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Record W4406810889 · doi:10.1101/2025.01.22.25320716

Risk factors for renal stone development in adults with primary hyperparathyroidism: A protocol for a systematic review and meta-analysis

2025· review· en· W4406810889 on OpenAlexaff
Mohammad Jay, Sorina Andrei, Peter Hoang, Hussein Samhat, Roland M. Jones, Rui Fu, Lorraine L. Lipscombe, Antoine Eskander

Bibliographic record

VenuemedRxiv · 2025
Typereview
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsUniversity of CalgaryMcGill UniversityPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsPrimary hyperparathyroidismMeta-analysisProtocol (science)MedicineRenal stoneInternal medicinePathologyUrinary systemAlternative medicine

Abstract

fetched live from OpenAlex

Abstract Background Primary hyperparathyroidism (PHPT) is characterized by overactive parathyroid glands. Renal stones (RS) are a common complication of PHPT and is associated with increased morbidity. However, the risk factors for RS in PHPT are not well-established and the latest international PHPT guideline highlights the need for further research into this area. Objective We aim to summarize and meta-analyze the existing evidence on prespecified risk factors associated with RS in adults with PHPT. Methods and Analysis We will search MEDLINE, EMBASE, and Cochrane Central from inception. Two independent reviewers will screen studies and include prospective/retrospective cohort, case-control, and cross-sectional designs in adults (≥18 years) with PHPT. Randomized trials, conference abstracts, case reports, and commentaries will be excluded. Two reviewers will independently extract data on population characteristics, risk factors, RS outcomes, and assess risk of bias using the Quality in Prognostic Studies tool. A random-effects model will be used to pool odds ratios. We will separately pool adjusted (primary analyses) and unadjusted odds ratios (secondary analyses) with their corresponding 95% confidence intervals. Certainty will be evaluated with the Grading of Recommendations Assessment, Development, and Evaluation framework. Heterogeneity will be assessed using the I² statistic and publication bias will be evaluated with funnel plots. Discussion Early identification of patients with PHPT at high risk for RS can facilitate the implementation of preventive strategies and reduce morbidity. Furthermore, recognizing these risk factors can assist clinicians in prioritizing treatment for those at higher risk, ultimately improving patient outcomes. Protocol registration The protocol was registered in PROSPERO on November 14, 2024 (registration ID: CRD42024608180). Funding No source of financial funding was used.

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)0.054
metaresearch head score (Gemma)0.096
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.054
Threshold uncertainty score0.286

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0540.096
Meta-epidemiology (narrow)0.0050.004
Meta-epidemiology (broad)0.0230.034
Bibliometrics0.0100.010
Science and technology studies0.0020.002
Scholarly communication0.0060.005
Open science0.0050.004
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0360.003

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 head0.067
GPT teacher head0.373
Teacher spread0.306 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations0
Published2025
Admission routes1
Has abstractyes

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