Background Stroke survivors often have coexisting cardiometabolic and behavioral disturbances that may increase functional disability. Whether cumulative cardiometabolic-behavioral (CMB) burden is associated with ADL disability in a dose-response manner and whether depression mediates this association remain unclear. Objectives To assess the association between CMB burden and ADL/IADL disability in stroke survivors, identify contributing components, and evaluate depression as a mediator of ADL disability. Design Cross-sectional analysis of nationally representative survey data. Data source and methods We analyzed 1,144 stroke survivors from 70,190 participants across seven NHANES cycles. The CMB score (0–5) included central obesity, hypertension, short sleep, hyperglycemia/diabetes, and depression. ADL and IADL disability were defined as difficulty with ≥1 task. Analyses comprised survey-weighted logistic regression, restricted cubic splines, component-level and subgroup assessments, exploratory mediation, and population-attributable fraction estimation. Results ADL disability affected 66.0% of participants (survey-weighted; 70.0% unweighted); 82.3% had a CMB score ≥2. Disability prevalence rose progressively from 59.1% (score 0) to 83.8% (score 5) (P-trend = 0.007). Each one-point CMB increase conferred 32% higher odds of disability (OR 1.32, 95% CI 1.07-1.62, p = 0.013). The binary high-risk threshold (≥2 vs. <2) was directionally consistent but not statistically significant after adjustment (fully adjusted OR 2.06, 95% CI 1.01-4.19, p = 0.059). Depression was the strongest individual predictor (OR 11.48, 95% CI 4.62–28.49, p < 0.001). Exploratory mediation using the original 5-component score suggested depression accounted for 63.8% of the total CMB effect; however, re-analysis with a 4-component score excluding depression yielded a non-significant total effect (p = 0.112) and an unstable proportion-mediated estimate (45.1%, 95% CI -171.4% to 264.7%, p = 0.132), indicating inflation due to exposure–mediator overlap. PAF analysis identified CMB score ≥2 (PAF 27.8%, p = 0.010) and depression (PAF 9.7%, p < 0.001) as key population-level targets. Conclusions Higher CMB burden shows a graded association with post-stroke ADL disability. Depression was the strongest modifiable predictor. Mediation analysis could not precisely estimate the CMB effect mediated by depression after correcting for exposure–mediator overlap. Given its strong independent link to disability, depression screening and treatment should remain a rehabilitation priority.
Summary What is this summary about? This is a plain language summary of a review article that discusses evidence around the risk of developing type 1 diabetes (T1D) when someone has a personal or family history of other autoimmune diseases. What were the key messages in this summary? People may have a 2- to 12-times higher risk of developing T1D compared to the general population if they have other autoimmune conditions including: Addison’s disease, autoimmune thyroid disease (such as Hashimoto’s thyroiditis and Graves’ disease), autoimmune liver disease, celiac disease (gluten intolerance), inflammatory bowel disease and juvenile idiopathic arthritis. People also may have a 2- to 4-times higher risk of developing T1D compared to the general population if they have a family history of: Addison’s disease, autoimmune thyroid disease, autoimmune liver disease, celiac disease, pernicious anemia, inflammatory bowel disease, Sjögren’s syndrome, rheumatoid arthritis and systemic lupus erythematosus. Why is this information important? Most people with autoimmune diseases will not develop T1D. However, if healthcare providers (HCPs) understand who might have a higher risk for developing T1D, it could help HCPs to 1) monitor these people closely, 2) diagnose T1D earlier, and in some cases, 3) intervene with medications or treatments that can delay progression of T1D. The risk of experiencing dangerous health complications of diabetes can be reduced when T1D is diagnosed earlier. What is the purpose of this plain language summary? This summary will help you to understand more about: T1D and other autoimmune conditions, autoimmune conditions that are linked to a higher risk of developing T1D, assessing individual and family risk, and when to talk with HCPs about T1D screening.
Pheochromocytoma may rarely present with pheochromocytoma multisystem crisis (PMC), and disseminated intravascular coagulation (DIC) is an uncommon manifestation. Their coexistence with spontaneous tumor rupture is particularly unusual and creates major diagnostic and therapeutic difficulty. We report a 27-year-old woman with spontaneously ruptured pheochromocytoma complicated by PMC and DIC. She initially presented with hyperglycemia, high-anion-gap metabolic acidosis, and hyperlactatemia, raising concern for diabetic ketoacidosis. Her condition then evolved rapidly, with marked blood pressure lability, pulmonary edema, shock, acute kidney and liver injury, respiratory failure, and pheochromocytoma-associated stress cardiomyopathy. Imaging showed a hemorrhagic adrenal mass with retroperitoneal hematoma. Laboratory testing demonstrated thrombocytopenia, hypofibrinogenemia, prolonged prothrombin time (PT) and activated partial thromboplastin time (APTT), markedly elevated D-dimer, persistent abnormalities in thrombin-antithrombin III complex (TAT), plasmin–α2-plasmin inhibitor complex (PIC), tissue plasminogen activator–plasminogen activator inhibitor-1 complex (t-PAIC), and thrombomodulin (TM), and severe mixed hypocoagulability on thromboelastography. Plasma metanephrine, normetanephrine, and 3-methoxytyramine were markedly elevated, supporting the diagnosis of pheochromocytoma crisis. Because the immediate priority at presentation was control of active hemorrhage, transarterial embolization (TAE) was performed before pheochromocytoma had been fully recognized. Conventional preoperative optimization was not feasible because even minimal α-blockade worsened hemodynamics, and aggressive fluid loading risked aggravating pulmonary edema. The patient was managed with staged treatment including TAE, organ support, transfusion and coagulation-directed therapy, and delayed adrenalectomy after stabilization. She survived and subsequently underwent definitive surgery. This case shows that DIC, although rare in pheochromocytoma, may occur in the setting of tumor rupture and PMC. In unstable patients in whom immediate adrenalectomy and standard preoperative preparation are not possible, staged management with early TAE and delayed surgery may be a useful approach.
There is a great heterogeneity in disease characteristics, progression, manifestations, and treatment efficacy that make population-level strategies based on diabetes mellitus ineffective. Precision medicine provides ways to tackle this disparity by combining clinical, genetic, molecular, metabolic and behavioural data with the goal of personalized diagnosis, risk stratification or choosing treatment. This review covers a comprehensive and clinically relevant assessment of personalized diabetes care and the emerging research areas of the associated biomarkers, genomics, transcriptomics, proteomics, metabolomics, epigenomics, pharmacogenomics, nutrigenomics, continuous glucose monitoring, wearable technologies, digital health and artificial intelligence-based decision support systems. Molecular characterization, patient stratification, personalised pharmacotherapy, lifestyle intervention, and long-term digital monitoring is integrated with these technologies rather than being considered separate entities. The main focus is on the clinical and/or translational implications of these strategies, such as their current evidence strength and their limitations, population diversity, external validation, cost-effectiveness, data interoperability, privacy and healthcare implementation. Combining the multi-omics and real-time digital information with traditional clinical evaluation could make it possible to better manage diabetes in a more predictive, adaptive, patient-centred manner. Yet, future validation, standardized analysis tools, access, and tools to be designed into standard clinical practice are still vital to bringing precision diabetes strategies from novel technologies into practical care.
