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PubMed2026

Potential Links Between Physiological and Perceptual Strain in High Heat Stress.

The physiological strain index (PhSI) is widely used to quantify thermoregulatory and cardiovascular strain during heat stress. However, direct physiological measurements may not always be feasible in occupational or athletic settings. Therefore, this study aimed to examine the relationship and agreement between perceptual strain and integrated physiological strain indices during high heat stress. Ten healthy, physically active, non-heat-acclimated males (29 (7) yr; 1.79 (0.11) m; 77.4 (9.3) kg) completed two randomized crossover exercise trials in hot-dry (HD) and warm-humid (WH) environments with equivalent wet-bulb globe temperatures. Heart rate, rectal temperature, skin temperature, rating of perceived exertion, and thermal sensation were measured at baseline and every 15 minutes during 60 minutes of cycling. Physiological strain index (PhSI), adaptive physiological strain index (aPhSI), and perceptual strain index (PeSI) were calculated using validated equations. Repeated-measures correlation analyses demonstrated very strong associations between PeSI and both PhSI and aPhSI under HD (Rrm = 0.940-0.943) and WH (Rrm = 0.980-0.982; all p < 0.001). Receiver operating characteristic analyses demonstrated good-to-excellent discrimination of physiological strain by PeSI (AUC = 0.895-0.969). Mixed-effects analyses showed that higher PeSI values were associated with increased PhSI (β = 1.325, p < 0.001) and aPhSI (β = 1.459, p < 0.001). However, Bland-Altman analyses demonstrated relatively small mean biases (0.4-0.9 AU) but wide limits of agreement (-2.8 to 4.2 AU), indicating that PeSI and physiological strain indices are not interchangeable. These findings suggest that PeSI may serve as a practical adjunctive or screening indicator of physiological strain when direct physiological measurements are unavailable.

Humans↗

PubMed2026

Redefining the real problem in psychedelic trials: Why fighting the Lessebo matters more than blinding integrity.

Imperfect blinding is not specific to psychedelic trials. In randomized trials, treatment allocation is frequently correctly guessed, yet blinding integrity is rarely assessed outside of psychedelic research and is generally not considered a barrier in regulatory evaluation. The intense debate in psychedelics may reflect a broader double standard affecting mental health research, when uncertainties arising from imperfect blinding are confounded by those linked to patient-reported outcome measures. Indeed, people living with mental disorders are often viewed as unreliable reporters, despite well-documented limitations of clinician-rated scales and the absence of robust biological markers of symptomatic change. Importantly, it is the maintenance of reasonable doubt of treatment allocation that sustains internal validity and ethical feasibility of placebo-controlled designs, rather than perfect blinding. Concerns about expectancy bias in psychedelic trials are closely tied to blinding debates. When allocation is inferred, expectations may cluster in the arm perceived as active or in stereotyped experiences and influence outcomes differently in active and control arms, leading to a risk of lessebo, a negative placebo effect due to the negative expectation related to receiving a placebo. However, we argue that an underrecognized mechanism of lessebo is disappointment. This risk may reflect insufficient clinical management of disappointment rather than pre-treatment expectation alone. We therefore propose shifting the emphasis from preserving inevitably imperfect blinding towards mitigating disappointment in both arms. Establishing non-stereotyped expectations prior to treatment through structured psychoeducation, strengthened therapeutic alliance, and realistic preparation would help avoid lessebo effects. Such strategies would enhance ethical rigor, interpretability, and the clinical usefulness of psychedelic trials.

Humans↗

PubMed2026

Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

Humans↗

PubMed2026

Association of time-averaged systemic immune-inflammation indices with in-hospital mortality after intracerebral hemorrhage: a retrospective study.

BACKGROUND: Systemic inflammation plays a central role in secondary brain injury following intracerebral hemorrhage (ICH). Although inflammatory indices such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) are linked to poor outcomes, their associations with mortality are commonly assumed to be linear, potentially overlooking nonlinear patterns where mortality risk rises steeply at higher levels. METHODS: We conducted a retrospective study using the MIMIC-IV database, including 440 patients with non-traumatic ICH who were alive and remained in the ICU for at least 72 h after admission. Mean NLR, SII, and SIRI were calculated from measurements obtained during this period. Multivariable logistic regression and restricted cubic spline (RCS) analyses were applied to assess their independent and nonlinear associations with in-hospital mortality. Model discrimination and calibration were internally validated using 1,000 bootstrap resamples. RESULTS: The in-hospital mortality rate was 26.1%. After multivariable adjustment, NLR and SIRI remained independently associated with mortality. Patients in the highest SIRI quartile had the highest risk of death (aOR = 5.12; 95% CI: 2.57-12.24; p < 0.001). RCS analysis revealed a significant nonlinear association between SIRI and mortality (p-nonlinearity < 0.05), showing a steep risk increase at higher SIRI levels. Adding SIRI to the base model provided a modest improvement in discrimination (AUC 0.762 to 0.785, p = 0.045) and significantly improved risk reclassification (cNRI = 0.4778, p < 0.001; IDI = 0.0240, p = 0.0151). CONCLUSIONS: Among patients with ICH who met the 72-hour eligibility criterion, higher 72-hour average SIRI was independently associated with in-hospital mortality. As a time-averaged measure, SIRI should be interpreted as a dynamic marker integrating the initial inflammatory state and the early clinical course rather than as a purely baseline prognostic factor. Although adding SIRI to the base model modestly improved discrimination and risk reclassification, it should be considered a candidate prognostic marker requiring external validation before clinical application.

Humans↗

PubMed2026

Plasma proteomics: considerations for preanalytical variability; a systematic review with narrative synthesis.

BACKGROUND: The plasma proteome (PP) is a dynamic system subject to pathology-associated changes and a focus for novel disease biomarker discovery. Disease-related PP research assumes protein concentrations in test specimens accurately reflect the in vivo milieu. However, measures to maintain the physicochemical integrity of the proteome before assay are often rudimentary, poorly described, or lacking standardisation in published studies. Contrastingly, in laboratory medicine, there is an expectation that errors in the so-called "preanalytical phase" (PAP) that impact patient results are understood, monitored, and mitigated against, while also being well described in research publications. There is therefore scope for good practice from laboratory medicine to inform PP research workflows. This review considers factors in the PAP which may impact the validity of PP results. CONTENT: A systematic review was conducted per PRISMA guidelines, limited to English-language peer-reviewed studies (2014-2024). Candidate studies were imported, screened, and managed using Covidence systematic review software. SUMMARY: 15 eligible studies were reviewed, covering many relevant processes. 11 studies reported statistically significant differences in PP due to factors in the PAP. Temperature and time-to-processing were the most commonly reported factors affecting the PP, with significant effects reported in 8 studies. OUTLOOK: PAP variability can significantly affect results in PP studies. Careful consideration of the effect of each stage of the PAP is needed when working with the PP. In multicenter studies, pre-defined and research question-specific sample processing workflows are essential for reducing PAP variability, which helps ensure the validity of PP studies.

Humans↗

PubMed2026

Assessing time to symptomatic progression, a patient-relevant efficacy endpoint, in the MARIPOSA study in non-small cell lung cancer.

INTRODUCTION: In the phase 3 randomized MARIPOSA study, amivantamab and lazertinib combination therapy demonstrated improved progression-free survival (PFS) and overall survival (OS) versus osimertinib in participants with previously untreated, epidermal growth factor receptor-mutated advanced non-small cell lung cancer. Time to symptomatic progression (TTSP) was introduced to assess clinical worsening and complement endpoints that investigate radiographic disease progression and patient-reported outcomes. TTSP provides an easily interpretable measure of disease-specific symptom worsening to further support patient experience. METHODS: In MARIPOSA, TTSP was quantitatively assessed as a secondary efficacy endpoint and defined as the time from randomization until participants experience disease-specific symptom worsening requiring a clinical intervention or treatment change, or death. To evaluate the impact of amivantamab and lazertinib on TTSP considering its established OS benefit against osimertinib, an exploratory analysis censoring death events was performed. RESULTS: At the final protocol-specified OS analysis (median follow up: 37.8 months), median TTSP was 43.6 months with amivantamab and lazertinib versus 29.3 months with osimertinib (hazard ratio [HR]: 0.69; 95% confidence interval [CI]: 0.57-0.83; p < 0.0001). Amivantamab and lazertinib reduced deaths following a TTSP event compared to osimertinib. A strong correlation between TTSP and PFS or OS was observed. CONCLUSIONS: Amivantamab and lazertinib significantly delayed TTSP versus osimertinib. TTSP offers a clinician-validated measurement of disease-specific symptom worsening, capturing symptoms perceived by patients that prompt clinical action. TTSP is highly correlated with PFS and OS, providing complementary insights alongside traditional endpoints. TTSP enhances understanding of treatment benefit and supports informed clinical decision-making by integrating patient experience.

Humans↗

PubMed2026

Protein profiling and GC-MS product analysis provide insights into lignite solubilization and bioconversion by Lysinibacillus sphaericus strain SH19.

Lignite biosolubilization offers a mild route for valorizing low-rank coal, although the microbial processes that accompany solubilization remain incompletely defined. Here, an endogenous isolate designated Lysinibacillus sphaericus strain SH19 was evaluated using nitric-acid-pretreated Shengli lignite. Under the selected working conditions (4 M nitric-acid pretreatment, initial pH 8, 40°C, and 16 days), the apparent solubilization rate reached 66.81%. Changes in A450, residual solid mass, culture pH, and extracellular protein concentration showed that chemical pretreatment and bacterial culture were both associated with the release of soluble lignite-derived material. SDS-PAGE and two-dimensional electrophoresis revealed treatment-associated differences in extracellular and intracellular protein patterns. LC-MS/MS analysis of excised protein spots yielded 85 candidate protein assignments; the revised supplementary table reports PEAKS scores, sequence coverage, peak area, and unique-peptide counts and highlights the limited support for several entries. GC-MS analysis produced 33 tentative library assignments in the solubilized fraction, but siloxane- and silyl-related signals were treated as possible analytical background, and no pathway was inferred from these assignments alone. Together, the data identify strain SH19 as a promising lignite-biosolubilizing isolate and provide candidate proteins and product signals for future validation. The proposed process model remains exploratory because direct enzyme assays, inhibitor experiments, carbon-balance measurements, transcriptomic or genetic validation, complete GC-MS blank subtraction, and authentic-standard confirmation were not available.

Bacillaceae↗

PubMed2026

Accurate quantification of canine mitochondrial DNA copy number from canine blood and brain samples.

Acute brain injury is difficult to evaluate in veterinary medicine and tools to investigate the potential involvement of mitochondrial involvement are limited. The brain is highly enriched in mitochondria and contains thousands of copies of mitochondrial DNA (mtDNA) per cell, but robust methods for quantifying mitochondrial DNA copy number (mtDNA-CN) in canine tissues are lacking. We describe the development of a quantitative real-time PCR assay for absolute measurement of mtDNA-CN which was validated in canine blood and brain tissue. To minimize amplification of nuclear mitochondrial insertion sequences (NumtS) and repetitive regions, species-specific oligonucleotide primers were designed following in silico genomic filtering. The assay was applied to a small pilot cohort comprising blood samples from dogs with and without acute brain injury (n = 4-6 per group) and cerebral cortex samples (n = 1 per group) to assess feasibility and biological plausibility. In non-brain injury dogs, blood mtDNA-CN ranged from 98 to 288 copies per nuclear genome (mean 193 ± 72), while values in brain-injured cases ranged from 163 to 228 copies per genome (mean 200 ± 33). Cerebral cortex samples exhibited higher mtDNA-CN than blood, consistent with known tissue-specific mitochondrial enrichment. In a single brain-injured case with serial sampling, mtDNA-CN increased over five days. This study presents a validated assay and pilot data for mtDNA-CN quantification in canine samples. While not powered for biomarker evaluation, this method may enable future studies of mitochondrial dynamics in canine brain injury and metabolic disease.

Animals↗

PubMed2026

Soluble CD163 as a Non-Invasive Biomarker in Autoimmune Nephrological and Rheumatological Diseases.

Autoimmune nephrological and rheumatological diseases involve macrophage-driven inflammation, yet disease activity is often assessed using invasive or non-specific measures. Soluble CD163 (sCD163), released from activated monocytes and macrophages, is emerging as a biomarker of macrophage-mediated inflammation in these conditions. This narrative review summarizes current evidence on the diagnostic, prognostic, and disease-monitoring potential of sCD163 measured in blood, urine, and synovial fluid in autoimmune nephrological and rheumatological diseases. This review is based on a narrative analysis of selected publications investigating the clinical utility of sCD163 in autoimmune kidney and rheumatic diseases, with emphasis on correlations with disease activity, histopathological findings, and clinical outcomes. Urinary sCD163 shows excellent diagnostic accuracy for active lupus nephritis (area under the receiver operating characteristic [AUROC] 0.89-0.998), correlates with histological activity index (but not chronicity), and distinguishes ongoing inflammation from chronic damage during treatment. In IgA nephropathy, it predicts remission failure and greater benefit from corticosteroids. In ANCA-associated vasculitis, it identifies active renal involvement (AUROC 0.95 in multicenter cohorts). In rheumatoid arthritis (RA), serum sCD163 correlates with early disease activity, predicts radiographic progression, and detects subclinical macrophage activation in remission. In spondylarthritis, synovial fluid sCD163 reflects a disease-specific M2-polarized macrophage phenotype distinct from RA. Utility is compartmentalized: urinary levels indicate intrarenal macrophage activation, synovial fluid local joint inflammation, and serum systemic activation. sCD163 is a promising macrophage-specific biomarker across autoimmune diseases, but its compartmentalized nature requires context-specific measurement. Before clinical implementation, assay standardization, multicenter validation, and interventional trials showing the benefit of sCD163-guided management are needed.

Humans↗

PubMed2026

Patient-reported outcomes with tarlatamab in extensive-stage small cell lung cancer after platinum-based chemotherapy: results from the phase 3 DeLLphi-304 trial.

BACKGROUND: Extensive-stage small cell lung cancer (ES-SCLC) is associated with a high symptom burden and impaired health-related quality of life (HRQoL). This prespecified analysis from the phase 3 DeLLphi-304 trial evaluated patient-reported outcomes (PROs) for tarlatamab versus standard-of-care (SoC) chemotherapy following first-line platinum-based therapy. METHODS: DeLLphi-304 is a multicenter, open-label, randomized phase 3 study in adults with ES-SCLC. PROs were assessed using validated instruments, including the EORTC QLQ-C30, EORTC QLQ-LC13, FACT-G GP5, BPI-SF, and the EQ-5D-5L visual analogue scale. Change from baseline, response rates, and time to deterioration in these PROs were analyzed. RESULTS: PRO data from all 509 patients enrolled were evaluated. Compliance with QLQ-C30 and QLQ-LC13 assessments remained above 69% through 19 weeks. A higher proportion of patients receiving tarlatamab achieved symptom or functional improvement at 19 weeks compared with SoC in chest pain (19% vs 10%), cough (35% vs 26%), dyspnea (22% vs 7%), physical functioning (13% vs 8%), and global health status (23% vs 15%), respectively. Tarlatamab also delayed deterioration in symptoms, physical functioning, and pain at worst relative to SoC. FACT-G GP5 results indicated that patients receiving tarlatamab were less bothered by treatment side effects over time. CONCLUSIONS: In addition to its previously reported antitumor activity, tarlatamab demonstrated clinically meaningful improvements in symptoms and HRQoL compared with SoC. These findings support a favorable benefit-risk profile of tarlatamab in patients previously treated for ES-SCLC.

Humans↗

PubMed2026

Providing Feedback on Previous Pain Scores Did Not Affect Weekly Pain Variability: A Cohort-Nested Randomised Study.

BACKGROUND: Spinal pain is one of the leading causes of disability worldwide and repeated symptom monitoring is increasingly used to capture its fluctuating nature. However, repeated pain assessments may be influenced by prior responses, potentially affecting longitudinal patterns of pain reporting. This study examined whether providing feedback on prior pain scores influenced within-person variability in weekly pain intensity ratings and retention over 60 weeks. METHODS: This randomised study evaluating a methodological feature of repeated pain assessment was embedded within a cohort of adults with spinal pain referred to an outpatient hospital clinic. Participants (n = 2448) were randomised 1:1 to weekly pain intensity ratings (0-10 numerical rating scale) either with feedback ('You answered [X] last week') or without feedback. Analyses included participants with ≥ 40% valid responses (n = 1883), of whom 948 received feedback and 935 did not. The primary outcome was within-person variability in pain intensity, quantified using the root mean square of successive differences. Secondary outcomes included additional fluctuation metrics and the number of weeks with missing responses. RESULTS: No meaningful between-group differences were observed for the primary outcome (mean difference -0.04 points [95% confidence interval -0.08 to 0.01]) or secondary outcomes, including retention rates. Sensitivity analyses yielded consistent findings. CONCLUSIONS: Providing participants with feedback on their previous pain score did not meaningfully influence within-person pain variability or retention during 60 weeks of weekly monitoring. These findings aid the interpretation of repeated longitudinal pain assessments by showing that the observed variability was robust to this specific study design. SIGNIFICANCE: This randomised study showed that providing participants with feedback on prior pain scores did not meaningfully alter weekly pain variability or retention during 60 weeks of longitudinal monitoring. These findings contribute to the interpretation of repeated longitudinal pain assessments in spinal pain research and suggest that weekly pain reporting patterns are robust to prior-pain feedback during long-term symptom monitoring.

Humans↗

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.

Humans↗

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↗

PubMed2025

Quantitative Outcomes for Shared Assessment and Management in Forensic Mental Health: A Meta-Analysis and Systematic Review.

Despite leading models of mental health care encouraging user involvement, users in forensic mental health (FMH) report poor involvement given the difficulty in reconciling shared approaches with risk-averse and legally mandated settings. While previous research has demonstrated qualitative benefits to shared approaches in FMH and has led to a proliferation of self-rated assessment tools, there remains to quantify agreement on self-rated tools and to clarify the impact of shared approaches on care. This meta-analysis examines (1) the correlation between clinician and user ratings, (2) the predictive validity of self-ratings for violence, and (3) the effects of shared risk management on violence and restriction in FMH. Five databases were searched from inception to April 2024, selecting for adult FMH inpatients, shared risk assessment, needs assessment or violence management as interventions, and quantitative outcomes (correlation, agreement, predictive validity, and effect on violence or restriction rates). Fifteen quantitative evaluations were retained. One of three planned meta-analyses could be conducted, with seven records providing paired clinician-user t-tests. Eleven more records provided clinical recommendations on operationalizing shared approaches. Random-effects meta-analysis showed a significant and large paired standard difference of .95 (95% CI = [.49,1.42]) across tools, with significant differences in DUNDRUM-3, DUNDRUM-4, and CANFOR sub-models. While acknowledging between-study heterogeneity, results substantiate quantitative differences where clinicians generally rate more needs and lesser progress than users across tools, showing that self-ratings can and should be used to broach collaborative discussions on needs and progress during FMH treatment. There remains an evidence gap for quantitative benefits in care outcomes and a need to standardize agreement measures for future comparisons and clinical sub-group analyses.

Humans↗

PubMed2026

Direct background subtraction LC-MS/MS assay for human plasma progesterone: Full validation and comparative application.

OBJECTIVE: To develop and validate a liquid chromatography-tandem mass spectrometry method based on direct background subtraction for the quantification of endogenous progesterone in human plasma. METHODS: Protein precipitation was used for sample preparation with deuterated progesterone as the internal standard. Chromatographic separation was performed on an ACQUITY C18 column using gradient elution with 0.1% formic acid in water and acetonitrile at a flow rate of 0.3 mL/min. Mass spectrometry was operated in positive electrospray ionization mode with multiple reaction monitoring. Instead of using analyte-stripped matrix or surrogate matrix, authentic plasma was directly used for all validation experiments. Quantitation was achieved by subtracting the background signal, and results were compared with those from the classical method using stripped matrix. RESULTS: Excellent linearity was achieved over 0.1-100 ng/mL (R2 ≥ 0.99). Precision, accuracy, recovery, matrix effect, and stability all met FDA and ICH M10 acceptance criteria. Compared with the classical method, the bias in Cmax and AUC0-t was within ±15%, indicating no significant difference between the two methods. CONCLUSION: The direct background subtraction method avoids laborious preparation of blank matrix, eliminates matrix effect discrepancies, and is simple, efficient, and low-cost. It can serve as a general strategy for endogenous substance determination.

Humans↗

PubMed2026

Multimodal intervention benefits: Responder analysis of J-MINT PRIME Kanagawa trial.

INTRODUCTION: The J-MINT PRIME Kanagawa trial was an 18-month multimodal intervention (incorporating exercise, nutrition, and metabolic management) for dementia prevention. Because the primary analysis showed no significant benefits, we performed an exploratory responder analysis to identify responsive subpopulations. METHODS: We analyzed the Full Analysis Set comprising 188 participants. Classification and regression tree (CART) analysis, applied to the intervention arm, identified baseline predictors of cognitive improvement. These rules were then applied to the entire cohort to evaluate treatment effects on the Mini-Mental State Examination (MMSE) using fully adjusted mixed-effects models for repeated measures (MMRM). RESULTS: CART identified a "Target Group" (N = 108) characterized by baseline profiles such as an MMSE score < 28 or specific metabolic ranges (e.g., LDL-C < 135 mg/dL). Within this target group, the intervention significantly preserved MMSE trajectories compared with the control group (group × time interaction, P = 0.022). In contrast, the Non-Target Group (N = 80), consisting of high-functioning individuals (MMSE ≥ 28), exhibited no significant group × time interaction. DISCUSSION: Multimodal interventions may effectively preserve global cognition in older adults with sub-threshold cognitive decline. Careful targeting of appropriate populations, while considering potential longitudinal measurement artifacts (e.g., practice effects), is essential. These findings provide a hypothesis-generating framework that warrants external validation in future prevention trials.

Humans↗

PubMed2026

Associations between smart infusion pump-electronic health record interoperability and healthcare outcomes: A systematic review.

OBJECTIVE: This study synthesized available evidence on the associations between smart infusion pump-electronic health record (EHR) interoperability and healthcare outcomes. METHODS: A systematic review of PubMed, CINAHL, Embase, and Scopus databases identified 901 records, which were imported into Rayyan® for duplicate removal, independent screening by three reviewers, and resolution of discrepancies. Eligible studies were peer-reviewed, data-driven, and reported associations between smart infusion pump-EHR interoperability and healthcare outcomes. Studies focused solely on technical validation or interoperability prototypes were excluded. A backward citation search identified additional studies. Two reviewers independently extracted and cross-validated study characteristics using standardized templates. Methodological quality was assessed with the Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Twenty records of 14 full-text studies and 6 conference proceedings were included. Most records reported positive associations between smart infusion pump-EHR interoperability and outcomes related to safety (e.g., medication administration errors, safety-reported events, pump alerts, and compliance with interoperability and drug library), operational efficiency (e.g., programming and documentation time and technical issues), financial performance (e.g., charges captured, and cost avoided), and user experience domains. Most studies used observational designs, reflecting real-world interoperability implementations, where controlling confounding factors is challenging. Limited reporting of baseline characteristics, pump type, and sample sizes limited comparability across studies. CONCLUSIONS: Smart infusion pump-EHR interoperability was associated with improvements in patient safety, efficiency, charge capture, and user experience, with variable findings across studies. Future research should use rigorous methodologies and standardized measures, examine relationships across outcome domains, assess limitations of pump-EHR interoperability, and evaluate underexplored outcomes, including team communication, cognitive workload, and AI-enabled pumps. IMPLICATIONS FOR CLINICAL PRACTICE: Interoperability should be viewed as a component of a broader sociotechnical system, in which technology, user, workflow, clinical content, and organizational practices collectively determine overall effectiveness.

Humans↗

PubMed2026

Metformin Adherence and Risk of Polyneuropathy in Type 2 Diabetes Mellitus: An International Matched Cohort Study with Independent Validation.

BACKGROUND: Metformin is a popular first-line glucose-lowering medication for type 2 diabetes mellitus (T2DM). Although metformin reduces the risks of various complications of diabetes, its potential to cause polyneuropathy by depleting vitamin B12 levels is concerning. This study investigated whether the adherence or discontinuation of metformin after adding-on a second-line antiglycemic agent increases the risk of polyneuropathy in patients with T2DM. METHODS: Data from TriNetX were obtained, and patients with T2DM who were receiving second-line antiglycemic agents were divided into metformin-adherent and metformin-nonadherent groups based on prescription claims data. Neuropathy incidence was evaluated using diagnostic claims and nerve conduction examinations. For independent confirmation and external validation of the primary findings, we used data from the National Health Insurance Research Database (NHIRD) of Taiwan. RESULTS: After matching, 58,027 patients were included in each group. Compared with metformin adherent patients, metformin nonadherent patients had a higher risk of polyneuropathy (adjusted hazard ratios [aHR] 1.26; 95% confidence interval [CI] 1.23-1.29; P < 0.001). Risks of diabetic foot ulcer, amputation, neuropathy-related medication use, and bone fracture were also higher among nonadherent patients. Sensitivity analyses confirmed the robustness of findings. In the validation NHIRD cohort (31,384 matched pairs), metformin nonadherence remained associated with increased polyneuropathy risk (aHR 1.25; 95% CI 1.10-1.42; P < 0.001). CONCLUSIONS: Metformin adherence in patients with T2DM who require second-line treatment may reduce the risk of polyneuropathy; vitamin B supplementation may enhance this benefit.

Humans↗