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PubMed2026

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

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

Humans↗

PubMed2026

Spinal meningiomas: histopathological grading using a benchmark radiomics model with notes on disease control.

OBJECTIVE: Spinal meningiomas (SMs) are common primary spinal tumors for which surgery is considered the first-line treatment when safe and feasible. The ability to extrapolate the tumor grade from preoperative imaging may significantly inform early patient expectation-setting regarding recurrence. Building on radiomics studies in cranial meningiomas, the authors aimed to construct a benchmark radiomics model to preoperatively identify the histological grade of SMs. METHODS: Institutional surgical records from May 2012 to November 2025 were queried for pathology-confirmed meningiomas below the foramen magnum, with preoperative contrast-enhanced imaging available for segmentation. SMs were classified as low-grade (WHO grade 1) and high-grade (WHO grade 2 tumors and grade 1 tumors with atypia). Tumors were manually segmented, and features were extracted using the PyRadiomics software package. An ensemble model of k-nearest neighbors, random forest, and support vector machine classifiers was trained using nested cross-validation on a subset of 10 features to differentiate tumor grades. Clinical data for the cohort were also extracted, and disease control in an adjunctive clinical series was assessed. RESULTS: Seventy-four patients were included in radiomics analysis, with an area under the receiver operating characteristic curve of 0.879 and a mean F1 score of 0.748. The model's top 5 features were all texture features that differed significantly (p < 0.05) across low- and high-grade SMs. These included measures of tumor textural and contrast-enhancement heterogeneity, with overlap with features reported in radiomics models for histological grading of intracranial meningiomas. Fifty-five patients with a median radiographic follow-up of 22.2 (range 1.9-86.4) months remained for clinical analysis after exclusion of patients with less than 1 month of follow-up and syndromic meningiomas. Four recurrences occurred at a median of 20.8 (range 1.8-41.8) months. High-grade tumor pathology did not significantly impact progression-free survival (p = 0.682, log-rank test; Cox regression high vs low grade hazard ratio [HR] 0.62, 95% CI 0.06-6.11, p = 0.685). Subtotal resection was associated with poorer progression-free survival than gross-total resection (p = 0.004, log-rank test; Cox regression subtotal vs gross-total resection HR 10.62, 95% CI 1.46-77.05, p = 0.019). These findings remain contextualized within a relatively limited follow-up window and small recurrence event count, suggesting a need to characterize the interplay between tumor grade and extent of resection as drivers of local disease control in SMs. CONCLUSIONS: A preoperative radiomics model can stratify high-grade SMs using open-source tools applied to single-institution data.

Humans↗

PubMed2026

Clinical Efficacy and Learning Curve of Far-Lateral Approach (FLA) in Uni-Portal Non-Coaxial Spinal Endoscopic Surgery (UNSES) in the Treatment of Lumbar Degenerative Diseases: A Prospective Study.

BACKGROUND: Uniportal non-coaxial spinal endoscopic surgery (UNSES) via far-lateral approach (FLA) is an innovative minimally invasive procedure for lumbar degenerative diseases, particularly far-lateral disc herniation and foraminal stenosis. However, complex lateral lumbar anatomy and strict endoscope-instrument coordination create a distinct learning curve that may compromise early surgical efficiency and safety. This study aimed to evaluate the efficacy and safety, quantify the learning curve, and to provide clinical guidance for the standardized promotion and application of this technology. METHODS: A total of 40 consecutive patients with lumbar degenerative diseases who underwent UNSES via FLA by a single surgeon between January 2025 and December 2025 were included. All data were analyzed using SPSS 26.0 statistical software (IBM, USA). Primary outcomes included operation time, blood loss, fluoroscopy frequency, and intraoperative complication rate. Secondary outcomes were VAS, ODI, and modified Macnab criteria at 1, 3, and 6 months postoperatively. The learning curve and the inflection point of the learning curve was determined using cumulative sum (CUSUM) analysis. The differences in clinical indicators between early and proficient stage were compared. RESULT: Operation time, blood loss, and fluoroscopy times decreased significantly with case accumulation (p < 0.05). CUSUM identified an inflection point at the 16th case, after which operation time stabilized at (55.3 ± 8.6) min, much shorter than the early phase (89.5 ± 10.3) min (p < 0.001). Before the 16th case, the curve was in an upward trend; after the 16th case, the curve tended to be flat, indicating the proficiency stage. Postoperative VAS and ODI improved significantly than those before surgery at each follow-up time (p < 0.05). There was no significant difference in postoperative VAS score and ODI between the two groups at each follow-up time point (p > 0.05). The total complication rate was 12.5% (5/40), were cured by conservative treatment. The total excellent-good rate was 90.0% (36/40). L5/S1 and Bertolotti's syndrome were independent factors affecting the learning curve. CONCLUSION: UNSES via FLA is a safe and effective minimally invasive technique for treating complex lumbar degenerative diseases. It has a certain learning curve, and the inflection point is about the 16th case. After mastering the key techniques such as anatomical positioning, endoscopic manipulation and hemostasis, the surgeon can gradually reach the proficiency stage, with significantly improved surgical efficiency and clinical efficacy, and controllable complications. This study provides a theoretical basis for the clinical training and technology promotion of UNSES via FLA.

Humans↗

PubMed2026

Smoke-Free Home Intervention in Permanent Supportive Housing: A Cluster Randomized Clinical Trial.

IMPORTANCE: Chronic diseases related to tobacco use and secondhand smoke exposure are the leading causes of death among formerly homeless adults living in permanent supportive housing (PSH) in the US. OBJECTIVE: To evaluate the efficacy of a brief, smoke-free home intervention in promoting voluntary smoke-free home adoption among PSH residents. DESIGN, SETTING, AND PARTICIPANTS: In this cluster randomized clinical trial, data collection occurred from January 11, 2022, to March 31, 2025. Participants were residents aged 18 years or older who smoked cigarettes at home in 40 multiunit PSH sites in the San Francisco Bay area, randomized to intervention or waiting list control clusters, and housing staff who worked at the study sites. INTERVENTION: Residents in intervention sites received one-on-one in-person coaching from research staff on adopting a smoke-free home; waiting list control site residents received no interventions during the study but were offered the intervention once the intervention group completed follow-up. Staff in both intervention and control sites received training on providing brief tobacco cessation coaching. MAIN OUTCOMES AND MEASURES: Primary outcomes were smoke-free home adoption for at least 90 days and 7-day carbon monoxide-verified point prevalence abstinence (PPA; expired carbon monoxide level ≤5 ppm) at 6 months. Secondary outcomes were any adoption (≥1 day) of a smoke-free home in the past 90 days among residents and changes in Smoking Knowledge, Attitudes, and Practices (S-KAP) scores among staff. RESULTS: The trial enrolled 400 residents (mean [SD] age, 54.5 [10.7] years; 251 [63.1%] male), 191 in the intervention and 209 in the control cluster. At 6 months, 13 residents (6.8%) in the intervention and 10 (4.8%) in the control group adopted a smoke-free home for at least 90 days (odds ratio [OR], 1.45; 95% CI, 0.69-3.07). Few residents achieved 7-day PPA, though more intervention residents (12 [6.3%]) achieved it compared with controls (2 [1.0%]) (OR, 6.94; 95% CI, 1.69-28.45). Intervention residents had greater odds than control residents of any smoke-free home adoption of at least 1 day (121 [63.4%] vs 77 [36.8%]; adjusted OR, 3.83 [95% CI, 2.63-5.57]). Among staff, mean (SD) S-KAP scores increased at 6 months vs baseline for beliefs (by 0.21 [0.55] points) and practices (by 0.24 [0.61] points) pertaining to providing cessation treatment. CONCLUSIONS AND RELEVANCE: In this cluster randomized clinical trial, the brief intervention did not result in a significant increase in smoke-free home adoption for at least 90 days, though more residents in the intervention than the control group attempted adoption for at least 1 day. These findings support the scalability of this approach to reduce smoking in PSH, but more intensive interventions may be needed to sustain intervention effects. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04855357.

Humans↗

PubMed2026

From fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

Humans↗

PubMed2026

Teaching Acute Coronary Syndrome High-Risk ECG Interpretation and Clinical Decision-Making Through FOAMed Videos and Podcast Versus Print-Based Materials Among Emergency Care Providers: Randomized Controlled Mixed Methods Trial.

BACKGROUND: Accurate interpretation of high-risk acute coronary syndrome (ACS) electrocardiograms (ECGs) is essential for early diagnosis and timely reperfusion, yet substantial deficits persist across health care professions. Digital self-learning formats such as FOAMed (Free Open Access Medical Education) are widely used, but their effectiveness has rarely been evaluated for complex, high-risk ACS ECG patterns. Existing ECG education studies often focus on students or single professional groups and established ST-segment elevation myocardial infarction (STEMI) criteria, leaving newer guideline-recognized STEMI equivalents, selected emerging occlusion myocardial infarction (OMI)-related patterns, and interprofessional emergency care underrepresented. OBJECTIVE: This study aimed to compare the effectiveness of FOAMed podcast and videos versus traditional print-based materials for teaching high-risk ACS ECG patterns and related clinical decision-making in emergency providers. METHODS: We conducted a prospective, interprofessional, controlled mixed methods trial across 5 training sites in Germany. Paramedics, prehospital emergency physicians, and emergency department clinicians received either a FOAMed multimedia module or print-based materials through concealed allocation; deviations from the intended 1:1 ratio resulted from participant no-shows. The intervention consisted of a 30-minute supervised self-learning session. In total, 103 participants were allocated to FOAMed (n=45) or print-based materials (n=58). Two coprimary outcomes were assessed: ECG interpretation accuracy and text-based ACS clinical decision-making. Secondary outcomes included subjective confidence, learning experience, and exploratory qualitative free-text responses. Outcome assessment was automated and blinded; mixed ANOVA was the primary analysis. The study was not prospectively registered because it assessed educational outcomes in health care professionals rather than patient health outcomes. RESULTS: All 103 participants completed the study. Both groups improved, with greater gains in the FOAMed group: ECG interpretation increased from 55% to 65.5% and text-based ACS clinical decision-making from 45% to 68%, versus 57% to 60% and from 47% to 63%, respectively, in the print-based group. Effect sizes were η²=0.055 for ECG interpretation and η²=0.044 for clinical decision-making. Exploratory subgroup analyses provided no evidence of differential effects across age, gender, or professional background and were likely underpowered. Qualitative responses (46 and 37 entries) provided contextual insights into perceived clarity, engagement, and practical relevance supporting the quantitative findings. CONCLUSIONS: This study is innovative in directly comparing a curated FOAMed multimedia module with selected print-based materials in an interprofessional emergency care population. It differs from existing research by focusing on subtle, emerging ischemic patterns and evaluating realistic, time-limited self-learning formats. The findings provide evidence that curated FOAMed resources can produce greater short-term improvements in ECG interpretation and text-based ACS clinical decision-making than traditional print-based materials in this setting. Although implications for clinical performance remain hypothetical, concise, high-quality digital modules may represent a practical supplement to structured continuing education in emergency care.

Humans↗

PubMed2026

Cognitive Behavioral Therapy vs Media Literacy for Prevention of Gaming Disorder and Unspecified Internet Use Disorder: A Randomized Clinical Trial.

IMPORTANCE: Mitigating the harmful effects of digitalization on youth mental health is essential. OBJECTIVES: To evaluate the effectiveness of cognitive behavioral therapy (CBT) compared with a media literacy-based intervention for gaming disorder and unspecified internet use disorder and to determine whether universal or indicated prevention yields stronger benefits. DESIGN, SETTING, AND PARTICIPANTS: PROTECTconfirm was a randomized clinical trial conducted from July 1, 2020, to August 31, 2024, across 44 secondary schools in Baden-Württemberg, Germany, with 1-, 4-, and 12-month follow-up. All students were included in universal prevention analyses, whereas indicated prevention analyses included a subgroup of adolescents at high risk meeting 2 or more Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) criteria for gaming disorder or unspecified internet use disorder at baseline. INTERVENTIONS: Students were individually randomized within 90 classes to PROTECTtraining, a CBT-based program; or PROTECTinfo, a structurally parallel media literacy program. Both consisted of four 90-minute sessions delivered weekly during school hours by trained local prevention professionals under live supervision and adherence protocols. MAIN OUTCOMES AND MEASURES: The primary outcome was gaming disorder symptom severity and unspecified internet use disorder symptom severity, assessed at 12 months with a modified version of the Video Game Dependency Scale. Secondary outcomes included internalizing, externalizing, and transdiagnostic symptoms. Primary and secondary outcomes were analyzed according to the intention-to-treat principle. RESULTS: A total of 1793 students were randomized to PROTECTtraining (n = 896; mean [SD] age, 13.1 [1.5] years; 498 male students [56.1%]) or PROTECTinfo (n = 897; mean [SD] age, 13.1 [1.5] years; 484 male students [54.8%]). Participants in the subsample of 205 adolescents at high risk showed significantly lower 12-month severity of gaming disorder and unspecified internet use disorder symptoms with PROTECTtraining than with PROTECTinfo (mean [SD] Modified Video Game Dependency Scale score: 14.7 [9.7] vs 17.7 [10.3]; within-group Cohen d = -0.91 [95% CI, -1.10 to -0.72] vs Cohen d = -0.61 [95% CI, -0.80 to -0.42]; between-group Cohen d = -0.30 [95% CI, -0.55 to -0.05]), but not in the total sample (mean [SD] Modified Video Game Dependency Scale score: PROTECTtraining, 8.8 [8.3] vs PROTECTinfo, 9.4 [8.4]; within-group Cohen d = -0.11 [95% CI, -0.18 to -0.05] vs Cohen d = -0.04 [95% CI, -0.11 to 0.02]; between-group Cohen d = -0.07 [95% CI, -0.16 to 0.01]). Secondary outcomes did not differ significantly between groups. CONCLUSIONS AND RELEVANCE: In this randomized clinical trial of 1793 adolescents, the CBT-based intervention reduced gaming disorder symptoms and unspecified internet use disorder symptoms more effectively than the media literacy-based intervention among adolescents at high risk. These findings support the use of CBT-based approaches primarily within indicated, rather than universal, prevention. TRIAL REGISTRATION: German Clinical Trials Register (DRKS) trial registration: DRKS00033989.

Humans↗

PubMed2026

Effectiveness of Mobile-Delivered Exercise and Yoga Programs on Depressive Symptom Reduction in Employees: Randomized Controlled Trial.

BACKGROUND: Mental health challenges such as stress and depression are prevalent among employees. Mobile health platforms that deliver exercise or yoga interventions offer a promising approach to improve mental health outcomes in this population. OBJECTIVE: This study aimed to assess the effectiveness of 12-session adaptive moderate-intensity exercise and yoga programs delivered via a motion-detecting digital platform in reducing stress and depressive symptoms among employees. METHODS: This was an unblinded, 3-arm, parallel-group, randomized controlled trial conducted at Seoul National University Bundang Hospital and Boramae Medical Center between November 2023 and January 2024. Eligible participants were full-time employees. Seventy-five participants were randomly assigned to an exercise, a yoga, or a cognitive behavioral therapy-based self-care control group using computer-generated randomization. The exercise and yoga groups engaged in motion-detecting, adaptive physical activity training, whereas the control group accessed mobile-based, self-directed stress management educational materials. The intervention was largely automated, with no individualized therapeutic guidance provided. Allocation was concealed until trial entry. All recruitment and outcome assessments were conducted in person at the hospitals. The primary outcomes were perceived stress and depressive symptoms, whereas the secondary outcomes included posttraumatic stress, insomnia severity, cognitive stress response, occupational stress, and burnout. Physiological outcomes were assessed using heart rate variability and electroencephalography. Measurements were collected at baseline, immediately after the intervention, and at 4-week follow-up. Data were analyzed using a multivariate linear model to evaluate the main effects of time, group, and time×group interactions. RESULTS: Of the 75 randomized participants (exercise: n=24, 32%; yoga: n=25, 33.3%; and control: n=26, 34.7%), 71 (94.7%) who completed at least 9 of the 12 sessions (≥40 min each) were included in the outcome analysis (exercise: n=21, 29.5%; yoga: n=24, 33.8%; and control: n=26, 36.6%). For the coprimary outcomes, the group×time interaction for depressive symptoms (Patient Health Questionnaire-9) approached but did not reach the Bonferroni-corrected threshold (F4,136=2.71; P=.03; adjusted α=.025); however, planned pairwise comparisons revealed significantly greater improvement in the yoga group compared to the control group at 4-week follow-up (β=-3.67; adjusted P<.001). For the Perceived Stress Scale, the interaction was not significant (P=.29), although a significant main effect of time (P<.001) indicated overall stress reduction across all groups. For secondary outcomes, a significant group×time interaction was found for the Cognitive Stress Responses Scale (P=.003), indicating differential trajectories of improvement. The yoga group showed a consistent linear decrease, whereas the exercise group showed immediate but less sustained gains. CONCLUSIONS: Digitally delivered adaptive yoga programs demonstrated superior and sustained improvements in depressive symptoms and Cognitive Stress Responses Scale scores compared with the active cognitive behavioral therapy-based self-care control group. However, the exercise program showed more modest and less sustained effects, warranting further investigation using larger samples.

Adult↗

PubMed2026

Holmium laser enucleation of the prostate for the treatment of lower urinary tract symptoms in men with benign prostatic hyperplasia.

RATIONALE: A range of surgical options is available for the treatment of benign prostatic hyperplasia (BPH), including holmium laser enucleation of the prostate (HoLEP). The evidence is unclear regarding differences in functional, perioperative, and morbidity outcomes between these modalities. OBJECTIVES: To assess the effects of holmium laser enucleation of the prostate compared with other surgical treatments for lower urinary tract symptoms in men with benign prostatic hyperplasia. SEARCH METHODS: We searched multiple databases (including MEDLINE, Embase, CENTRAL, Web of Science, LILACS, and the International HTA database), trial registries, and conference abstracts through April 08, 2026. ELIGIBILITY CRITERIA: We only included randomized trials of men over 40 years of age with a prostate volume of at least 20 mL (assessed by digital rectal examination, ultrasound, or conventional imaging) who exhibited lower urinary tract symptoms (LUTS) defined by an International Prostate Symptom Score (IPSS) of eight or greater undergoing surgical interventions for BPH. OUTCOMES: The critical outcomes measured were the urologic symptoms score, the quality-of-life score, and major adverse events. The important outcomes measured were: re-treatment, erectile function, ejaculatory function, transfusions, acute urinary retention, indwelling urinary catheter duration, and hospital stay duration. RISK OF BIAS: We used the Cochrane risk of bias tool (RoB 1) to assess for potential sources of bias on a study and outcome level basis. SYNTHESIS METHODS: We pooled outcome data using the random-effects model and performed meta-analyses using the Mantel-Haenszel method. We assessed statistical heterogeneity in the pooled data by visually inspecting forest plots and using the I2 statistic to quantify it. We used the GRADE framework to assess the certainty of evidence. INCLUDED STUDIES: We included 52 trials that included 6242 participants that compared HoLEP to other surgical interventions for benign prostatic hyperplasia. The median age of participants across the studies ranged from 65 to 74 years. The baseline prostate volume ranged from 30 cc to 142 cc. Baseline IPSS scores ranged from 19.6 to 28.6 (range 0-35). SYNTHESIS OF RESULTS: We prioritized comparing HoLEP with transurethral resection of the prostate (TURP) at short-term follow-up (up to 12 months), because TURP is the long-standing reference standard and the predominant comparator in randomized surgical trials. Findings for the four remaining comparisons (laser ablation, alternative energy source enucleation, other minimally invasive therapies, and simple prostatectomy), for long-term follow-up, and for all remaining outcomes are reported in full in the review. Compared to TURP, at short-term follow-up: Critical outcomes - HoLEP may result in little to no difference in short-term urologic symptom scores measured using the IPSS (range 0 to 35; lower values reflect fewer symptoms) (MD -0.67, 95% CI -1.20 to -0.14; I² = 93%; 14 studies, 1666 participants, low-certainty evidence). - HoLEP may result in little to no difference in short-term quality of life (range 0 to 6; lower values reflect better quality of life) (MD -0.04, 95% CI -0.23 to 0.15; I² = 73%; 6 studies, 876 participants, low-certainty evidence). - HoLEP may result in little to no difference in short-term major adverse events (RR 0.75, 95% CI 0.35 to 1.58; I² = 0%; 10 studies, 1147 participants, low-certainty evidence). Important outcomes - HoLEP likely results in little to no difference in re-treatment (RR 0.45, 95% CI 0.14 to 1.50; I² = 0%; 8 studies, 813 participants, moderate-certainty evidence). - HoLEP likely results in little to no difference in erectile function (MD -0.03, 95% CI -0.47 to 0.42; I² = 0%; 3 studies, 518 participants, moderate-certainty evidence). - Ejaculatory function: we did not find any data for this outcome. - HoLEP likely reduces the need for blood transfusion (RR 0.19, 95% CI 0.09 to 0.42; I² = 0%; 15 studies, 1755 participants, moderate-certainty evidence). AUTHORS' CONCLUSIONS: Compared with TURP, HoLEP may achieve similar relief of urologic symptoms, similar quality of life, and similar rates of major adverse events in the first 12 months after surgery, and probably similar re-treatment rates and erectile function. HoLEP likely reduces the need for blood transfusion; this is the only advantage of HoLEP that the randomized evidence, as summarized here, supports as clinically important. There was insufficient evidence to assess outcomes in the subset of individuals with larger prostates or on anticoagulation. Future research should prioritize long-term trials reporting sexual function and urinary incontinence outcomes, recruit men with very large prostates (≥ 150 cc) or on anticoagulation therapy, and evaluate cost-effectiveness and training requirements. FUNDING: No external funding was received for this review. REGISTRATION: The protocol for this review was published in the Cochrane Database 2019 (https://doi.org/10.1002/14651858.CD013291).

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