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Record W4406011554 · doi:10.1186/s12894-024-01655-w

Percutaneous nephroscopy versus flexible ureteroscopy in the treatment of calyceal diverticulum calculi: a meta-analysis

2025· review· en· W4406011554 on OpenAlexaboutno aff
Conglei Hu, Rui Ma, Yongxiang Shao, Zhou Liang, Meng Cheng, Liping Yao, Fei Liu

Bibliographic record

VenueBMC Urology · 2025
Typereview
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMedicineMeta-analysisCochrane LibraryUreteroscopyJadad scaleSurgeryPercutaneousSubgroup analysisInternal medicineUreter

Abstract

fetched live from OpenAlex

BACKGROUND: There is still controversy about the best minimally invasive surgical method for the treatment of calyceal diverticulum calculi. We conducted meta-analysis to evaluate the effectiveness and safety of PCNL and FURL in the treatment of calyceal diverticulum calculi. METHODS: We searched Pubmed, Cochrane Library, Web of Science, Embase, Clinical trial platform, CNKI, VIP until April 2024. We utilized the Newcastle-Ottawa Scale (NOS, 0 to 9 stars) to assess the quality of the included literature. RESULTS: Totally 15 high-quality studies with 755 patients were included in the meta-analysis. Meta-analysis showed that FURL group was better than PCNL group in blood loss [SMD = 1.713, 95%CI:(0.858, 2.568), Z = 3.928, P = 0.000] and hospital stay [SMD = 2.611, 95%CI: (1.726, 3.496), Z = 5.784, P = 0.000], there was no significant difference in operating time [SMD = 0.079, 95%CI:(-0.43, 0.589), Z = 0.306, P = 0.760], complication rate [OR = 1.793,95%CI: (0.952,2.602), Z = 1.586, P = 0.113], stone-free rate [OR = 1.339, 95%CI: (0.576, 3.112), Z = 0.678, P = 0.497] and symptom-free rate [OR = 3.826,95%CI: (0.561,10.238), Z = 0.966, P = 0.334] as well. CONCLUSION: Whether FURL is indeed superior to PCNL in safety, whether FURL's efficacy is really close to PCNL, and whether FURL can surpass PCNL as the first choice for the treatment of renal diverticulum stones in the future need to be further verified by multi-center, large-sample and high-quality studies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.019
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.056
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.177
GPT teacher head0.423
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations2
Published2025
Admission routes1
Has abstractyes

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