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BACKGROUND: Reference intervals of thyroid-stimulating hormone (TSH) and free thyroxine (FT4) are statistically defined by the 2·5-97·5th percentiles, without accounting for potential risk of clinical outcomes. We aimed to define the optimal healthy ranges of TSH and FT4 based on the risk of cardiovascular disease and mortality. METHODS: This systematic review and individual participant data (IPD) meta-analysis identified eligible prospective cohorts through the Thyroid Studies Collaboration, supplemented with a systematic search via Embase, MEDLINE (Ovid), Web of science, the Cochrane Central Register of Controlled Trials, and Google Scholar from Jan 1, 2011, to Feb 12, 2017 with an updated search to Oct 13, 2022 (cohorts found in the second search were not included in the IPD). We included cohorts that collected TSH or FT4, and cardiovascular outcomes or mortality for adults (aged ≥18 years). We excluded cohorts that included solely pregnant women, individuals with overt thyroid diseases, and individuals with cardiovascular disease. We contacted the study investigators of eligible cohorts to provide IPD on demographics, TSH, FT4, thyroid peroxidase antibodies, history of cardiovascular disease and risk factors, medication use, cardiovascular disease events, cardiovascular disease mortality, and all-cause mortality. The primary outcome was a composite outcome including cardiovascular disease events (coronary heart disease, stroke, and heart failure) and all-cause mortality. Secondary outcomes were the separate assessment of cardiovascular disease events, all-cause mortality, and cardiovascular disease mortality. We performed one-step (cohort-stratified Cox models) and two-step (random-effects models) meta-analyses adjusting for age, sex, smoking, systolic blood pressure, diabetes, and total cholesterol. The study was registered with PROSPERO, CRD42017057576. FINDINGS: We identified 3935 studies, of which 53 cohorts fulfilled the inclusion criteria and 26 cohorts agreed to participate. We included IPD on 134 346 participants with a median age of 59 years (range 18-106) at baseline. There was a J-shaped association of FT4 with the composite outcome and secondary outcomes, with the 20th (median 13·5 pmol/L [IQR 11·2-13·9]) to 40th percentiles (median 14·8 pmol/L [12·3-15·0]) conveying the lowest risk. Compared with the 20-40th percentiles, the age-adjusted and sex-adjusted hazard ratio (HR) for FT4 in the 80-100th percentiles was 1·20 (95% CI 1·11-1·31) for the composite outcome, 1·34 (1·20-1·49) for all-cause mortality, 1·57 (1·31-1·89) for cardiovascular disease mortality, and 1·22 (1·11-1·33) for cardiovascular disease events. In individuals aged 70 years and older, the 10-year absolute risk of composite outcome increased over 5% for women with FT4 greater than the 85th percentile (median 17·6 pmol/L [IQR 15·0-18·3]), and men with FT4 greater than the 75th percentile (16·7 pmol/L [14·0-17·4]). Non-linear associations were identified for TSH, with the 60th (median 1·90 mIU/L [IQR 1·68-2·25]) to 80th percentiles (2·90 mIU/L [2·41-3·32]) associated with the lowest risk of cardiovascular disease and mortality. Compared with the 60-80th percentiles, the age-adjusted and sex-adjusted HR of TSH in the 0-20th percentiles was 1·07 (95% CI 1·02-1·12) for the composite outcome, 1·09 (1·05-1·14) for all-cause mortality, and 1·07 (0·99-1·16) for cardiovascular disease mortality. INTERPRETATION: There was a J-shaped association of FT4 with cardiovascular disease and mortality. Low concentrations of TSH were associated with a higher risk of all-cause mortality and cardiovascular disease mortality. The 20-40th percentiles of FT4 and the 60-80th percentiles of TSH could represent the optimal healthy ranges of thyroid function based on the risk of cardiovascular disease and mortality, with more than 5% increase of 10-year composite risk identified for FT4 greater than the 85th percentile in women and men older than 70 years. We propose a feasible approach to establish the optimal healthy ranges of thyroid function, allowing for better identification of individuals with a higher risk of thyroid-related outcomes. FUNDING: None.

ObjectiveFew prospective studies have assessed whether individuals with subclinical thyroid dysfunction are more likely to develop diabetes, with conflicting results. In this study, we conducted a systematic review of the literature and an individual participant data analysis of multiple prospective cohorts to investigate the association between subclinical thyroid dysfunction and incident diabetes.MethodsWe performed a systematic review of the literature in Medline, Embase, and the Cochrane Library from inception to February 11, 2022. A two-stage individual participant data analysis was conducted to compare participants with subclinical hypothyroidism and subclinical hyperthyroidism vs euthyroidism at baseline and the adjusted risk of developing diabetes at follow-up.ResultsAmong 61 178 adults from 18 studies, 49% were females, mean age was 58 years, and mean follow-up time was 8.2 years. At the last available follow-up, there was no association between subclinical hypothyroidism and incidence of diabetes (odds ratio (OR) = 1.02, 95% CI: 0.88-1.17, I2 = 0%) or subclinical hyperthyroidism and incidence of diabetes (OR = 1.03, 95% CI: 0.82-1.30, I2 = 0%), in age- and sex-adjusted analyses. Time-to-event analysis showed similar results (hazard ratio for subclinical hypothyroidism: 0.98, 95% CI: 0.87-1.11; hazard ratio for subclinical hyperthyroidism: 1.07, 95% CI: 0.88-1.29). The results were robust in all sub-group and sensitivity analyses.ConclusionsThis is the largest systematic review and individual participant data analysis to date investigating the prospective association between subclinical thyroid dysfunction and diabetes. We did not find an association between subclinical thyroid dysfunction and incident diabetes. Our results do not support screening patients with subclinical thyroid dysfunction for diabetes.Significance statementEvidence is conflicting regarding whether an association exists between subclinical thyroid dysfunction and incident diabetes. We therefore aimed to investigate whether individuals with subclinical thyroid dysfunction are more prone to develop diabetes in the long run as compared to euthyroid individuals. We included data from 18 international cohort studies with 61 178 adults and a mean follow-up time of 8.2 years. We did not find an association between subclinical hypothyroidism or subclinical hyperthyroidism at baseline and incident diabetes at follow-up. Our results have clinical implications as they neither support screening patients with subclinical thyroid dysfunction for diabetes nor treating them in the hope of preventing diabetes in the future.

BackgroundIn non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC).MethodsFor the first aim we systematically searched in MEDLINE, EMBASE, and Cochrane from inception to February 2021 to identify published IPD-MAs of NRSs that adjusted for baseline outcome measures in the analysis of continuous outcomes. For the second aim, we applied analysis of covariance (ANCOVA), change score, propensity score and the naïve approach (ignores the baseline outcome data) in IPD-MA from NRSs on the association between subclinical hyperthyroidism and depressive symptoms and renal function. We estimated the study and meta-analytic mean difference (MD) and relative standard error (SE). We used both fixed- and random-effects MA.ResultsTen of 18 (56%) of the included studies used the change score method, seven (39%) studies used ANCOVA and one the propensity score (5%). The study estimates were similar across the methods in studies in which groups were balanced at baseline with regard to outcome variables but differed in studies with baseline imbalance. In our empirical examples, ANCOVA and change score showed study results on the same direction, not the propensity score. In our applications, ANCOVA provided more precise estimates, both at study and meta-analytical level, in comparison to other methods. Heterogeneity was higher when change score was used as outcome, moderate for ANCOVA and null with the propensity score.ConclusionANCOVA provided the most precise estimates at both study and meta-analytic level and thus seems preferable in the meta-analysis of IPD from non-randomized studies. For the studies that were well-balanced between groups, change score, and ANCOVA performed similarly.

Abstract Background Hashimoto's thyroiditis is the most important cause of hypothyroidism. It is a systemic disease that can even affect the cardiovascular system, by accelerating the atherosclerotic process. Aim of this study was to examine whether autoimmune thyroiditis has an effect on the intima-media thickness of the common carotid artery (IMT-CCT), independently of the thyroid function and well-known cardiovascular risk factors. Hashimoto's thyroiditis is a systemic disease. The aim is to examine whether autoimmune thyroiditis and adiposity can effect carotid IMT independently of thyroid hormones and cardiovascular risk factors. Methods A total of 104 obese women (BMI ≥ 25.0 kg/m-2), with FT3 and FT4 serum levels in the normal range and TSH levels < 4.5 μU/ml, were investigated. None of these patients was taking any kind of drug influencing thyroid function. Measurements were made of the IMT-CCT, BMI, waist circumference, blood pressure levels, as well as fasting TSH, FT3, FT4, anti-thyroid antibodies, insulin, fasting glycemia, triglycerides, total and HDL-cholesterol serum concentrations. Results Of the 104 women, 30 (28.8%) were affected by autoimmune thyroiditis. Significantly higher values of IMT-CCT (p < 0.05), TSH (p < 0.05), and triglycerides (p < 0.05) were obtained, and significantly lower values of FT4 (p < 0.05), in patients with Hashimoto's thyroiditis as compared to those with a normal thyroid function. When examining the whole group together, at multiple regression analysis Hashimoto's thyroiditis maintained a positive association with the IMT (p < 0.001), independently of age, hypertension, BMI, and the fasting serum levels of TSH, FT3, FT4, insulin, fasting glycemia, triglycerides, total and HDL-cholesterol levels. Conclusions The present study shows that Hashimoto's thyroiditis is associated to an increased IMT only in overweight and obese, independently of the thyroid function, BMI and cardiovascular risk factors. These results suggest that Hashimoto's thyroiditis is a marker of evolution of the atherosclerosis if combined to adiposity.

BackgroundChronic kidney disease (CKD) is frequently accompanied by thyroid hormone dysfunction. It is currently unclear whether these alterations are the cause or consequence of CKD. This study aimed at studying the effect of thyroid hormone alterations on renal function in cross-sectional and longitudinal analyses in individuals from all adult age groups.MethodsIndividual participant data (IPD) from 16 independent cohorts having measured thyroid stimulating hormone, free thyroxine levels and creatinine levels were included. Thyroid hormone status was defined using clinical cut-off values. Estimated glomerular filtration rates (eGFR) were calculated by means of the four-variable Modification of Diet in Renal Disease (MDRD) formula. For this IPD meta-analysis, eGFR at baseline and eGFR change during follow-up were computed by fitting linear regression models and linear mixed models in each cohort separately. Effect estimates were pooled using random effects models.ResultsA total of 72 856 individuals from 16 different cohorts were included. At baseline, individuals with overt hypothyroidism (n = 704) and subclinical hypothyroidism (n = 3356) had a average (95% confidence interval) -4.07 (-6.37 to -1.78) and -2.40 (-3.78 to -1.02) mL/min/1.73 m2 lower eGFR as compared with euthyroid subjects (n = 66 542). In (subclinical) hyperthyroid subjects (n = 2254), average eGFR was 3.01 (1.50-4.52) mL/min/1.73 m2 higher. During 329 713 patient years of follow-up, eGFR did not decline more rapidly in individuals with low thyroid function compared with individuals with normal thyroid function.ConclusionsLow thyroid function is not associated with a deterioration of renal function. The cross-sectional association may be explained by renal dysfunction causing thyroid hormone alterations.

The integration of artificial intelligence (AI) in healthcare management marks a significant advance in technological innovation, promising transformative effects on healthcare processes, patient care, and the efficacy of emergency responses. The scientific novelty of the study lies in its integrated approach, combining systematic review and predictive algorithms to provide a comprehensive understanding of AI's role in improving healthcare management across different contexts. Covering the period between 2019 and 2023, which includes the global challenges posed by the COVID-19 pandemic, this research investigates the operational, strategic, and emergency response implications of AI adoption in the healthcare sector. It further examines how the impact of AI varies across temporal and geographical contexts. The study addresses two main research objectives: to explore how AI influences healthcare management in operational, strategic, and emergency response domains, and to identify variations in the impact of AI on healthcare management based on temporal and geographical contexts. Utilizing an integrated approach, we compared various prediction algorithms, including logistic regression, and interpreted the results through SHAP (SHapley Additive exPlanations) analysis. The findings reveal five key thematic areas: AI's role in enhancing quality assurance, resource management, technological innovation, security, and the healthcare response to the COVID-19 pandemic. The study highlights AI's positive influence on operational efficiency and strategic decision making, while also identifying challenges related to data privacy, ethical considerations, and the need for ongoing technological integration. These insights provide opportunities for targeted interventions to optimize AI's impact in current and future healthcare landscapes. In conclusion, this work contributes to a deeper understanding of the role of AI in healthcare management and provides insights for policymakers, healthcare professionals, and researchers, offering a roadmap for addressing both the opportunities and challenges posed by AI integration in the healthcare sector. [ABSTRACT FROM AUTHOR]

BackgroundAtrial fibrillation (AF) is a highly prevalent disorder leading to heart failure, stroke, and death. Enhanced understanding of modifiable risk factors may yield opportunities for prevention. The risk of AF is increased in subclinical hyperthyroidism, but it is uncertain whether variations in thyroid function within the normal range or subclinical hypothyroidism are also associated with AF.MethodsWe conducted a systematic review and obtained individual participant data from prospective cohort studies that measured thyroid function at baseline and assessed incident AF. Studies were identified from MEDLINE and EMBASE databases from inception to July 27, 2016. The euthyroid state was defined as thyroid-stimulating hormone (TSH) 0.45 to 4.49 mIU/L, and subclinical hypothyroidism as TSH 4.5 to 19.9 mIU/L with free thyroxine (fT4) levels within reference range. The association of TSH levels in the euthyroid and subclinical hypothyroid range with incident AF was examined by using Cox proportional hazards models. In euthyroid participants, we additionally examined the association between fT4 levels and incident AF.ResultsOf 30 085 participants from 11 cohorts (278 955 person-years of follow-up), 1958 (6.5%) had subclinical hypothyroidism and 2574 individuals (8.6%) developed AF during follow-up. TSH at baseline was not significantly associated with incident AF in euthyroid participants or those with subclinical hypothyroidism. Higher fT4 levels at baseline in euthyroid individuals were associated with increased AF risk in age- and sex-adjusted analyses (hazard ratio, 1.45; 95% confidence interval, 1.26-1.66, for the highest quartile versus the lowest quartile of fT4; P for trend ≤0.001 across quartiles). Estimates did not substantially differ after further adjustment for preexisting cardiovascular disease.ConclusionsIn euthyroid individuals, higher circulating fT4 levels, but not TSH levels, are associated with increased risk of incident AF.

Aims: Patients with heart failure (HF) remain often undertreated for multiple reasons, including treatment inertia, contraindications, and intolerance. The OPTIimal PHARMacological therapy for patients with Heart Failure (OPTIPHARM‐HF) registry is designed to evaluate the prevalence of evidence‐based medical treatment prescription and titration, as well as the causes of its underuse, in a broad real‐world population of consecutive patients with HF across the whole ejection fraction spectrum and among different clinical phenotypes. Methods: The OPTIPHARM‐HF registry (NCT06192524) is a prospective, multicenter, observational, national study of adult patients with symptomatic HF, as defined by current international guidelines, regardless of ejection fraction. Both outpatients and inpatients with chronic and acute decompensated HF will be recruited. The study will enroll up to 2500 patients with chronic HF at approximately 35 Italian HF centres. Patients will be followed for a maximum duration of 24 months. The primary objective of the OPTIPHARM‐HF registry is to assess prescription and adherence to evidence‐based guideline‐directed medical therapy (GDMT) in patients with HF. The primary outcome is to describe the prevalence of GDMT use according to target guideline recommendation. Secondary objectives include implementation of comorbidity treatment, evaluation of sequence of treatment introduction and up‐titration, description of GDMT implementation in the specific HF population, main causes of GDMT underuse, and assessment of cumulative rate of cardiovascular events. Conclusion: The OPTIPHARM‐HF registry will provide important implications for improving patient care and adoption of recommended medical therapy into clinical practice among HF patients. [ABSTRACT FROM AUTHOR]

This study delves into hospital mobility within the Italian regions of Apulia and Emilia-Romagna, interpreting it as an indicator of perceived service quality. Utilizing logistic regression alongside other machine learning techniques, we analyze the impact of structural, operational, and clinical variables on patient perceptions of quality, thus influencing their healthcare choices. The analysis of mobility trends has uncovered significant regional differences, emphasizing how the regional context shapes perceived service quality. To further enhance the analysis, SHAP (SHapley Additive exPlanations) values have been integrated into the logistic regression model. These values quantify the specific contributions of each variable to the perceived quality of service, significantly improving the interpretability and fairness of evaluations. A methodological innovation of this study is the use of these SHAP impact scores as weights in the data envelopment analysis (DEA), facilitating a comparative efficiency analysis of healthcare facilities that is both weighted and normative. The combination of logistic regression and SHAP-weighted DEA provides a deeper understanding of perceived quality dynamics and offers essential insights for optimizing the distribution of healthcare resources. This approach underscores the importance of data-driven strategies to develop more equitable, efficient, and patient-centered healthcare systems. This research significantly contributes to the understanding of perceived quality dynamics within the healthcare context and promotes further investigations to enhance service accessibility and quality, leveraging machine learning as a tool to increase the efficiency of healthcare services across diverse regional settings. These findings are pivotal for policymakers and healthcare system managers aiming to reduce regional disparities and promote a more responsive and personalized healthcare service. [ABSTRACT FROM AUTHOR]

For a long time, the study of heart failure focused on single heart chamber disease. There is, instead, growing attention on the interplay between the atria and the ventricles during the cardiac cycle and on the consequences of an altered chamber coupling on global heart performance and heart failure. This review aimed to explore the principles of atrioventricular (AV) function and coupling of the left heart and the consequences that their disruption could have in several diseases. Furthermore, we will examine echocardiographic tips for analyzing the chamber function and the AV coupling. Finally, we will explore the most recent pharmacological acquisitions and the device therapies we have for use. [ABSTRACT FROM AUTHOR]

BackgroundAmerican College of Cardiology/American Heart Association guidelines for the diagnosis and management of heart failure recommend investigating exacerbating conditions such as thyroid dysfunction, but without specifying the impact of different thyroid-stimulation hormone (TSH) levels. Limited prospective data exist on the association between subclinical thyroid dysfunction and heart failure events.Methods and resultsWe performed a pooled analysis of individual participant data using all available prospective cohorts with thyroid function tests and subsequent follow-up of heart failure events. Individual data on 25 390 participants with 216 248 person-years of follow-up were supplied from 6 prospective cohorts in the United States and Europe. Euthyroidism was defined as TSH of 0.45 to 4.49 mIU/L, subclinical hypothyroidism as TSH of 4.5 to 19.9 mIU/L, and subclinical hyperthyroidism as TSH