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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

Randomized Trial of Intensive Nurse-Led Follow‑Up Versus Standard Care in Inflammatory Bowel Disease.

BACKGROUND:  Nurses play a key role in inflammatory bowel disease (IBD) management. This randomized controlled trial evaluated intensive nurse-led program in patients with IBD starting advanced therapy. METHODS:  Patients were randomized (1:1) to intensive nurse follow‑up (Arm A) or standard care (Arm B). Both arms received baseline nurse education; Arm A additionally had scheduled nurse calls and visits. Primary outcome was reduction in IBD‑Disk score in W12. Secondary outcomes were W52 reduction, robust response (> 20-point improvement), and IBD-Disk remission (score < 40). RESULTS: Overall, 98 patients were randomized (Arm A: n = 50; Arm B: n = 48) with similar baseline characteristics. Mean baseline IBD‑Disk scores were 49.2 ± 20.7 in Arm A and 42.0 ± 19.8 in Arm B (p = 0.07). At W12, both groups improved, with greater IBD-Disk reductions in Arm A (16.1 ± 22.9 vs. 10.1 ± 20.1, p = 0.09). At W52, improvement was greater in Arm A (18.4 ± 20.7 vs 9.4 ± 17.8; p = 0.08). More patients achieved robust response in Arm A (49% vs 21%, p = 0.013) at W12. By W52, IBD-Disk remission was achieved by 22/25 (88%) patients in Arm A vs 18/28 (64%) in Arm B (p = 0.045). CONCLUSIONS:  In this pilot randomized trial, intensive nurse-led follow-up did not significantly improve IBD-Disk at week 12, yet favorable trends of functional outcomes were observed. Intensive nurse‑led follow‑up program may improve quality of life in patients with IBD. These findings support the integration of specialist IBD nurses to improve patient‑centered outcomes.

Humans↗

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.

Humans↗

PubMed2026

Risk Factors and Predictive Model for Postoperative High Myopia in Children Undergoing Congenital Cataract Surgery With Intraocular Lens Implantation.

PURPOSE: To identify risk factors associated with the development of high myopia following congenital cataract surgery and to establish a robust predictive model. DESIGN: Retrospective clinical cohort study. SUBJECTS: This retrospective study included 106 pediatric patients who underwent congenital cataract surgery with primary IOL implantation (mean follow-up 8.19 years). The model was externally validated in an independent cohort of 72 patients with a mean follow-up of 7.83 years. METHODS: Preoperative and postoperative ocular biometric parameters were collected. Risk factors for postoperative high myopia were analyzed using Cox proportional hazards regression, which served as the basis for model construction. The predictive performance of the model was rigorously evaluated for discrimination and calibration. Discriminative ability was quantified using Harrell's C-index and the area under the receiver operating characteristic curve (AUC). Model calibration was assessed via calibration plots by comparing predicted probabilities with actual observed outcomes. Internal validation was performed using a bootstrapping method (500 iterations) to ensure model stability and adjust for potential overfitting. RESULTS: An initial postoperative refraction of <+0.75D, and a higher IOL Power to Axial length Ratio (IOL/AL ratio) were identified as significant risk factors for the development of postoperative high myopia. Shorter preoperative axial length was associated with a greater magnitude of postoperative myopic shift. The predictive model demonstrated robust performance, achieving a C-index of 0.711 (internal validation C-index: 0.713). The area under the receiver operating characteristic curve (AUC) values for predicting high myopia at 5 and 10 years were 0.858 and 0.745, respectively. Furthermore, calibration curves demonstrated excellent agreement between the predicted and observed outcomes throughout the follow-up period. In external validation, the model achieved a C-index of 0.825, 5-year AUC of 0.833, and 10-year AUC of 0.713. CONCLUSIONS: Our analysis established that initial postoperative refraction <+0.75D, and an elevated IOL/AL ratio are key determinants of high myopia risk following surgery. Shorter preoperative axial length was associated with a greater magnitude of postoperative myopic shift. This predictive framework provides clinicians with a practical tool to optimize preoperative IOL selection and identify high-risk infants who require vigilant myopia prevention and balanced amblyopia management.

Humans↗

PubMed2026

Preparation and study of non-thrombotic and biostable sulfobetaine-modified small-diameter polyurethane vascular grafts.

A novel sulfobetaine-modified polysiloxane-polycarbonate polyurethane (ZSiPCU) was synthesized. In vitro characterizations revealed that polysiloxane surface enrichment endowed the material with excellent biostability. Importantly, sulfobetaine zwitterions formed a robust hydration layer, effectively suppressing protein adsorption and platelet adhesion to ensure outstanding hemocompatibility. Furthermore, the material supported the adhesion and proliferation of vascular endothelial cells, confirming its cytocompatibility, while its elastomeric matrix provided rapid mechanical self-sealing capabilities. Electrospun ZSiPCU grafts were evaluated in a 3-month rat abdominal aorta model, maintaining high patency rates and facilitating in situ luminal endothelialization and smooth muscle cell remodeling. Additionally, superior puncture resistance of the grafts was demonstrated by puncture tests, with complete hemostasis achieved within 2 mins through mechanical self-sealing.

Polyurethanes↗

PubMed2026

Recovering membrane interaction kinetics of single molecules from 3D tracking data.

Interactions between cytosolic biomolecules and the bacterial inner membrane are fundamental to many cellular processes, yet directly measuring their binding kinetics in living cells remains challenging. Conventional 2D single-molecule tracking analyses can be insufficient, particularly when membrane association does not markedly alter the diffusion rate. Here, we present a method to recover membrane interaction kinetics from 3D single-molecule trajectories in rod-shaped bacteria. Using simulated 3D tracking data, we identify membrane-associated motion by quantifying how well short trajectory segments follow the circular curvature of the cell membrane. The resulting measure is further analyzed using a hidden Markov modeling framework, enabling robust discrimination between cytosolic and membrane-bound states and capturing the dynamics of state transitions without requiring diffusion-rate changes or direct colocalization with membrane markers. This work establishes a general framework for extracting membrane interaction kinetics from 3D single-molecule tracking data in live bacteria and highlights the value of realistic microscopy simulations for quantitative interpretation and systematic bias assessment.

Kinetics↗

PubMed2026

Transcription regulation of cell fate plasticity - from embryonic development to tissue regeneration.

Cell fate plasticity refers to the capacity of cells sharing the same genome to alter, reverse, or reconfigure their identity under physiological, pathological, or experimental conditions. This property underlies embryonic development, cellular reprogramming, and tissue regeneration, but becomes progressively restricted as lineage identity is stabilized. Embryonic development represents an intrinsic process of fate transitions, whereas reprogramming and regeneration reveal how differentiated cells can dedifferentiate or transdifferentiate under specific conditions. Across these contexts, plasticity is governed by multilayered regulatory networks involving transcription factors, epigenetic regulators, cofactors, and the core transcription machinery. Robust regulatory programs stabilize cell identity, whereas stochastic fluctuations in gene expression and chromatin state can prime cells for fate transitions, adding a tunable dimension to plasticity control. In this review, we synthesize recent advances in the regulation of cell fate plasticity across development, reprogramming, and regeneration, highlighting how transcription factors, epigenetic modifications, transcriptional cofactors, and core transcription machinery cooperate to control cell fate decisions and plasticity.

Animals↗

PubMed2026

GLP-1 Receptor Agonists and Musculoskeletal Outcomes: A Systematic Literature Review and Meta-Analysis.

INTRODUCTION: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are increasingly used for the treatment of type 2 diabetes and obesity, but their effects on musculoskeletal health remain completely misunderstood. OBJECTIVE: This systematic review/meta-analysis aims to synthesise clinical data on the effects of GLP-1 RAs on key relevant bone, muscle, and joint outcomes. METHODS: MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL) (both via Ovid® platform) and Embase were searched from inception to March 2025 to identify relevant randomised controlled trials (RCTs) or real-world evidence (RWE) studies to be included. This bibliographic search was completed manually. A random-effect model meta-analysis was performed for any outcome reported in at least 2 studies. Subgroup analyses were performed on the type of GLP-1 RAs, type of comparator used and study design. Sensitivity analyses (i.e., leave-out sensitivity analyses and analyses restricted to the most adjusted effect estimate) were performed to test the robustness of the data. The strength of evidence was assessed using GRADE. This work has been performed in adherence with PRISMA statement. (PROSPERO Record ID: CRD420251024082). RESULTS: From 1148 potentially relevant references, 60 articles (46 RCTs, 13 RWE studies and 1 pharmacovigilance study, comprising 1,250,717 individuals) met our inclusion criteria. Different GLP-1 RAs were represented across the panel of studies, i.e., semaglutide, liraglutide, exenatide, dulaglutide, tirzepatide (dual agonist gastric inhibitory polypeptide [GIP]/GLP-1) and others. No effect on bone outcomes (i.e., bone mineral density [all sites] and fractures [all sites]) were observed when the meta-analytical models included the most adjusted effect size. Regarding muscle outcomes, a significant decrease of lean body mass/fat-free mass was consistently observed with GLP-1 RAs in the global model (k = 28, standardised mean difference [SMD] 0.52, 95% confidence interval [CI] -0.8; -0.23, I2 88%, p-value for heterogeneity <0.0001), which remained robust in all sensitivity analyses. Subgroup analyses showed that the effect was mainly driven by liraglutide and semaglutide, with a decrease in lean body mass/fat-free mass observed when GLP-1 RAs were compared with placebo. No publication bias was found. Regarding joint outcome, models revealed no significant change in The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain, physical function and stiffness. CONCLUSIONS: This meta-analysis is the first to investigate the effects of GLP-1 RAs on a large panel of musculoskeletal health outcomes. While no significant effects were observed on bone- or joint-related outcomes, GLP-1 RAs were associated with reductions in lean body mass/fat-free mass, although the certainty of evidence was low and these changes appeared largely related to weight loss. Whether these changes translate into clinically meaningful impairments in muscle function or physical performance remains uncertain. Further studies in this field, including those looking at muscle function, strength or performance and using multivariate models considering confounding are needed to better reinforce the models and final findings.

Journal Article↗

PubMed2026

Single-nucleus transcriptomics reveals cell type-specific remodeling and epilepsy-associated microglia.

Temporal lobe epilepsy (TLE) is the most common acquired epilepsy, causing refractory seizures and cognitive deficits. We performed single-nucleus RNA sequencing on hippocampal tissue from mice 3 and 6 weeks following pilocarpine-induced status epilepticus, a robust model of TLE. Epilepsy samples showed reductions in Cck and Lamp5-Lhx6 interneuron subclusters, alongside increases in Cajal-Retzius cells, dentate granule (DG) cell precursors, and a mature DG cell subcluster. Among glia, an astrocyte subcluster and a markedly expanded microglia sublcuster were increased. We term this microglia population epilepsy-associated microglia (EAM). The transcriptomic profile of EAM overlaps with microglia described in models of Alzheimer's disease and traumatic brain injury, including enrichment of Myo1e and Igf1. EAM display amoeboid morphology, can be found in clumps around pyramidal and granule cell body layers, and exhibit enlarged vesicles and mitochondria. Cell-cell interaction analysis predicts DG cells as their primary interaction partners. This dataset defines transcriptomic programs underlying key cellular alterations in TLE, enabling mechanistic dissection of epileptogenesis.

TLE↗

PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗

PubMed2026

Making waves: toward systems-level interpretation of hormonal and endogenous biomarkers in wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has proven invaluable for population health monitoring, most notably during the COVID-19 pandemic. Yet current WBE largely relies on exogenous markers such as drugs, pathogens, and their metabolites, limiting surveillance to what communities are exposed to. We argue for expanding WBE towards endogenous biomarkers, particularly hormones, which provide insights into physiological stress, metabolic function, and endocrine activity. Hormone-based WBE offers new opportunities to capture population-level biological responses to societal and environmental stressors, disasters, and chronic disease burdens at the community scale. This perspective outlines a systems-level framework for integrating hormonal signals in wastewater with clinical data, behavioral indicators, environmental factors, and digital markers to support more robust and context-aware public health surveillance. We highlight key technical considerations, interpretive challenges, and opportunities for translational pilot studies. By moving beyond exposure tracking toward more integrated interpretation of biological responses, hormone-informed WBE may contribute to more resilient, inclusive, and actionable public health infrastructure.

Humans↗

PubMed2026

Physical Appearance Anxiety and Eating Disorders Symptomatology: A Systematic Review and Meta-Analysis.

The present study aimed to assess the link between physical appearance anxiety (PAA) and eating disorder (ED) symptomatology by a meta-analysis of existing literature. Eligible studies were searched across six electronic databases up until November 20, 2025. Pooled effect sizes (r) were calculated using random-effects models. Potential variables that influence effect heterogeneity were analyzed by univariable and multivariable meta-regressions. Influence analyses and a three-parameter selection model (3PSM) were used to assess robustness of the results and publication bias. Twenty-seven effect sizes from 21 studies (N = 5261) were obtained. The results indicated a strong association (i.e., r = 0.559) between the two variables under consideration, which was notably stronger (i) among females compared to males; and (ii) for overall eating disorder symptoms rather than bulimic symptoms. The results of this study advocate for further investigation into the effectiveness of addressing anxiety responses related to personal body traits, particularly among females, within the context of preventing and treating eating disorders.

Humans↗

PubMed2026

Systematic evaluation of one-dimensional-to-two-dimensional near-infrared spectroscopy transformations with deep learning for quantifying coconut sap adulteration.

Near-infrared (NIR) spectroscopy have limitations when combined with deep learning (DL) algorithms because they rely on low-dimensional datasets. Therefore, we investigated the potential of transforming one-dimensional (1D) NIR spectra into two-dimensional (2D) spectrograms using synchronous and asynchronous techniques and the continuous wavelet transform (CWT) and their effectiveness by integrating with DL for detecting adulteration in coconut sap. NIR spectra (12,500-4000 cm-1) were collected from binary mixtures (0%-100%;w/w). The performance of all DL (convolutional neural networks-CNN, AlexNet and ResNet) models was compared with that of partial least squares (PLS). The models were ranked in the mentioned order based on their performances: 2D-CWT > 2D-asynchronous > 2D-synchronous > 1D/2D-PLS. The important features of the best model can be explained and visualized using gradient-weighted-class-activation-mapping. The findings highlight that the 1D-to-2D NIR data transformation combined with DL is a highly robust approach because it addresses the feature representation gap in NIR data and effectively captures the spatial-spectral correlations.

Spectroscopy, Near-Infrared↗

PubMed2026

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans↗

PubMed2026

Metabolic engineering of Candida yeasts for biotechnological applications.

Candida yeasts represent a versatile yet underexploited platform for industrial biotechnology. These yeasts utilize a remarkably broad range of carbon sources, particularly for hydrophobic carbon sources, coupled with robust growth and diverse biosynthetic capacities, making them promising hosts for sustainable production of chemicals, fuels, and proteins. Despite these advantages, industrial deployment of Candida species has been hindered by concerns regarding opportunistic pathogenicity and the historical lack of efficient genetic manipulation tools, leading to a substantial gap between metabolic potential and practical utilization. Recent advances in functional genomics, genome editing, and systems metabolic engineering are rapidly overcoming these barriers, enabling more precise and efficient strain development. In this review, we systematically summarize recent progress in the metabolic engineering of Candida species as microbial cell factories, with particular emphasis on expanding genetic toolkits, utilizting renewable and non-conventional carbon sources, and biosynthesizing high-value compounds. In addition, we propose a biosafety-oriented classification framework to support their safe industrial deployment. Finally, we discuss current challenges and emerging opportunities, emphasizing that the synergy of synthetic biology and artificial intelligence-driven design holds the key to unlocking the biotechnological potential of Candida yeasts.

Candida↗

PubMed2026

A smartphone-integrated Pt@Cu-HCF nanozyme-based paper sensor for on-site determination of total antioxidant capacity in marine oils.

Total antioxidant capacity (TAC) serves as a key indicator for evaluating the nutritional quality of foods. In this study, we designed a platinum-embedded copper hexacyanoferrate (denoted as Pt@Cu-HCF) nanozyme that exhibits high oxidase-like activity, efficiently catalyzing the oxidation of chromogenic substrates to generate robust colorimetric signals. Antioxidants quench hydroxyl radicals (∙OH) produced during the catalytic process, leading to a concentration-dependent suppression of the color signal. Leveraging this mechanism, a smartphone-integrated, colorimetric paper sensor for on-site TAC quantification was developed, using vitamin E as the calibration standard. The sensor was applied to determine TAC in fish oil, algal oil, and krill oil, demonstrating a linear response range of 9.78-312.5 μM and a limit of detection (LOD) of 6.41 μM. Validation using real-world marine oil samples showed excellent agreement with a commercial assay kit, confirming the reliability and practical applicability of this portable sensor for TAC measurement in complex biological matrices.

Antioxidants↗

PubMed2026

Human-Centered Workspace Optimization: A 2 × 2 Factorial Study of Adjustable Furniture and Indoor Environmental Quality.

Small workspaces function as integrated systems, yet ergonomic furniture and indoor environmental conditions are usually evaluated separately. A six-site, assessor-blinded, randomized 2 × 2 factorial controlled study was conducted of two multicomponent packages-adjustable furniture and optimized indoor environmental quality (IEQ)-among 240 office workers for four weeks. Each group included 60 participants. Overall comfort in week 4 was highest for both packages (5.62 ± 0.53 versus 3.99 ± 0.60 with fixed furniture and basic IEQ). In a site-adjusted factorial model with HC3 robust standard errors, the adjustable-furniture effect was 0.86 points (95% confidence interval [CI], 0.62-1.09), the optimized-IEQ effect was 0.34 points (95% CI, 0.12-0.55), and their interaction was 0.44 points (95% CI, 0.14-0.74). Adjustable furniture improved postural comfort and reduced neck and lower back discomfort; optimized IEQ improved environmental comfort; both packages improved perceived productivity, satisfaction, and fatigue. The task-accuracy interaction did not remain significant after false-discovery-rate adjustment, and exploratory mediation and spline analyses did not support indirect or nonlinear effects. These results support coordinated ergonomic and environmental implementation while preserving distinct outcome pathways.

Interior Design and Furnishings↗

PubMed2026

Association between anaemia and osteoporosis: a systematic review and meta-analysis.

BACKGROUND: Osteoporosis significantly impacts global morbidity. Recent evidence suggests anaemia may contribute to osteoporosis risk. This systematic review and meta-analysis investigates this association. METHODS: PubMed, Scopus, EBSCO, and ScienceDirect were searched for papers. Studies with definition of anaemia and assessing osteoporosis outcomes were included. Meta-analysis utilized random-effects models (DerSimonian-Laird method), and study quality was assessed via Newcastle-Ottawa Scale (NOS). Analyses were performed using R Studio. RESULT: Eighteen studies (861,540 participants) were analyzed. Anaemia significantly increased osteoporosis risk in univariate analysis (OR 1.62; 95% CI 1.33-1.98; p < 0.001), despite high heterogeneity (I2 = 92.7%). The results remain significant in studies that reported multivariate analysis (OR 2.01; 95% CI 1.26-3.21; p = 0.004). Sensitivity analyses confirmed the robustness of our result. CONCLUSION: Anaemia significantly associated with osteoporosis, emphasizing the need for targeted screening in anaemic individuals. Further studies should consider incorporating anaemia into osteoporosis and fracture prediction tools.

Humans↗