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PubMed2026

Multimodal alignment improves generalizability of genomic biomarker prediction in computational pathology.

Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for the prediction of genomic biomarkers, a key task in precision oncology. However, as new genomic biomarkers are discovered or quantified, large, labeled datasets must be prospectively collected to train new models. To address this challenge, we developed multimodal alignment for biomarker learning and generalization (MARBLE), a multimodal contrastive pretraining strategy that integrates structured biomarker knowledge into representation learning of histopathology images. MARBLE aligns histopathology-derived representations with representations of genomic biomarkers generated by a large language model (LLM) and a protein language model (PLM). This biologically informed alignment enables data-efficient generalization to novel, out-of-distribution biomarkers. Using the MSK-IMPACT cohort of over 40,000 patients across multiple biomarker panel versions, we design experiments grounded in real-world data to demonstrate the value of our proposed approach.

CP: computational biology↗

PubMed2026

Externally validated risk prediction models for gestational diabetes mellitus: A systematic review and meta-analysis.

INTRODUCTION: Risk prediction models for gestational diabetes mellitus (GDM) offer potential for early identification and targeted prevention. External validation is crucial to assess model performance across diverse populations. Despite the availability of numerous GDM prediction models, limited evidence exists on their external validation frequency, methodological quality, and clinical applicability. This systematic review evaluated externally validated GDM prediction models, focusing on methodological rigor, reporting standards, and clinical relevance to inform future research and implementation. MATERIAL AND METHODS: Databases including Ovid MEDLINE, Embase, Scopus, Emcare, and CINAHL were searched up to May 1, 2025. Studies reporting external validation of GDM risk prediction models were included. Two reviewers independently screened studies. Data were extracted using the CHARMS framework, and risk of bias and applicability were assessed using PROBAST+AI. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD420251125758). RESULTS: Twenty-six studies validated 33 models, with validation sample sizes ranging from 50 to 75 161. Over half used the IADPSG criteria to define GDM. Discrimination metrics were commonly reported, but calibration, overall performance, and clinical utility were often lacking. Meta-analysis was feasible for only four models: Teede et al., Nanda et al., Naylor et al., and Van Leeuwen et al., each showing fair discrimination. The Teede et al. model was the most widely validated, with 11 external validations across six continents and a pooled AUC of 0.72 (95% CI: 0.67-0.76). Despite fewer validations, the Nanda et al. model achieved the highest pooled discrimination (5 validations; pooled AUC 0.77, 95% CI: 0.74-0.80). The Naylor et al. and van Leeuwen et al. models also underwent meta-analysis, as sufficient external validation studies were available to support comparative performance assessment. Notably, 69.23% of studies had a high risk of bias. CONCLUSIONS: While many models showed acceptable predictive performance, most validations were methodologically weak. Future studies should follow best-practice guidelines and promote scalable validation strategies, such as algorithm sharing, to enhance clinical utility.

Humans↗

PubMed2026

Association of lipoprotein-associated phospholipase A2 with recurrence risk and its predictive value in large artery atherosclerotic stroke.

OBJECTIVE: To investigate the association of lipoprotein-associated phospholipase A2 (Lp-PLA2) with large artery atherosclerotic (LAA) stroke and its predictive value for recurrence. METHODS: We consecutively enrolled 412 acute LAA stroke patients. Using a cutoff of 200 ng/mL, patients were divided into high and low Lp-PLA2 groups, and into recurrence and non‑recurrence groups based on 1‑year follow‑up. Baseline characteristics, lipid profiles, National Institutes of Health Stroke Scale (NIHSS) scores, and vascular stenosis degree were compared. Binary logistic regression and Receiver Operating Characteristic (ROC) analysis were used to identify independent risk factors and evaluate predictive value. RESULTS: The high Lp-PLA2 group had significantly higher low-density lipoprotein cholesterol (LDL-C), small dense low-density lipoprotein cholesterol (sdLDL-C), prevalence of severe stenosis (≥70%), and proportion of NIHSS > 15 (all P < 0.05). The recurrence group showed elevated Lp-PLA2, higher LDL‑C and sdLDL-C, more severe neurological deficits, and more severe stenosis (all P < 0.001). Multivariable regression identified elevated Lp-PLA2 (per 10 ng/mL: OR = 1.139, 95% CI: 1.089-1.191), moderate (OR = 3.145) and severe (OR = 11.663) neurological deficits, and severe stenosis (OR = 9.390) as independent risk factors for recurrence (all P < 0.05). The Area Under the Curve (AUC) of Lp-PLA2 was 0.75 (95% CI: 0.69-0.82), with an optimal cutoff of 208.95 ng/mL. CONCLUSION: Elevated Lp-PLA2 is associated with adverse lipid profiles, more severe neurological deficits, and greater vascular stenosis in LAA stroke patients, and independently predicts 1‑year recurrence. Lp-PLA2 shows moderate predictive value, supporting its potential for risk stratification.

Humans↗

PubMed2026

Safety and efficacy of immune checkpoint inhibitors as a bridge to allogeneic hematopoietic stem cell transplantation in classical Hodgkin lymphoma: A systematic review and meta-analysis.

Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape for relapsed or refractory classical Hodgkin lymphoma (cHL); however, a substantial subset of patients ultimately requires allogeneic hematopoietic stem cell transplantation (allo-HCT) to achieve long-lasting disease control. The use of ICIs as a bridge to allo-HCT has therefore gained increasing clinical interest, though concerns persist regarding post-transplant complications and incompletely-defined safety profiles. Accordingly, this systematic review and meta-analysis was conducted to evaluate outcomes of ICIs administered prior to allo-HCT in cHL. Following PRISMA guidelines, a comprehensive literature search was conducted across online databases through January 2026. Eligible studies included observational designs reporting survival and transplant-related outcomes in cHL patients treated with ICIs followed by allo-HCT. Pooled proportions for overall survival, progression-free survival, non-relapse mortality, and graft-versus-host disease (GVHD) incidence were calculated using a random-effects model. Seven studies comprising 739 patients were included. Post-transplant survival outcomes were favorable, with high pooled estimates across timepoints. Transplant-related mortality remained low, with NRM rates consistently within an acceptable range through long-term follow-up. Acute GVHD was observed at a meaningful frequency, including a smaller subset of severe cases, while chronic GVHD occurred in approximately one-quarter of patients at follow-up. Overall, these findings suggest that ICI therapy prior to allo-HCT in cHL is associated with encouraging survival and disease control and does not appear to confer excessive non-relapse mortality, supporting its use as a feasible and effective bridging strategy, while underscoring the need for future prospective studies to clarify optimal timing, risk mitigation strategies, and patient selection.

Humans↗

PubMed2026

Efficacy of sodium-glucose cotransporter 2 inhibitors after acute myocardial infarction: Are the benefits limited to patients with diabetes? A systematic review and meta-analysis.

BACKGROUND: Acute myocardial infarction remains one of the leading causes of death worldwide. Recently, studies have focused on evaluating the effectiveness of SGLT2 inhibitors in this scenario. Objectives We aimed to perform a meta-analysis comparing the efficacy of SGLT2 inhibitors vs standard care. METHODS: We systematically searched PubMed, Embase, and Cochrane for randomized controlled trials (RCTs) and observational studies comparing patients with acute myocardial infarction using iSGLT2 inhibitors and standard care. Statistical analyses were conducted using R software (v 4.3.2) and a random-effects model was employed for all outcomes. RESULTS: A total of 31,378 patients were included, with 10,897 (34.7%) assigned to the SGLT2 inhibitor group. Among these studies, three were randomized controlled trials (RCTs). There was a significant difference in reduction of HF readmissions (OR 0.61; p < 0.01), all-cause mortality (OR 0.62; p < 0.01;) and stroke (OR 0.67; p < 0.01;). However, there was no significant difference in cardiovascular death, rehospitalization for any cause and recurrence of acute MI. Meta regression and subgroup analysis showed a trend toward better outcomes in the diabetic and non-STEMI population. CONCLUSIONS: SGLT2 inhibitors were associated with lower HF rehospitalization, stroke, and all-cause mortality after acute MI, mainly in observational studies. Benefits appeared greater in diabetic and non-STEMI patients. Dedicated RCTs focusing on diabetic, particularly non-STEMI, populations are needed to confirm these findings. KEY POINTS: What is already known on this topic: SGLT2 inhibitors have demonstrated cardiovascular and renal benefits in patients with heart failure and type 2 diabetes mellitus. However, their role in the acute myocardial infarction (AMI) setting remains uncertain, particularly regarding post-AMI outcomes such as heart failure readmissions, mortality, and recurrent ischemic events, with current evidence derived from heterogeneous and predominantly observational studies. WHAT THIS STUDY ADDS: This meta-analysis, including over 31,000 patients, suggests that SGLT2 inhibitors are associated with reductions in heart failure readmissions, all-cause mortality, and stroke following AMI. These associations were more consistently observed in patients with type 2 diabetes and in non-ST-segment elevation myocardial infarction (NSTEMI) populations. However, randomized controlled trials showed neutral results, and the observed benefits were mainly driven by observational studies. Meaning: These findings should be interpreted as hypothesis-generating. While SGLT2 inhibitors may represent a potential therapeutic strategy in selected post-AMI populations, particularly patients with diabetes and NSTEMI, current evidence does not support routine early in-hospital initiation. Dedicated randomized trials specifically enrolling diabetic post-AMI patients are required to clarify optimal timing and clinical benefit.

Humans↗

PubMed2026

Tranexamic acid in spontaneous intracerebral hemorrhage: an updated systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Tranexamic acid (TXA) is a well-established antifibrinolytic medication in the general population. However, its efficacy and safety for patients with spontaneous intracerebral hemorrhage (ICH) remain inconclusive. Consequently, we conducted a systematic review and meta-analysis to assess the effectiveness and safety of TXA for spontaneous ICH. METHODS: We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) following established methodological standards. Our search encompassed eight electronic databases from inception to April 25, 2024. The primary outcome was a reduction in all-cause mortality. The secondary outcomes included improvements in functional independence, neurological impairment, activities of daily living, and reduction in hematoma expansion (HE). Fixed-effects or random-effects model were performed for pooled data where eligible. RESULTS: A total of 9 RCTs that initially enrolled 3,124 patients were included. There were no significant differences observed concerning all-cause mortality (RR, 1.03; 95% CI [0.89-1.18]), hematoma expansion (RR, 0.90; 95% CI [0.80-1.00]), improvement of functional independence (RR, 1.02; 95% CI [0.92-1.12], neurological impairment (MD, -0.88 [95% CI, -2.22-0.45]), or activities in daily living (MD, -0.83 [95% CI, -29.25-12.59]). The pooled data indicated that TXA for ICH was associated with a decrease in hematoma volume from baseline (MD, -1.74; 95% CI [-2.47 to -1.02]). No significant difference in adverse events was observed between the TXA group and the control group. CONCLUSIONS: In summary, TXA does not affect all-cause mortality, functional outcomes, or neurological impairment, nor does it reduce HE, despite reducing hematoma volulume. TXA use for ICH requires careful clinical consideration.

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PubMed2026

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans↗

PubMed2026

Predicting training outcomes for developmental dyslexia from EEG data.

Developmental dyslexia (DD) is characterised by lower-than-average reading abilities and is diagnosed in approximately 10% of individuals. The societal barriers may limit professional fulfilment and psychological wellbeing of individuals with DD, calling for the development of effective interventions to counteract them. As DD is associated with challenges in both phonological and visuo-attentional domains, different longitudinal training approaches were developed to strengthen them. However, they require a considerable amount of personal, social and economic resources and the outcomes may vary depending on individual differences in behavioural and neurophysiological functionality. Hence, predicting training outcomes might help in developing personalised treatment protocols and optimising the use of resources. In the present work we applied machine learning to resting-state EEG to predict longitudinal training outcomes in adults with DD enrolled in a randomized clinical trial. In particular, one group received a visuo-attentional training combined with transcranial alternating current stimulation (tACS), another group received visuo-attentional training with sham/placebo stimulation, and the third group received a phonological training with sham/placebo stimulation. The improvement in text reading speed was associated with spectral power in low-beta and individual frequencies in the alpha (IAF) and beta (IBF) bands, while the improvement in pseudoword reading was associated with IBF. The findings highlight the potential of capturing neural markers of treatment responsiveness in DD. Future studies should focus on the generalisability of predictive models to real-world settings, while investigating whether specific EEG markers predict responsiveness to distinct remediation protocols, thus supporting the development of personalised interventions.

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PubMed2026

Surgical management and outcomes of total colonic aganglionosis in children: A systematic review and meta-analysis.

AIM: Total colonic aganglionosis (TCA) is a rare form of Hirschsprung disease, and there is no consensus regarding its optimal surgical management. This systematic review and meta-analysis aimed to evaluate different surgical approaches and outcomes in children with TCA. METHODS: A systematic search of PubMed/MEDLINE and Embase was performed for studies published between January 2000 and December 2025. The review followed PRISMA guidelines and was prospectively registered in PROSPERO (CRD420251078401). Eligible studies included patients aged ≤18 years with TCA who underwent conventional pull-through procedures (CPT; Duhamel, Soave, Swenson, Rehbein, and Ikeda-Soper) or non-conventional techniques (NCPT; STATE procedure, J-pouch, right- or left-sided colonic patch pull-through, and ileocecal patch). A subgroup analysis comparing Duhamel and ileoanal pull-through procedures (IAPT) was also performed. Outcomes included fecal incontinence, Hirschsprung-associated enterocolitis (HAEC), requirement for additional interventions, postoperative intestinal obstruction, and mortality. Meta-analysis was performed using jamovi software, version 2.3.28, with p < 0.05 considered statistically significant. RESULTS: Seven studies including 134 patients compared CPT (n = 85) with NCPT (n = 49), and ten studies including 274 patients compared Duhamel (n = 143) with IAPT (n = 131). Across both comparisons, pooled odds ratios (ORs) showed no statistically significant differences in fecal incontinence, HAEC, requirement for additional interventions, postoperative intestinal obstruction (Duhamel vs IAPT only), or mortality. For CPT versus NCPT, the pooled ORs were 1.1 for fecal incontinence (95% CI, 0.44-2.73; p = 0.837), 1.1 for HAEC (95% CI, 0.49-2.71; p = 0.743), 4.3 for requirement for additional interventions (95% CI, 0.86-22.1; p = 0.074), and 3.4 for mortality (95% CI, 0.52-21.5; p = 0.198). For Duhamel versus IAPT, the pooled ORs were 1.4 for fecal incontinence (95% CI, 0.60-3.36; p = 0.423), 0.6 for HAEC (95% CI, 0.22-2.06; p = 0.503), 1.8 for requirement for additional interventions (95% CI, 0.62-5.50; p = 0.262), 1.1 for postoperative intestinal obstruction (95% CI, 0.21-6.01; p = 0.875), and 1.03 for mortality (95% CI, 0.25-4.20; p = 0.965). CONCLUSION: No statistically significant differences were identified between CPT and NCPT or between Duhamel and IAPT for the evaluated outcomes in children with TCA. However, the absence of statistically significant differences should not be interpreted as evidence of equivalence, particularly given the small sample sizes, wide confidence intervals, and clinical and methodological heterogeneity of the studies included. The choice of surgical approach should be individualized according to disease extent, patient-specific factors, institutional experience, and surgical expertise. TYPE OF STUDY: Meta-analysis. LEVEL OF EVIDENCE: III.

Humans↗

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.

Humans↗

PubMed2026

Excimer laser angioplasty for acute coronary occlusion: a stratified meta-analysis of efficacy against aspiration thrombectomy and conventional PCI.

Primary percutaneous coronary intervention (PCI) achieves epicardial reperfusion in most STEMI patients, yet microvascular obstruction persists in up to 60% of patients. Excimer laser coronary angioplasty (ELCA) vaporizes thrombus in situ and may reduce distal embolization, but the evidence base has not been systematically synthesized. This systematic review and meta-analysis (PROSPERO CRD420261422463) included comparative studies of adjunctive ELCA versus aspiration thrombectomy (Stratum A) or PCI alone (Stratum B) in acute coronary occlusion. Primary outcomes were final TIMI-3 flow and myocardial blush grade (MBG) 3; secondary outcomes were short-term mortality, MACCE, and slow-flow/no-reflow. A random-effects model with Hartung-Knapp-Sidik-Jonkman confidence intervals was applied to all outcomes. Certainty was assessed with GRADE. Ten studies (1 RCT, 9 observational) were included, from a total enrolled population exceeding 3,500. In Stratum A, no outcome reached significance: MBG-3 (OR 3.57, 95% CI 0.07-185.10), mortality (OR 0.31, 0.02-4.04), MACCE (OR 0.22, 0.04-1.26), TIMI-3 flow (OR 1.58, 0.67-3.75) and slow-flow/no-reflow (OR 0.78, 0.22-2.78). In Stratum B, using each study's propensity-matched data, no outcome differed significantly (TIMI-3 OR 0.88, 0.38-2.03; MBG-3 OR 1.06, 0.13-8.43; slow-flow/no-reflow OR 0.93, 0.29-3.02; mortality OR 0.44, 0.05-3.80). Composite endpoints were not pooled across incompatible follow-up horizons, and all outcomes were of very low certainty. Adjunctive ELCA-containing strategies during primary PCI were not associated with improved angiographic or short-term clinical outcomes against either comparator. Multicenter randomized trials are required before recommending clinical adoption.

Humans↗

PubMed2026

Risk prediction models for blood transfusion in patients undergoing total hip and knee arthroplasty: a systematic review and meta-analysis.

OBJECTIVE: To systematically review and evaluate published risk prediction models for perioperative blood transfusion in patients undergoing total hip or knee arthroplasty (THA/TKA). METHODS: We systematically searched PubMed, Web of Science, the Cochrane Library, and Embase from inception to May 31, 2025. Two researchers independently screened the literature, extracted data, and assessed the risk of bias and applicability using the Prediction model Risk Of Bias Assessment Tool (PROBAST). The area under the receiver operating characteristic curve (AUC) values were pooled via a meta-analysis using Stata 18.0. RESULTS: d Fourteen studies containing 36 prediction models were included. The incidence of blood transfusion among THA/TKA patients ranged from 3.2% to 30.8%. Preoperative hemoglobin (Hb) level, tranexamic acid (TXA) use, operative duration, intraoperative blood loss, and age were the most frequently incorporated predictors. Model sensitivity ranged from 58% to 94.5%, and specificity ranged from 71.3% to 94%. Meta-analysis showed that the pooled AUC value of the 13 validated models was 0.87 (95% CI: 0.85-0.90), suggesting good discriminatory performance. All models were rated as having a high risk of bias. The applicability of four studies was rated as unclear. CONCLUSION: Although the included studies demonstrated promising discriminative ability of prediction models for blood transfusion in THA/TKA, all were assessed as having a high risk of bias using the PROBAST tool. Therefore, future research should prioritize the development of models with larger sample sizes, rigorous study designs, and multicenter external validation.

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PubMed2026

Efficacy and safety of middle meningeal artery embolization for chronic subdural hematoma: an updated systematic review and meta-analysis focusing on time of intervention.

INTRODUCTION: Chronic subdural hematoma (cSDH) is increasingly prevalent among older adults due to population aging and widespread antithrombotic use. Although burr-hole drainage remains the standard treatment, recurrence rates are substantial. Middle meningeal artery embolization (MMAE) has emerged as an adjunctive strategy to disrupt dural neovascularization and prevent rebleeding. OBJECTIVES: To assess the efficacy and safety of MMAE combined with standard therapy versus standard therapy alone, with stratification by timing of intervention. METHODS: Randomized controlled trials (RCTs) were searched in PubMed, Scopus, and Cochrane Central up to July 2025. Adults with confirmed cSDH were included. The primary outcome was hematoma recurrence or persistence. Secondary outcomes were reoperation, hematoma resorption, serious adverse events, neurological death, mortality, functional independence, and hospital stay. Risk of bias was assessed with RoB-2, and analyses followed PRISMA guidelines (PROSPERO CRD420251112841). RESULTS: Seven RCTs (1,889 patients) were included. Compared with standard therapy, MMAE significantly reduced recurrent or residual cSDH (RR 0.63; 95% CI 0.46-0.85) and reoperation (RR 0.39; 95% CI 0.28-0.56) without increasing serious adverse events (RR 0.87; 95% CI 0.72-1.06), neurological death, mortality, or poor functional outcomes. Hematoma resorption did not differ significantly. Subgroup and sensitivity analyses confirmed the robustness of the results across age, intervention timing, and follow-up duration. CONCLUSION: MMAE combined with standard therapy significantly reduces recurrence and reoperation in cSDH without increasing adverse events or mortality. Benefits appear independent of procedural timing, though larger RCTs with extended follow-up are warranted to define long-term outcomes and optimal use.

Humans↗

PubMed2026

Assessment of the Potential of Different Anthropometric Indices in Predicting the Risk of Diabetes and Associated Co-morbidities.

Diabetes, a chronic disorder, is showing a rapidly increasing trend globally. India holds the second position in the global diabetes epidemic. The present investigation is an assessment of different anthropometric measurements and their association with type 2 diabetes to determine their diagnostic potential for diabetes as well as its co-morbidities. In this cross-sectional study, we have measured anthropometric parameters and blood biomarkers in subjects with diabetes. We have presented the comparisons of cost- and time-effective anthropometric variable with costly and time-dependent biochemical variables in control and diabetic groups (n = 233/group). Correlations between anthropometric variables and biochemical measurements, as well as the diagnostic utility of anthropometric variables for diabetes, were evaluated. The diagnostic utility of anthropometric variables for diabetes was assessed through receiver operating characteristic (ROC) curves. Neck circumference, sagittal abdominal diameter (SAD), skinfold thickness, and body roundness index (BRI) displayed high specificity and diagnostic utility for diabetes, emphasizing their potential in predicting diabetes and the further development of metabolic syndrome. The study highlights the importance of cost- and time-effective anthropometric assessments in diabetes risk evaluation and calls for further research to elucidate this intricate relationship and develop personalized management strategies.

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PubMed2026

Safety and outcomes of dapagliflozin initiation in critically ill patients with acute kidney injury: A post-hoc analysis of the defender trial.

BACKGROUND: SGLT2 inhibitor use in acute kidney injury (AKI) is controversial due to concerns about hemodynamic instability. We evaluated dapagliflozin initiation in critically ill patients with AKI enrolled in the DEFENDER trial. METHODS: Among 212 patients with AKI at enrollment (100 dapagliflozin, 112 control), we compared 28-day mortality, kidney replacement therapy (KRT), and composite death/KRT. Adjusted risk differences were estimated controlling for age, sepsis, baseline vasopressor use, and creatinine. Physiological trajectories (creatinine, urine output, fluid balance, acid-base parameters) over days 1-5 were analyzed using mixed models. Likelihood ratios quantified compatibility with clinically meaningful harm or benefit. RESULTS: Event rates were similar: 28-day mortality 38% vs 40%, KRT 12% vs 18%, composite 41% vs 42% (dapagliflozin vs control). Adjusted risk differences were - 1.9% (95% CI -14.5 to 10.7) for death, -7.4% (-16.2 to 1.5) for KRT, and - 0.9% (-13.6 to 11.8) for the composite. Physiological trajectories showed no divergence suggestive of hemodynamic or metabolic instability. Likelihood ratios provided limited separation: at 5% absolute effect threshold, LR against harm was 1.47 and against benefit 1.19. CONCLUSIONS: Dapagliflozin initiation in critically ill patients with AKI was not associated with excess mortality, KRT, or physiological derangement. The near-neutral evidential profile indicates neither moderate harm nor benefit can be excluded, supporting feasibility of dedicated trials of SGLT2 inhibitors in AKI.

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PubMed2026

A Dynamic Nomogram to Predict Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Metabolic Syndrome.

BACKGROUND: Metabolic syndrome (MetS) involves multiple metabolic disorders. This study aimed to identify high-risk populations for metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with MetS and to establish a dynamic predictive nomogram. METHODS: A total of 627 patients with MetS from six regions in Zhejiang Province were enrolled and categorized into MAFLD and non-MAFLD groups, then randomly assigned to training and validation sets at a ratio of 7:3. Independent predictors of MAFLD were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses. These predictors were then used to construct a dynamic nomogram. RESULTS: A total of 627 patients with MetS were included in the final analysis, of whom 77.0% (483/627) were diagnosed with MAFLD. Multivariable logistic regression analysis identified body mass index (BMI), waist circumference (WC), total cholesterol (TC), alanine aminotransferase (ALT), MetS-defined dysglycemia, and education level as independent risk factors for MAFLD. MetS-defined dysglycemia showed the highest odds ratio (OR) for MAFLD development [OR = 1.87, 95% confidence interval (CI): 1.07-3.29]. Although the number of MetS components and the metabolic syndrome score were significantly associated with MAFLD in univariate analysis, they were not independently associated with MAFLD in the multivariate model. A dynamic nomogram for predicting MAFLD risk in patients with MetS was developed and internally validated. The area under the receiver operating characteristic curve was 0.834 (95% CI: 0.787-0.880) in the training set and 0.839 (95% CI: 0.771-0.899) in the validation set, indicating strong predictive performance. Bootstrap internal validation demonstrated good agreement between predicted and observed outcomes in calibration curves. Decision curve analysis further indicated favorable clinical applicability of the nomogram. CONCLUSION: BMI, WC, TC, ALT, MetS-defined dysglycemia, and education level are independent risk factors for MAFLD. A dynamic nomogram for predicting MAFLD risk in patients with MetS was successfully developed and validated.

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PubMed2026

Effects of hospital planning reforms on access, costs, efficiency, and quality of care in OECD countries: Systematic review and meta-analysis.

BACKGROUND: Many OECD countries have implemented hospital planning reforms to rising healthcare costs, demographic changes, and concerns about access, efficiency, and quality of care. Despite broad implementation, evidence on effectiveness remains fragmented and country-specific. OBJECTIVE: To synthesize evidence on the effects of hospital planning reforms aross four outcome domains: access, costs, efficiency, and quality of care. METHODS: We conducted a systematic review following Cochrane methodology, searching PubMed and Web of Science (January 2000 - September 2025). Studies were categorized into four intervention types - centralization, minimum volume requirements (MVR), performance-based targets, and governance and ownership restructuring. Risk of bias was assessed using Joanna Briggs Institute checklist for quasi-experimental designs. Where data permitted, random-effects meta-analyses pooled standardized mean differences (SMD) for access and efficiency and risk differences (RD) for quality outcomes. RESULTS: 26 studies from 12 countries were included. Centralization increased patient travel distances and reduced length of stay (SMD -0.09, 95% CI -0.17 to -0.01) and complications (RD -14.52 pp, -25.95 to -3.09), and, jointly with performance-based targets, 30-day readmissions (RD -0.43 pp, -0.65 to -0.22). Mortality effects varied by timepoint and intervention: short-term endpoints were largely non-significant, whereas 90-day mortality was reduced under centralization (RD -0.80 pp, -1.25 to -0.35) and 60-day mortality under MVR (RD -2.00 pp, -2.82 to -1.18). Survival was non-significant throughout. No study examined costs. CONCLUSION: The absence of cost evidence is a critical gap. Substantial heterogeneity reflects variation in reform design and context, underscoring the need to interpret findings by intervention and country conditions.

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PubMed2026

An individualized nomogram for predicting progression-free survival in systemic anaplastic large cell lymphoma: a multicenter, retrospective, and internally validated study.

OBJECTIVES: To develop an individualized nomogram for predicting disease progression risk in systemic anaplastic large cell lymphoma (sALCL). METHODS: Independent predictors of progression-free survival (PFS) were identified using Cox regression in a multicenter retrospective cohort of 109 sALCL patients (2010-2022). These were incorporated into a three-factor nomogram, evaluated via bootstrapped internal validation (1000 resamples), ROC analysis, C-index, decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: A total of 29 PFS events occurred during a median follow-up of 31 months. Multivariable modelling selected serum β2-microglobulin elevation, extranodal disease, and front-line chemotherapy choice (CHOP versus CHOPE or BV+CHP) as autonomous progression drivers. Upon internal bootstrap validation, the nomogram yielded strong prognostic accuracy, achieving AUCs of 0.81, 0.85 and 0.87 for 1-, 3- and 5-year progression-free survival, alongside a corrected C-index of 0.779 (95% CI: 0.699 - 0.861). Calibration plots showed close agreement between predicted and observed outcomes, while DCA confirmed superior net clinical benefit versus conventional IPI or Ann Arbor stratification across multiple decision thresholds. CONCLUSION: This first sALCL-specific nomogram integrates clinical and treatment variables to provide personalized PFS risk estimation. While internally validated, this exploratory, observation-based tool requires external validation and recalibration in prospective cohorts before clinical implementation.

Humans↗