely to lead to an increase in another type. Between-individual analysis found a nonlinear relationship between the number of new-onset chronic diseases and nighttime sleep duration, identifying the optimal nighttime sleep duration as 7.46 h. ConclusionsThese findings elucidate the interplay between sleep duration and number of new-onset chronic diseases and underscore the need for public awareness and comprehensive interventions. Future studies should focus on refining sleep monitoring and exploring the sleep–chronic diseases nexus in greater depth.

Characteristics and predictors of Long Covid in children: a 3-year prospective cohort study

Children can develop Long Covid, however long term outcomes and their predictors are poorly described in these patients. The primary aim is to describe characteristics and predictors of Long Covid in children assessed in-clinics up to 36 months post-SARS-CoV-2 infection, as well as investigate the role of vaccines in preventing Long Covid, risk of reinfections and development of autoimmune diseases. Children aged 0-18 years old with confirmed SARS-CoV-2 infection were invited for a prospective follow-up assessment at a peadiatric post-covid clinic in Rome, Italy, at serial intervals (3-, 6-, 12-, 18-, 24- and 36-months post-infection onset, between 01/02/2020 and 28/02/2024). Long Covid was defined as persistence of otherwise unexplained symptoms for at least three months after initial infection. 1319 patients were initially included, 1296 reached the 3 months follow-up or more. Of the patients who underwent multiple follow-ups, 23.2% (301), 169 (13.2%), 89 (7.9%), 67 (6.1%), 47 (7.1%) were diagnosed with Long Covid at 3-6-12-18-24 months, respectively For the primary outcome of Long Covid at three months, age >12 years (P<0.001, OR 11.33, 95% CI 4.2; 15.15), comorbidities (P=0.008, OR 1.83, 95% CI 1.06; 2.44), being infected with original variants (P<0.001, OR 4.77, 95% CI 2.46; 14.47), female sex (P<0.001, OR 1.62, 95% CI 1.02; 1.89) were statistically significant risk factors. Age >12 years (P=0.002, OR 9.37, 95% CI 1.58; 8.64), and infection with original (P=0.012, OR 3.52, 95% CI 1.32; 8.64) and alfa (P<0.001, OR 4.09, 95% CI 2.01; 8.3) SARS-CoV-2 variants remained statistically significant risk factors for Long Covid duration for at least 18 months. Vaccination was associated with a lower risk of long covid at 3, 6 and 12 months for older children and a lower risk of reinfections. Being infected with the original SARS-CoV-2 variant was associated with a higher risk of new-onset autoimmune diseases ((P=0.035, 95% CI 1.12; 2.4). One patient was diagnosed with Long Covid after a re-infection. This is the longest follow-up study of children with SARS-CoV-2 infection, showing a significant and long-lasting burden of Long Covid in the pediatric population. Our findings highlight the urgent need of investing in pediatric Long Covid in order to find effective diagnostic and therapeutic approaches, as well can inform preventive strategies in case of future pandemics. This study has been funde by Pfizer non-competitive grant, granted to DB (#65925795).

New-onset obstructive airway disease following COVID-19: a multicenter retrospective cohort study

BackgroundThe study assessed the association between COVID-19 and new-onset obstructive airway diseases, including asthma, chronic obstructive pulmonary disease, and bronchiectasis among vaccinated individuals recovering from COVID-19 during the Omicron wave.MethodsThis multicenter retrospective cohort study comprised 549,606 individuals from the U.S. Collaborative Network of TriNetX database, from January 8, 2022, to January 17, 2024. The hazard of new-onset obstructive airway diseases between COVID-19 and no-COVID-19 groups were compared following propensity score matching using the Kaplan–Meier method and Cox proportional hazards model.ResultsAfter propensity score matching, each group contained 274,803 participants. Patients with COVID-19 exhibited a higher risk of developing new-onset asthma than that of individuals without COVID-19 (adjusted hazard ratio (aHR), 1.27; 95% CI, 1.22–1.33; p < 0.001). Stratified analyses by age, SARS-CoV-2 variant, vaccination status, and infection status consistently supported this association. Non-hospitalized individuals with COVID-19 demonstrated a higher risk of new-onset asthma (aHR, 1.27; 95% CI, 1.22–1.33; p < 0.001); however, no significant differences were observed in hospitalized and critically ill groups. The study also identified an increased risk of subsequent bronchiectasis following COVID-19 (aHR, 1.30; 95% CI, 1.13–1.50; p < 0.001). In contrast, there was no significant difference in the hazard of chronic obstructive pulmonary disease between the groups (aHR, 1.00; 95% CI, 0.95–1.06; p = 0.994).ConclusionThis study offers convincing evidence of the association between COVID-19 and the subsequent onset of asthma and bronchiectasis. It underscores the need for a multidisciplinary approach to post-COVID-19 care, with a particular focus on respiratory health.

Associations of very low Lipoprotein(a) levels with risks of new-onset diabetes and non-alcoholic liver disease

Background and aimsWe aimed to study the association of very low serum Lipoprotein(a) [Lp(a)] concentrations with new-onset type 2 diabetes (T2D) and non-alcoholic liver disease (NAFLD) in the context of statin usage in the UK Biobank, a large prospective population cohort. MethodsUsing an extended biomarker dataset, we identified 47,362 participants with very low Lp(a) concentrations (<3.8 nmol/L) from a total of 451,479 participants. With a median follow-up of 12.3 years, we assessed the risk of new-onset cardiometabolic diseases in participants stratified by statin usage with Cox proportional hazards models. We performed two-sample Mendelian randomization MR analyses to test causal relationship between genetically predicted Lp(a) and T2D and NAFLD. ResultsTaking the participants with Lp(a) within reportable range as the reference group, the hazard ratios (HR) for T2D were 1.07 (95 % confidence interval, CI 1.01–1.13) and for NAFLD 1.30 (95 % CI 1.20–1.41) respectively for participants with very low Lp(a) (<3.8 nmol/L). The risk for new-onset T2D was higher in participants using statins (adjusted HR 1.15; 95 % CI 1.05–1.27). The risk estimates for new-onset NAFLD were comparable in the analysis stratified by statin use. There was no evidence for causal links between genetically predicted Lp(a) and T2D nor NAFLD in two-sample MR analyses. ConclusionsVery low Lp(a) was associated with higher risks of T2D and NAFLD in a prospective analysis of the UK Biobank. The association with T2D was influenced by lipid lowering medication usage. MR analyses did not support causality for these inverse associations.

Deep Learning-Based Vascular Aging Prediction From Retinal Fundus Images.

The purpose of this study was to establish and validate a deep learning model to screen vascular aging using retinal fundus images. Although vascular aging is considered a novel cardiovascular risk factor, the assessment methods are currently limited and often only available in developed regions. We used 8865 retinal fundus images and clinical parameters of 4376 patients from two independent datasets for training a deep learning algorithm. The gold standard for vascular aging was defined as a pulse wave velocity ≥1400 cm/s. The probability of the presence of vascular aging was defined as deep learning retinal vascular aging score, the Reti-aging score. We compared the performance of the deep learning model and clinical parameters by calculating the area under the receiver operating characteristics curve (AUC). We recruited clinical specialists, including ophthalmologists and geriatricians, to assess vascular aging in patients using retinal fundus images, aiming to compare the diagnostic performance between deep learning models and clinical specialists. Finally, the potential of Reti-aging score for identifying new-onset hypertension (NH) and new-onset carotid artery plaque (NCP) in the subsequent three years was examined. The Reti-aging score model achieved an AUC of 0.826 (95% confidence interval [CI] = 0.793-0.855) and 0.779 (95% CI = 0.765-0.794) in the internal and external dataset. It showed better performance in predicting vascular aging compared with the prediction with clinical parameters. The average accuracy of ophthalmologists (66.3%) was lower than that of the Reti-aging score model, whereas geriatricians were unable to make predictions based on retinal fundus images. The Reti-aging score was associated with the risk of NH and NCP (P < 0.05). The Reti-aging score model might serve as a novel method to predict vascular aging through analysis of retinal fundus images. Reti-aging score provides a novel indicator to predict new-onset cardiovascular diseases. Given the robust performance of our model, it provides a new and reliable method for screening vascular aging, especially in undeveloped areas.

Immune checkpoint inhibitor-associated new-onset hypophysitis: a retrospective analysis using the FAERS.

Our study aimed to investigate the prevalence and demographic characteristics of immune checkpoint inhibitor-associated hypophysitis (ICI-hypophysitis) using data from the FAERS, and the risk factors of prognosis were explored. In this retrospective study, all cases of newly-diagnosed hypophysitis associated with FDA approved ICIs from 1st January 2007 to 31st December 2022 were accumulated using FAERS. Demographic data including age, sex, body weight, the prognosis of cases, and other co-occurred endocrinopathies induced by ICIs were analyzed and compared between different subgroups of immunotherapy. The reporting frequency of ICI-hypophysitis was 1.46% (2343/160089). Patients on the combination therapy had higher risk of hypophysitis reporting, followed by anti-CTLA-4 agent compared with other monotherapies (p < 0.001). Male subjects displayed higher reporting risk of ICI-hypophysitis (p = 0.015). Patients on anti-PD-1 therapy or the combination therapy showed higher occurrence rate of type 1 diabetes (anti-PD-1 vs. anti-PD-L1 vs. anti-CTLA-4 vs. combination therapy, 4.2% vs. 0.7% vs. 0.3% vs. 8.4%, p < 0.001). The occurrence rate of new-onset thyroid diseases in patients receiving combination therapy was higher than anti-PD-1 monotherapy (12.3% vs. 8.4%, p = 0.010). Elder age, lung cancer, and renal cancer emerged to be positively associated with severe clinical outcomes [>65 years, OR 1.042, 95%CI (1.022-1.063), p < 0.001; lung cancer, OR 1.400, 95%CI (1.019-1.923), p = 0.038; renal cancer, OR 1.667, 95%CI (1.153-2.412), p = 0.007]. Anti-CTLA-4 monotherapy was discovered to be a protective factor of severe outcomes [OR 0.433, 95%CI (0.335-0.558), p < 0.001]. Female sex and co-occurrence of ICI-related diabetes exhibited lower risk of death [female, OR 0.571, 95%CI (0.361-0.903), p = 0.017; diabetes, OR 0.090, 95%CI (0.016-0.524), p = 0.007]. ICI-induced hypophysitis is male-predominant irAE, most commonly seen in patients on anti-CTLA-4 mono- or combination therapy. Awareness among clinicians is critical when patients with elder age, lung or renal cancer develop hypophysitis, which indicates poor clinical outcomes. Female sex, anti-CTLA-4 monotherapy and co-occurrence of ICI-related diabetes are protective risk factors for poor prognosis.

Comparison of triglyceride glucose index and modified triglyceride glucose indices in prediction of cardiovascular diseases in middle aged and older Chinese adults

BackgroundTriglyceride and glucose (TyG) index, a surrogate marker of insulin resistance, has been validated as a predictor of cardiovascular disease. However, effects of TyG-related indices combined with obesity markers on cardiovascular diseases remained unknown. We aimed to investigate the associations between TyG index and modified TyG indices with new-onset cardiovascular disease and the time-dependent predictive capacity using a national representative cohort.MethodsThis study is a retrospective observational cohort study using data from China Health and Retirement Longitudinal Study (CHARLS) of 7 115 participants. The TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. The modified TyG indices were developed combining TyG with body mass index (BMI), waist circumference (WC) and waist-to‐height ratio (WHtR). We used adjusted Cox proportional hazards regression to analyze the association and predictive capacity based on hazard ratio (HR) and Harrell’s C‐index.ResultsOver a 7-year follow‐up period, 2136 participants developed cardiovascular disease, including 1633 cases of coronary heart disease and 719 cases of stroke. Compared with the lowest tertile group, the adjusted HR (95% CI) for new-onset cardiovascular disease in the highest tertile for TyG, TyG-BMI, TyG-WC, and TyG-WHtR were 1.215 (1.088–1.356), 1.073 (0.967–1.191), 1.078 (0.970–1.198), and 1.112 (1.002–1.235), respectively. The C‐indices of TyG index for cardiovascular disease onset were higher than other modified TyG indices. Similar results were observed for coronary heart disease and stroke.ConclusionTyG and TyG-WhtR were significantly associated with new-onset cardiovascular diseases, and TyG outperformed the modified TyG indices to identify individuals at risk of incident cardiovascular event.

Comprehensive clinical application analysis of artificial intelligence-enabled electrocardiograms for screening multiple valvular heart diseases.

Valvular heart disease (VHD) is becoming increasingly important to manage the risk of future complications. Electrocardiographic (ECG) changes may be related to multiple VHDs, and (AI)-enabled ECG has been able to detect some VHDs. We aimed to develop five deep learning models (DLMs) to identify aortic stenosis, aortic regurgitation, pulmonary regurgitation, tricuspid regurgitation, and mitral regurgitation. Between 2010 and 2021, 77,047 patients with echocardiography and 12-lead ECG performed within 7 days were identified from an academic medical center to provide DLM development (122,728 ECGs), and internal validation (7,637 ECGs). Additional 11,800 patients from a community hospital were identified to external validation. The ECGs were classified as with or without moderate-to-severe VHDs according to transthoracic echocardiography (TTE) records, and we also collected the other echocardiographic data and follow-up TTE records to identify new-onset valvular heart diseases. AI-ECG adjusted for age and sex achieved areas under the curves (AUCs) of >0.84, >0.80, >0.77, >0.83, and >0.81 for detecting aortic stenosis, aortic regurgitation, pulmonary regurgitation, tricuspid regurgitation, and mitral regurgitation, respectively. Since predictions of each DLM shared similar components of ECG rhythms, the positive findings of each DLM were highly correlated with other valvular heart diseases. Of note, a total of 37.5-51.7% of false-positive predictions had at least one significant echocardiographic finding, which may lead to a significantly higher risk of future moderate-to-severe VHDs in patients with initially minimal-to-mild VHDs. AI-ECG may be used as a large-scale screening tool for detecting VHDs and a basis to undergo an echocardiography.

Association between lung function and risk of microvascular diseases in patients with diabetes: A prospective cohort and Mendelian randomization study

Background and aimsTo investigate causal relationships of lung function with risks microvascular diseases among participants with diabetes, type 2 diabetes mellitus (T2DM) and type 1 diabetes mellitus (T1DM), respectively, in prospective and Mendelian randomization (MR) study. Methods and results14,617 participants with diabetes and without microvascular diseases at baseline from the UK Biobank were included in the prospective analysis. Of these, 13,421 had T2DM and 1196 had T1DM. The linear MR analyses were conducted in the UK Biobank with 6838 cases of microvascular diseases and 10,755 controls. Lung function measurements included forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). The study outcome was microvascular diseases, a composite outcome including chronic kidney diseases, retinopathy and peripheral neuropathy. During a median follow-up of 12.1 years, 2668 new-onset microvascular diseases were recorded. FVC (%predicted) was inversely associated with the risk of new-onset microvascular diseases in participants with diabetes (Per SD increment, adjusted HR = 0.86; 95%CI:0.83–0.89), T2DM (Per SD increment, adjusted HR = 0.86; 95%CI:0.82–0.90) and T1DM (Per SD increment, adjusted HR = 0.87; 95%CI: 0.79–0.97), respectively. Similar results were found for FEV1 (%predicted). In MR analyses, genetically predicted FVC (adjusted RR = 0.55, 95%CI:0.39–0.77) and FEV1 (adjusted RR = 0.48, 95%CI:0.28–0.83) were both inversely associated with microvascular diseases in participants with T1DM. No significant association was found in those with T2DM. Similar findings were found for each component of microvascular diseases. ConclusionThere was a causal inverse association between lung function and risks of microvascular diseases in participants with T1DM, but not in those with T2DM.

New-Onset Diabetes Mellitus after COVID-19: Combined Effects of SARS-CoV-2 Variants, Molecular Mimicry, and m6A RNA Methylation

Post-COVID syndrome, also known as long COVID, includes a range of symptoms that persist for months or even years after initial infection such as fatigue, shortness of breath, joint pain, chest pain, muscle aches, and heart palpitations, among others. In addition, long COVID is related with new-onset diseases such as diabetes mellitus. The association between SARS-CoV-2 infections and the development of diabetes mellitus is complex and not fully understood. Therefore, the objective of this article was to summarize the state of the art in possible mechanisms involved in the development of diabetes mellitus in the post-COVID-19 era, particularly the impact of SARS-CoV-2 variants on molecular mimicry, the role of viral m6A RNA methylation, and the potential associations between these factors. A better understanding of the combinatorial effects of these mechanisms is paramount for both clinicians and researchers alike because it could help tailor more effective treatment strategies, enhance patient care, and guide future research efforts.

Long-term health outcomes associated with hydration status.

Body water balance is determined by fundamental homeostatic mechanisms that maintain stable volume, osmolality and the composition of extracellular and intracellular fluids. Water balance is maintained by multiple mechanisms that continuously match water losses through urine, the skin, the gastrointestinal tract and respiration with water gains achieved through drinking, eating and metabolic water production. Hydration status is determined by the state of the water balance. Underhydration occurs when a decrease in body water availability, due to high losses or low gains, stimulates adaptive responses within the water balance network that are aimed at decreasing losses and increasing gains. This stimulation is also accompanied by cardiovascular adjustments. Epidemiological and experimental studies have linked markers of low fluid intake and underhydration - such as increased plasma concentration of vasopressin and sodium, as well as elevated urine osmolality - with an increased risk of new-onset chronic diseases, accelerated aging and premature mortality, suggesting that persistent activation of adaptive responses may be detrimental to long-term health outcomes. The causative nature of these associations is currently being tested in interventional trials. Understanding of the physiological responses to underhydration may help to identify possible mechanisms that underlie potential adverse, long-term effects of underhydration and inform future research to develop preventative and treatment approaches to the optimization of hydration status.

Анализ содержания катехоламинов и параметров липидного обмена у аборигенного и местного европеоидного населения Арктической зоны Российской Федерации

The study of fat metabolism and the levels of sympathoadrenal hormones in the indigenous population of the Arctic presently changing their lifestyle from nomadic to sedentary is undoubtedly of practical interest. The purpose of this article was to conduct a comparative analysis of the content of catecholamines, triglycerides and saturated fatty acids in the inhabitants of the Arctic zone of the Russian Federation, depending on their lifestyle (nomadic indigenous people, sedentary indigenous people, and local Russian population), age and sex. Materials and methods. The study involved 472 subjects: men and women of the first (men: 22–35 years old; women: 21–35 years old) and second (men: 36–60 years old; women: 36–55 years old) periods of adulthood, leading different lifestyles. The following were determined in the blood serum: triglyceride concentrations using the enzymatic method; level of saturated fatty acids (ƩSFA) using gas-liquid chromatography, followed by а calculation of the content of short-, medium- and long-chain saturated fatty acids (ƩSCFA, ƩMCFA, ƩLCFA). Urine levels of adrenaline and noradrenaline were determined by means of fluorimetry. Results. Regardless of their lifestyle, adult subjects, primarily women, showed high adrenaline values, low triglyceride concentrations and elevated ƩSFA. Correlation analysis established a negative association of adrenaline with ƩLCFA and ƩSFA in sedentary indigenous women aged 21–35 years and with ƩMCFA in those aged 36–55 years. In local Russian women aged 36–55 years, on the contrary, a positive association of noradrenaline with ƩSCFA, ƩMCFA, ƩLCFA and ƩSFA was found. No statistically significant correlations were identified in nomadic indigenous women. Unlike women, men had a correlation between adrenaline content and ƩMCFA only among local Russians: negative in 22–35-year-olds and positive in 36–60-year-olds with high noradrenaline levels. On the one hand, low triglyceride values and elevated ƩSFA among residents of the Arctic zone of the Russian Federation maintain the energy homeostasis of the body. On the other hand, they lead to overweight and obesity, which increases the risk of new-onset metabolic dysfunction-associated diseases, especially in women.

Comparing Artificial Intelligence-Enabled Electrocardiogram Models in Identifying Left Atrium Enlargement and Long-term Cardiovascular Risk

BackgroundThe role of P-wave in identifying left atrial enlargement (LAE) with the use of artificial intelligence (AI)–enabled electrocardiography (ECG) models is unclear. It is also unknown if AI-enabled single-lead ECG could be used as a diagnostic tool for LAE surveillance. We aimed to build AI-enabled P-wave and single-lead ECG models to identify LAE using sinus rhythm (SR) and non-SR ECGs, and compare the prognostic ability of severe LAE, defined as left atrial diameter ≥ 50 mm, assessed by AI-enabled ECG models vs echocardiography. MethodsThis retrospective study used data from 382,594 consecutive adults with paired 12-lead ECG and echocardiography performed within 2 weeks of each other at Chang Gung Memorial Hospital. UNet++ was used for P-wave segmentation. ResNet-18 was used to develop deep convolutional neural network–enabled ECG models for discriminating LAE. External validation was performed with the use of data from 11,753 patients from another hospital. ResultsThe AI-enabled 12-lead ECG model outperformed other ECG models for classifying LAE, but the single-lead ECG models also showed excellent performance at a left atrial diameter cutoff of 50 mm. AI-enabled ECG models had excellent and fair discrimination on LAE using the SR and the non-SR data set, respectively. Severe LAE identified by AI-enabled ECG models was more predictive of future cardiovascular disease than echocardiography; however, the cumulative incidence of new-onset atrial fibrillation and heart failure was higher in patients with echocardiography-severe LAE than with AI-enabled ECG-severe LAE. ConclusionsP-Wave plays a crucial role in discriminating LAE in AI-enabled ECG models. AI-enabled ECG models outperform echocardiography in predicting new-onset cardiovascular diseases associated with severe LAE.

Internet use, cardiometabolic multimorbidity, and death in older adults: a multi-cohort study spanning developing and developed countries

BackgroundInternet use is a double-edged sword for older adults’ health. Whether internet use can prevent cardiometabolic diseases and death in older adults remains controversial.MethodsFour cohorts across China, Mexico, the United States, and Europe were utilized. Internet use was defined using similar questions. Cardiometabolic diseases included diabetes, heart diseases, and stroke, with 2 or more denoting cardiometabolic multimorbidity. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale and Europe-depression scale. The competing risk analysis based on subdistribution hazard regression, random-effects meta-analysis, and mediation analysis were utilized.ResultsA total of 104,422 older adults aged 50 or older were included. Internet users (vs. digital exclusion) were at lower risks of diabetes, stroke, and death, with pooled sHRs (95% CIs) of 0.83 (0.74–0.93), 0.81 (0.71–0.92), and 0.67 (0.52–0.86), respectively, which remained significant in sensitivity analyses. The inverse associations of internet use with new-onset cardiometabolic diseases and death were progressively significant in Mexico, China, the United States, and Europe. For instance, older internet users in Europe were at 14-30% lower cardiometabolic risks and 40% lower risk of death. These associations were partially mediated by reduced depressive symptoms and were more pronounced in those with high socioeconomic status and women. Furthermore, patients with prior cardiometabolic conditions were at about 30% lower risk of death if they used the internet, which was also mediated by reduced depressive symptoms. However, certain cardiometabolic hazards of internet use in those aged < 65 years, with low socioeconomic status, men, and single ones were also observed.ConclusionEnhancing internet usage in older adults can reduce depressive symptoms and thus reduce the risks of cardiometabolic diseases and death. The balance of internet use, socioeconomic status, and health literacy should be considered when popularizing the internet in older adults.

Possible link between statin and iron deficiency anemia: A South Korean nationwide population-based cohort study.

An extensive evaluation of disease occurrence after statin use based on a "hypothesis-free" approach remains scarce. To examine the effect of statin use on the potential risk of developing diseases, a propensity score-matched cohort study was executed using data from the National Sample Cohort in South Korea. A total of 7847 statin users and 39,235 nonstatin users were included in the final analysis. The period of statin use was defined as our main time-dependent exposure and was divided into three periods: current, recent, and past. The main outcomes were defined as new-onset diseases with ≥100 events based on the International Statistical Classification of Diseases, 10th Revision. We calculated the adjusted hazard ratios and 95% confidence intervals (CIs) using Cox regression. We found that statin use significantly increased the risk of developing iron deficiency anemia up to 5.04 times (95% CI, 2.11 to 12.03). Therefore, the iron levels of patients using statins should be monitored carefully.

Increase in presentations with new-onset psychiatric disorders in a psychiatric emergency department in Berlin, Germany during the second wave of the COVID-19 pandemic - a retrospective cross-sectional study.

While numerous studies have identified an increase in symptoms of depression as well as anxiety and distress due to the COVID-19 pandemic, relatively few studies have investigated the new-onset of psychiatric diseases during the pandemic. This study focuses on the number of psychiatric new-onset diagnoses in a psychiatric emergency department (pED) in Berlin, Germany during the second wave of the pandemic (i.e. from 09/15/2020 to 03/01/2021 = COVID-19-period) compared to pre-pandemic times (09/15/2019 to 03/01/2020 = control period). We focused on diagnostic subgroups and performed logistic regression analysis to investigate potential risk groups based on covariables such as age, gender, homelessness, attending in police custody and familial relationship. Overall, there was a 59.7% increase in new-onset psychiatric diagnoses during the COVID-19-period. Increases in the following diagnoses were observed: new-onset of substance-related and addictive disorders (+192.5%), depressive disorders (+115.8%), schizophrenia spectrum and psychotic disorders (+113.3%) and anxiety disorders (+63.6%). These diagnostic subgroups, together with attending in police custody, were found to predict pED presentations with new-onset during the COVID-19-period. Interestingly, in the group of new-onset psychiatric diseases in the COVID-19-period, higher amounts of job loss and living alone as well as a relative decrease in familial relationships were observed. COVID-19 infections and post-COVID-19 syndrome are unlikely to have played a substantial role in the increase of new-onset diseases in this study. Conclusion: Our findings underline the role of indirect factors in new-onset of psychiatric diseases during the pandemic and should be a caveat for future pandemic control policies.

New-Onset Rheumatic Immune-Mediated Inflammatory Diseases Following SARS-CoV-2 Vaccinations until May 2023: A Systematic Review.

A comprehensive, up-to-date systematic review (SR) of the new-onset rheumatic immune-mediated inflammatory diseases (R-IMIDs) following COVID-19 vaccinations is lacking. Therefore, we investigated the demographics, management, and prognosis of new R-IMIDs in adults following SARS-CoV-2 vaccinations. A systematic literature search of Medline, Embase, Google Scholar, LitCovid, and Cochrane was conducted. We included any English-language study that reported new-onset R-IMID in adults following the post-COVID-19 vaccination. A total of 271 cases were reported from 39 countries between January 2021 and May 2023. The mean age of patients was 56 (range 18-90), and most were females (170, 62.5%). Most (153, 56.5%) received the Pfizer BioNTech COVID-19 vaccine. Nearly 50% of patients developed R-IMID after the second dose of the vaccine. Vasculitis was the most prevalent clinical presentation (86, 31.7%), followed by connective tissue disease (66, 24.3%). The mean duration between the vaccine's 'trigger' dose and R-IMID was 11 days. Most (220, 81.2%) received corticosteroids; however, 42% (115) received DMARDs such as methotrexate, cyclophosphamide, tocilizumab, anakinra, IV immunoglobulins, plasma exchange, or rituximab. Complete remission was achieved in 75 patients (27.7%), and 137 (50.6%) improved following the treatment. Two patients died due to myositis. This SR highlights that SARS-CoV-2 vaccines may trigger R-IMID; however, further epidemiology studies are required.

Incidence of New-onset Hypertension and New-onset Type 2 Diabetes during or after SARS-CoV-2 Infection.

Background: Considering the potential clinical and therapeutic implications, there is a need to determine whether or not COVID infection induces or unmasks new-onset/newly diagnosed hypertension/diabetes during the acute phase and post-COVID-19. Aim: In the current article, we discuss the current data at the intersection of COVID, hypertension, and COVID and diabetes, from prevalence, risk factors, and underlying mechanisms during an acute and post-COVID phase; focusing on new-onset hypertension and new onset type 2 diabetes. Method: We have performed a literature search via online databases such as PubMed/MEDLINE and Google Scholar from December 2019-August 2022. The data from various studies and review articles have been included. Results: Current evidence suggests the occurrence of new-onset hypertension and new onset type 2 diabetes in patients infected with the SARS-CoV-2 virus. Data also indicate a higher risk of negative outcomes in these patients. Conclusions: It is evident that the tenacity of these new-onset diseases post-COVID-19 is likely to have huge implications in terms of unexpected morbidity. Therefore, screening and follow-up of these patients seems reasonable. Clinicians shall have to deal with this evolving challenge and adequately equip themselves to address this facet of COVID-19 as well. Further data from various follow-up studies and registries like the CoviDIAB Project is required to be better equipped to propose exact recommendations for patients with NOD. On the contrary, more evidence is required for incidence and long-term sequelae for patients with new-onset hypertension. How to cite this article: Gupta A, Duggal R. Incidence of New-onset Hypertension and New-onset Type 2 Diabetes during or after SARS-CoV-2 Infection. J Assoc Physicians India 2023;71(10):78-82.

Post-marketing surveillance for the safety of the 9-valent human papillomavirus vaccine: a retrospective real-world study in China

ABSTRACTBackgroundThe 9-valent human papillomavirus (9vHPV) vaccine was introduced in China in 2018. This study was conducted to monitor the occurrence of new-onset autoimmune diseases (AIs) in Chinese women vaccinated with the 9vHPV vaccine and adverse pregnancy outcomes in infants born to mothers with inadvertent pregnancy exposure.Research design and methodsWomen who received the first dose of the 9vHPV vaccine at age 16–26 years in Ningbo between January 2019 and March 2021 were monitored in the Ningbo Regional Health Information Platform. New-onset cases of seven pre-specified AIs diagnosed within six months after vaccination were collected. Cases of stillbirth and 23 major congenital anomalies diagnosed within three months of birth in target infants were collected.ResultsA total of 102,670 doses of the 9vHPV vaccine were administered to 41,609 women who had received no other HPV vaccine. New-onset AIs were diagnosed in 36 women, comprising 21 Hashimoto’s, 11 Graves’, and 4 uveitis disease cases. Among 50 women with maternal vaccination exposure, no stillbirths were observed. One case of microtia was observed.ConclusionsIn this first post-marketing surveillance of the 9vHPV vaccine in China, no safety signals were identified when putting the results in context to published data.