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Record W4406777783 · doi:10.30574/wjarr.2025.25.1.0166

Head-to-head comparison of Rezum vs Urolift for patient with benign prostatic hyperplasia: A systematic review

2025· review· en· W4406777783 on OpenAlexaboutno aff
Muhammad Usman, Asyam Syafiq Hasbullah, Ulinnuha Khirza Kafalah, Raih Viguruh Hermarwan

Bibliographic record

VenueWorld Journal of Advanced Research and Reviews · 2025
Typereview
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsnot available
Fundersnot available
KeywordsHyperplasiaHead (geology)MedicineUrologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Introduction: Minimally invasive surgical therapies (MISTs) have been developed to treat Benign Prostatic hyperplasia (BPH) while minimizing adverse surgical effect. Most recent developed MIST, Rezum and Urolift, showed effective efficacy in improving, but head-to-head comparison still lacking. This study aims to compare the efficacy and safety of Urolift and Rezum in managing BPH-related LUTS. Methods:A systematic search was conducted in Cochrane, PubMed, EMBASE, SCOPUS and EBSCOhost, identifying observational studies comparing rezum and urolift in BPH patient. Data extraction included demographics, intervention protocols, follow-up duration, and outcomes International Prostate Symptom Score (IPSS) score, IPSS-QoL, sexual function, and reintervention rate. The quality of studies was assessed using the Newcastle-Ottawa Scale. Results:Two cohort with a total of 101 patients with BPH were included. At 12 months, Rezum tends to be superior in improving symptoms severity, while at 2 months of follow-up, Urolift outperformed Rezum. Both intervention preserved patient’s sexual function and does not differ significantly. Reintervention rate significantly higher in Urolift compared to Rezum group. Conclusion: Rezum offers a more effective alternative to Urolift for managing BPH in long term setting, with lower reintervention rate and preserved sexual function. In early setting, Urolift showed higher efficacy and rapid improvement compared to Rezum.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.125
GPT teacher head0.507
Teacher spread0.383 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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