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PubMed2025

Selective Neurectomy Outcomes in Synkinesis Patients: The First 56 Consecutive Primary Cases with Minimum 1-Year Follow-Up.

INTRODUCTION: Evaluation of 1-year follow-up outcomes after selective neurectomy (SN) is essential to confirm sustained improvements in patient-reported, clinician-graded, and objective results. OBJECTIVE: To assess outcomes of SN in synkinesis, using patient-reported outcomes (VAS), clinician-graded assessments (eFACE), and objective evaluations. METHODS: Synkinesis patients who underwent SN were included in the study. Patients with less than 12 months of follow-up were excluded. Visual analog scale (VAS) was assessed as patient-reported outcomes. The Electronic Clinician-Graded Facial Function Scale (eFACE) was also assessed. Objective evaluations were carried out via Emotrics Software. RESULTS: Fifty-six primary cases were included, with a mean patient age at surgery of 33.8 ± 11.0 years. Of these, 45 patients (80.3%) were female. The average duration between paralysis and surgery was 124.3 ± 103.3 months. The mean duration between surgery and evaluation was 19.7 ± 7.5 months (mean/SD). Preoperative and postoperative mean aggregate VAS scores were 35.5 ± 19.8 and 67.7 ± 16.5, respectively (p < 0.001). However, two patients (3.7%) reported worsening in moving food around in the mouth, and four patients (7.5%) reported worsening in drooling. All postoperative eFACE subscores except periocular demonstrated significant improvement (p < 0.001). Emotrics analysis demonstrated improvement in all postoperative symmetry parameters, except in the periocular region. CONCLUSIONS: SN improves patient-reported outcomes, clinician-graded assessments, and objective measurements. However, periocular outcomes remain suboptimal, and functional deficits should be carefully considered.

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PubMed2026

Effectiveness of exercise-based prehabilitation on pre and postoperative outcomes of patients undergoing cardiac surgery-An umbrella review of systematic reviews.

AIMS: Individuals undergoing cardiac surgery are becoming older, frailer, and less mobile. Prehabilitation has shown to improve postoperative outcomes by optimizing preoperative physical function. This umbrella review aims to pool the systematic reviews assessing the effectiveness of exercise-based prehabilitation in cardiac surgery. METHODS AND RESULTS: The review followed the PRIOR checklist. PubMed, Embase, CINAHL, Cochrane library, Scopus, Web of science, ProQuest NAHD, ProQuest HMC, Open Grey and MedNar were searched using relevant keywords from inception to 16th December, 2024. Two reviewers screened and extracted data from the included reviews and assessed primary study overlap with the corrected covered area. Methodological quality of the reviews was evaluated with the A MeaSurement Tool to Assess systematic Reviews-2 scale. Certainty of evidence was assessed using a previously developed criteria for overview of reviews. Six systematic reviews with 30 unique trials and 6705 participants were included. The interventions assessed included breathing exercises, inspiratory muscle training, and exercise training. Prehabilitation reduced length of hospital stay, postoperative pulmonary complications, and clinically improved functional capacity with a very low to moderate certainty of evidence. However, there was uncertainty regarding the effects pertaining to adverse events and quality of life. The methodological quality of all reviews was critically low. The primary trials scored poorly in the domains of selection and detection bias. CONCLUSION: Exercise-based prehabilitation might reduce length of hospital stay and postoperative complications, and improve functional capacity. However, the quality of evidence is poor, and individual discretion is required before implementing them into practice. REGISTRATION: PROSPERO: CRD42023480100.

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PubMed2026

PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.

BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.

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PubMed2026

Affective reactivity to a remote computer-based Trier Social Stress Test during a planned quit attempt: associations with short-term cigarette smoking lapse risk.

BACKGROUND: The Trier Social Stress Test (TSST) elicits affective responses and has been linked to smoking behavior. However, its remote use during a planned quit attempt-when stress reactivity may influence early lapse-remains understudied. OBJECTIVE: To quantify affective reactivity to a remotely administered TSST on a planned quit date following overnight abstinence and evaluate associations with cigarette use and lapse within 48 h. METHODS: This secondary analysis used data from a randomized controlled trial of adult smokers completing a remotely administered TSST following overnight nicotine abstinence. Urge, anxiety, and stress were assessed using visual analog scales and summarized using area under the curve (AUC) metrics. Smoking outcomes included cigarette count and lapse within 48 h. Associations were estimated using generalized estimating equations. RESULTS: In adjusted models, anxiety reactivity-but not urge or stress-was associated with cigarette count and lapse. Greater anxiety exposure (AUCtot) and change above baseline (AUCab) were associated with higher cigarette count (IRR=1.0004, 95%CI:1.0002-1.001, p=.002; IRR=1.01, 95%CI: 1.002-1.01, p=.002) and increased odds of lapse (OR=1.001, 95%CI: 1.0001-1.002, p=.03; OR=1.02, 95%CI: 1.001-1.03, p=.03). Effect sizes were small. CONCLUSIONS: Anxiety reactivity under nicotine deprivation was associated with increased cigarette use and lapse 48 h post quit attempt, suggesting individual differences in stress-evoked anxiety may serve as a behavioral marker for early lapse. Remote TSST administration appears feasible for eliciting affective responses on a quit date.

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PubMed2026

Teach-Back in Clinical Communication: A Systematic Review and Meta-analysis.

BACKGROUND: Teach-back has been identified as a high-quality clinical communication strategy. Our aim was to synthesize current literature on teach-back effectiveness. METHODS: We searched MEDLINE, Embase, and CINAHL Complete databases to identify relevant studies published between 2018 and 2026. We also included pre-2018 studies identified in prior systematic reviews. Studies were eligible for inclusion if they involved adult patients and/or care partners, delivered teach-back in a single encounter, had a comparator group, and reported proximal/intermediate patient outcomes (as defined in our conceptual model). Two independent investigators screened each citation at the title/abstract and full-text levels and assessed risk of bias. Study characteristics and results were extracted. When meta-analysis was performed, we used standardized mean differences (SMD) to estimate summary effects. We assessed certainty of evidence (COE) using Grading of Recommendations Assessment, Development and Evaluation (GRADE) domains. RESULTS: Our systematic review included 18 randomized controlled trials (RCTs) involving 1985 participants. Across 9 RCTs assessing knowledge acquisition, conceptual inconsistencies precluded meta-analysis. Overall, there was no clear pattern of the effect of teach-back on knowledge (very low COE). In a meta-analysis of 5 RCTs assessing self-efficacy (416 participants), we found that teach-back interventions led to a large increase in self-efficacy relative to usual care (SMD = 2.40; 95%CI 0.37-4.44) (very low COE). In a meta-analysis of 7 RCTs assessing adherence to health behaviors (571 participants), teach-back interventions led to a large increase in adherence (SMD = 1.04; 95%CI 0.45-1.64) (low COE). Meta-analyses for both self-efficacy and adherence had large confidence intervals that ranged from small to large effect sizes and had substantial heterogeneity. DISCUSSION: In this systematic review and meta-analysis, we did not identify a clear benefit of teach-back on knowledge acquisition but did find evidence that teach-back improves self-efficacy and self-reported, short-term adherence to health behaviors.

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PubMed2026

Time to subsequent therapy (TTST) as an endpoint in clinical studies: development of standardized documentation of subsequent therapy through systematic literature review, expert interviews, and Delphi survey.

BACKGROUND: The endpoint Time to Subsequent Therapy (TTST) is an intermediate endpoint used in research and regulatory assessments. TTST denotes initiation of subsequent therapy and is a clearly definable, clinically relevant event for healthcare professionals. However, it has not been systematically established to which extent TTST is subjectively meaningful to patients. The objective of this study was to define TTST as a patient-relevant intermediate endpoint. METHODS: The study examined five oncological indications (breast cancer, prostate cancer, melanoma, multiple myeloma, and non-small cell lung cancer) using a systematic literature review, analysis of case report forms used in international randomized controlled trials, review of German Federal Joint Committee (G-BA) documents, semi-structured interviews and a two-stage Delphi survey with healthcare professionals, patients, and relatives. RESULTS: A total of 35 individuals participated in qualitative interviews. Most of them rated TTST as particularly significant. The Delphi Survey included 264 interviewees in round one, and 117 in round two. Patient-relevance of TTST was confirmed by 81% of respondents (95% confidence interval 76%, 85%). Nine treatment scenarios that justify TTST were identified. To capture patient-relevance, prospective collection of reasons for and consequences of therapy change are required. A checklist with standardized response formats plus free-text fields was developed: a comprehensive master checklist for flexible, complete documentation and a short version focused on therapy change-specific items. CONCLUSIONS: TTST is an intermediate endpoint whose systematic documentation of characteristics demonstrating patient-relevance can be standardized in research and clinical practice using the developed checklists.

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PubMed2026

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

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PubMed2026

Biomonitoring of industrial heavy metal pollution via enzymatic and metabolic responses in desert ants (Cataglyphis savignyi) and beetles (Tentyrum sp) as bioindicators.

The current work seeks to evaluate the effectiveness of Cataglyphis saviginyi and Tentyrum sp as indicators of pollution in the city's main industrial regions by analyzing their enzymatic activity and primary metabolites. Soil samples were collected at each site under investigation to analyze soil characteristics and heavy metal content. C. saviginyi and Tentyrum sp were collected across four consecutive seasons (2023-2024) to investigate enzymatic (GPT, GOT, ALP, ACP, LDH) and metabolic (lipid, protein, carbohydrate) biomarkers. The physicochemical properties of the soil differed substantially between the industrial areas and the control site. Soil heavy metal buildup was highest at industrial sites (1 and 4) compared to the control site, with the order being Zn > Cr > Cd > Cu. Heavy metal pollution indices were determined. Increased industrial activity from metal industries, ceramics, and chemical painting companies defines this area, as seen by the high Cdeg, mCd, PI, and PLI values derived for industrial sites 1 and 4. While C. saviginyi and Tentyrum sp deconcentrated and released Cr, Cd, and Zn into the soil via the biological accumulation factor (BAF), Cu acted as a macro-concentrator. Compared with the control site, industrial environments were shown to increase levels of GPT, GOT, LDH, ACP, protein, and carbohydrates in C. saviginyi. However, lipid and ALP activity was suppressed. at industrial sites, Tentyrum sp carbohydrate content was higher than at control sites, but GPT, GOT, ALP, ACP, LDH, protein, and lipid activities were all suppressed. Consequently, enzymatic and metabolic biomarkers proved to be sensitive indicators for assessing industrial heavy metal pollution in desert ecosystems.

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PubMed2026

Beyond multidimensionality: a systematic review of recurrent frailty archetypes in community-dwelling older adults.

BACKGROUND: Frailty is a clinically heterogeneous geriatric syndrome commonly summarised using physical or multidomain severity scores. Whether person-centred analyses identify recurring within-frailty configurations has not been systematically examined in community-dwelling older adults. METHODS: We searched PubMed, Embase, MEDLINE, and CINAHL (January 2000-November 2025) for cross-sectional studies using latent class, latent profile, or analogous clustering methods to derive frailty subgroups. Quality was assessed using the AHRQ checklist and a purpose-built appraisal of person-centred model reporting. Study-derived classes were mapped in duplicate to a structured archetype framework developed through comparison of class-defining features across studies. RESULTS: Fourteen reports representing 12 independent datasets from eight countries were included. Six configurations were identified: minimally impaired reference, mobility-physical, nutritional-metabolic, cognitive-predominant, combined cognitive-physical, and psychosocial/mood-predominant. Convergence was measurement-dependent. The reference and mobility-physical configurations recurred across physical-only and multidomain indicator sets, while the combined cognitive-physical configuration appeared across several multidomain frameworks but required cognition to be measured. The remaining configurations emerged only when their defining domains were included. Evidence of prognostic value beyond aggregate frailty severity came from one deficit-index study. Collapsing shared-provenance reports and excluding the boundary-eligible study did not alter recurrence; excluding the Croatian dataset left five configurations recurrent, with the cognitive-predominant configuration supported by one independent dataset. CONCLUSIONS: Person-centred analyses identify recurring within-frailty configurations, but their apparent stability is partly measurement-dependent. A five-configuration core persisted after exclusion of the Croatian dataset, whereas the cognitive-predominant configuration remained weakly replicated. Harmonised indicators and rigorous external validation are needed before clinical application.

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PubMed2026

Effectiveness of Multidomain Cardiac Rehabilitation After Myocardial Infarction by Patient Frailty: Prespecified Subgroup Analysis of the PIpELINe Trial.

BACKGROUND: Frailty is common among older patients surviving myocardial infarction, is associated with adverse outcomes, and is often perceived as a barrier to cardiac rehabilitation (CR). The aim of this study is to determine whether frailty influences prognosis after myocardial infarction, and whether frailty modifies the clinical benefit of multidomain CR. METHODS: We performed a prespecified subgroup analysis of the PIpELINe (Physical Activity Intervention in Elderly Patients With Myocardial Infarction) randomized clinical trial conducted in Italy, which enrolled 512 patients aged ≥65 years recovering from myocardial infarction and randomized them in a 2:1 ratio to CR or usual care. Frailty was assessed using the Fried Frailty Phenotype, and patients were categorized as nonfrail (robust) or prefrail/frail. Time-to-event outcomes were analyzed using Kaplan-Meier estimates and Cox proportional hazards models, including treatment-by-frailty interaction terms to evaluate effect modification of the multidomain CR. The primary outcome was a composite of cardiovascular death or unplanned hospitalization for cardiovascular causes within 1 year after randomization. RESULTS: Overall, 350 patients (68.4%) were classified as prefrail/frail, of whom 232 were randomized to intervention arm (66%). Frail patients were older (median age, 80 [75-85] years) and more frequently female (41.7% versus 24.7%). Compared with robust patients, prefrail/frail patients had a higher risk of the primary outcome (16 [9.9%] versus 62 [17.7%]; hazard ratio, 1.59 [95% CI, 0.89-2.82]; adjusted P=0.117). Among prefrail/frail patients, assignment to multidomain CR was associated with a lower risk of the primary outcome compared with usual care (hazard ratio, 0.57 [95% CI, 0.34-0.94]; P=0.028), with no statistically significant interaction in the treatment effect on the primary end point (P=0.57). CONCLUSIONS: Among older patients recovering from myocardial infarction, frailty is associated with worse prognosis but does not diminish the benefit of multidomain CR. These findings support the use of frailty assessment to guide rather than limit access to CR. REGISTRATION: ClinicalTrials.gov; Unique identifier: NCT04183465.

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PubMed2026

ESC quality indicators for post-myocardial infarction care: transition and chronic coronary syndrome phases.

AIMS: We aimed to develop the European Society of Cardiology (ESC) quality indicators (QIs) for myocardial infarction (MI), from 1 year after hospital discharge, corresponding to transition to the chronic coronary syndrome phases. METHODS AND RESULTS: We collaborated with the European Association of Preventive Cardiology (EAPC) and developed QIs for the long-term management of patients following MI. We applied the ESC methodology for QI development by (i) determining key domains of post-MI care; (ii) developing candidate QIs by performing a systematic review of the literature, and (iii) selecting the final set of QIs using a modified Delphi approach. In total, 18 QIs were identified across seven domains of care including (i) structural framework, (ii) risk assessment and follow-up, (iii) pharmacological management, (iv) rehabilitation, behavioural, and preventive interventions, (v) coronary revascularization, (vi) clinical outcomes, and (vii) patient-reported outcomes. CONCLUSION: We present the ESC QIs from 1 year after hospitalization for MI, to standardize and address gaps in care for this high-risk group. These QIs are supported by evidence from contemporary literature, endorsed by expert consensus, and aligned with the 2024 ESC guidelines on the management of chronic coronary syndromes. LAY SUMMARY: Measures to evaluate and improve the long-term management of patients following a heart attack are needed. In this paper, we identified key aspects of care that can help clinicians, decision-makers and patients improve the quality of care, from one year after a heart attack onwards, and help address inequalities and variations in clinical practice.

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PubMed2026

Enhanced risk stratification in hypertrophic cardiomyopathy through the integration of extracellular volume fraction on cardiovascular magnetic resonance.

AIMS: This study investigated the incremental prognostic value of cardiovascular magnetic resonance (CMR)-derived extracellular volume fraction (ECV), a marker of diffuse interstitial fibrosis, beyond late gadolinium enhancement (LGE) in hypertrophic cardiomyopathy (HCM). METHODS AND RESULTS: We analysed 990 consecutive HCM patients (median age 58 years, male 68.3%) who underwent CMR between 2012 and 2024. LGE and global ECV were quantified, and their associations with the primary endpoint of HCM-related events-a composite of sudden cardiac death (SCD) events, heart failure (HF) events, and HCM-related death-were assessed. During a median follow-up of 3.2 years, 64 (6.5%) patients experienced the primary endpoint. While LGE (median 7.1%, IQR 2.3-16.9%) and ECV (median 29.0%, IQR 26.6-32.0%) were moderately correlated (R = 0.604, P < 0.001), both were significantly associated with increased risk of the primary endpoint and individual outcomes of SCD and HF events, and optimal cutoffs were determined as LGE ≥ 27% and ECV ≥ 35%. Patients with ECV ≥ 35% had more symptoms, a more severe phenotype with greater systolic and diastolic dysfunction, and more pathogenic gene variants. Notably, ECV remained a significant predictor of the primary endpoint (adjusted HR 1.08, 95% CI 1.02-1.15, per 1%) after adjustment for key disease variables, including left ventricular ejection fraction and LGE. Elevated ECV effectively identified high-risk individuals even among lower-risk subgroups, including those with low LGE burden. CONCLUSION: Increased ECV is an independent predictor of HCM-related outcomes. ECV may serve as a novel imaging biomarker to refine risk stratification in HCM patients who do not meet traditional LGE-based high-risk criteria.

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PubMed2026

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30‑day all‑cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged ≥ 60 years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K‑Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P < 0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR = 9.752), smoking (OR = 5.171), AIP (OR = 6.691), TyG index (OR = 4.393), HALP score (OR = 2.831), and ≥ 2 comorbidities (OR = 3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC = 0.884, accuracy = 0.829, sensitivity = 0.812, specificity = 0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30‑day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

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PubMed2026

Longitudinal Neurocognitive Changes for Patients With Hematologic Malignancies Undergoing Hematopoietic Stem Cell Transplantation: A Systematic Review With Structured Narrative Synthesis.

OBJECTIVES: Neurocognitive changes in hematological malignancies (HM) and as a sequela of hematopoietic stem cell transplantation (HSCT) remain under-recognized. These changes may substantially affect patients' quality of life. Therefore, this review systematically evaluated longitudinal neurocognitive changes in patients with HM undergoing HSCT. METHODS: Following PRISMA guidelines, PubMed, Scopus, and CINAHL were searched on October 30, 2025. Longitudinal studies assessing neurocognitive changes in patients with HM undergoing HSCT, with or without healthy controls, were included. Risk of bias was assessed using an adapted National Institutes of Health quality assessment tool for before-after studies. Effect sizes with 95% confidence intervals were calculated to quantify changes in neurocognitive performance. RESULTS: Nine of 2012 studies met the inclusion criteria, with overall moderate study quality. Improvements may occur post-HSCT; however, allogeneic HSCT and myeloablative conditioning were main risk factors identified for persistent cognitive decline. In line with white matter damage, executive function and attention/processing speed impairments likely represent core deficits, which may affect other cognitive impairments. Post-HSCT changes depend on task characteristics, cognitive load, and conditioning intensity. CONCLUSIONS: Future research should emphasize regular neurocognitive assessment to guide cognitive rehabilitation, implement pre-transplant cognitive rehabilitation strategies to mitigate post-HSCT cognitive decline, and enhance treatment outcomes.

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PubMed2026

Identifying biomarkers of accelerated ageing in cancer patients from routine clinical data.

INTRODUCTION: Cancer and ageing have a bidirectional relationship: age is the strongest risk factor for cancer, and cancer and treatments can accelerate ageing. Therefore, biological age can differ from chronological age; biomarkers are needed to stratify interventions to minimise accelerated ageing. METHODS: PhenoAge was calculated from routine blood test results of patients attending a Geriatric Oncology clinic. PhenoAgeAccel was the residual from a regression of PhenoAge against age. RESULTS: Data were available for 173 patients (62% male). Mean PhenoAge was higher than age (84.3 (12.6) vs 76.2 (7.24), p < 0.001), though the two were correlated (r = 0.579, p < 0.001). Unlike age, PhenoAge and PhenoAgeAccel were associated with one-year mortality (PhenoAge OR=1.083, 95% CI: 1.038-1.136; PhenoAgeAccel OR=1.096, 95% CI: 1.047-1.155). PhenoAge correlated with Clinical Frailty Score and Timed Up and Go (CFS: Rs=0.31, p < 0.001; TUG: Rs=0.25, p < 0.005); there were no correlations with age. PhenoAgeAccel correlated with the number of CGA interventions made (Rs=0.17, p < 0.05), unlike age and PhenoAge. Patients with diabetes mellitus had a higher PhenoAgeAccel compared to those without (3.40 vs -1.71, p = 0.002). In patients receiving systemic anti-cancer treatment, patients with PhenoAgeAccel calculated pre-treatment had less age acceleration than those with PhenoAgeAccel calculated post-treatment, both overall (2.18 vs -2.87; p = 0.048) and in matched samples (n = 21, 7.76 vs -2.87, p < 0.001). CONCLUSIONS: PhenoAgeAccel is a greater predictor of risk than chronological age in older people with cancer. This makes it a promising biomarker to stratify patients for holistic geriatric assessment, dose reductions, or future geroprotective measures which could be integrated within electronic healthcare record systems.

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PubMed2026

Thrombus Metabolism-Based Molecular Subtyping for Prognostic Risk Stratification in Acute Ischemic Stroke: A Preliminary Study.

AIMS: To preliminarily characterize metabolic molecular subtypes of cerebral thromboemboli and evaluate their clinical significance in anterior circulation acute ischemic stroke due to large vessel occlusion (AIS-LVO). METHODS: Untargeted metabolomics was performed on thromboemboli retrieved from 36 patients with anterior circulation AIS-LVO using ultra-performance coupled liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Unsupervised hierarchical clustering was employed to identify distinct metabolic molecular subtypes, and their associations with stroke etiology, radiographic severity, and functional outcomes were analyzed. RESULTS: Two distinct thrombus metabolic molecular subtypes (C1 and C2) were identified based on 12 metabolites significantly associated with both short-term (7-day ∆NIHSS) and long-term (90-day mRS) functional outcomes. The C1 subtype, predominantly cardioembolic, exhibited enhanced lipid metabolism, whereas the C2 subtype, primarily atherothrombotic, demonstrated increased folate metabolism. Patients with C1 thromboemboli presented more severe admission ischemic lesions (as indicated by ASPECTS) and experienced poorer short-term and long-term outcomes. A six-metabolite signature derived from LASSO regression was identified for exploratory discrimination of thrombus metabolic subtypes, etiological subtypes, and 90-day outcomes. CONCLUSION: This preliminary exploratory study identifies two metabolically distinct thrombus molecular subtypes with clinical implications in anterior circulation AIS-LVO, providing a novel basis for risk stratification and personalized secondary prevention and warrants further investigation.

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PubMed2025

Mediators of Change in Cognitive Behavioral and Mindfulness-Based Online-Interventions for Hypoactive Sexual Desire Dysfunction in Women.

Low sexual desire is a common sexual problem among women. When it is accompanied by significant personal distress, it may be diagnosed as hypoactive sexual desire dysfunction (HSDD). Both cognitive behavioral therapy (CBT) and mindfulness-based therapy (MBT) are effective treatments for HSDD when delivered in person or online. In this randomized controlled treatment study, CBT and MBT consisted of eight guided self-help modules delivered online, and participants completed measures at pretreatment and after 3, 6, and 12 months. Nine variables were examined as potential mediators of treatment outcomes (i.e., sexual desire and sexual distress), namely mindfulness, self-compassion, rumination, body connection, self-consciousness, relationship satisfaction, sexual communication, depression, and anxiety. In total, 212 women diagnosed with HSDD were randomized to either CBT or MBT (Mage = 36.3, SD = 10.2). Improvements in self-compassion, rumination, body connection, and self-consciousness partially mediated treatment outcomes in at least one of the treatment groups. Mediation effects were mostly small, explaining up to 15% of the total effects. No systematic differences in mediation pathways between CBT and MBT were found. These findings emphasize the importance of emotion regulation, metacognitive processes, and embodiment for the effective treatment of HSDD. Future research should refine treatment components to enhance efficacy and ensure that psychological interventions adequately address common concerns among women with HSDD.

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PubMed2026

Construction of precision clinical-proteomics risk model based on machine learning for predicting heart failure in type II diabetes mellitus.

BACKGROUND AND AIMS: Heart failure (HF) is a severe complication in type 2 diabetes mellitus (T2DM), but current risk stratification scores have limited predictive accuracy. We aimed to develop novel prediction tools integrating clinical variables with proteomics to improve risk stratification of hospitalization for HF in T2DM. METHODS AND RESULTS: In this study, we included 2111 UK Biobank participants with T2DM but no prior HF, and profiled 2920 proteins to predict 10-year incident HF hospitalization. Participants were randomly divided into training (70%), tuning (10%), and validation (20%) sets.Three prediction models were developed: a Clinical model based on demographic characteristics, comorbidities, medication use, and laboratory indices; a Protein model based on 40 proteins selected by the Light Gradient Boosting Machine (LGBM); and the Clinical OMics and Protein ASSessment for Heart Failure (COMPASS-HF) model, which integrated both clinical variables and the LGBM-selected proteins. Models were evaluated for area under the curve (AUC), sensitivity, and specificity. During follow-up, 168 participants (7.96%) developed incident HF. The COMPASS-HF model showed better discrimination than the Clinical model, with an AUC of 0.897 (95% CI: 0.850-0.945) versus 0.790 (95% CI: 0.723-0.856). It also demonstrated higher sensitivity (0.882; 95% CI: 0.725-0.967) and consistent performance in subgroups. COMPASS-HF effectively stratified risk of hospitalization for HF, with cumulative incidence rates of 31.9% in the high-risk group and 1.2% in the low-risk group. CONCLUSIONS: By combining clinical and proteomic variables, we developed a high-performance HF prediction model for T2DM, enabling precise risk stratification and informing early intervention strategies.

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