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Nonsteroidal anti-inflammatory drugs (NSAIDs) for acute renal colic

2025· review· en· W4408459762 on OpenAlexaff
Kourosh Afshar, Jagdeep Gill, Hanan Mostafa, Maryam Noparast

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2025
Typereview
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsNonsteroidalMedicineAnti-inflammatoryPharmacologyRenal colicIntensive care medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Urolithiasis (urinary stones) is a common disease with an increasing incidence globally. It often presents with renal colic, which is characterised by acute and intense abdominal pain. The first step in the management of renal colic is pain control. Various medications, including narcotics, nonsteroidal anti-inflammatory drugs (NSAIDs), antispasmodics, and others, have been used for this condition. NSAIDs are amongst the most commonly used drugs for renal colic. They act by reducing inflammation and lowering the pressure inside the urinary collecting system. This review updates a previous Cochrane Systematic Review (Afshar 2015), focusing exclusively on NSAIDs. OBJECTIVES: To assess the benefits and harms of different nonsteroidal anti-inflammatory drugs (NSAIDs) for the management of pain in adults with acute renal colic. SEARCH METHODS: We performed a comprehensive search of the Cochrane Library, MEDLINE, Embase, Google Scholar, trial registries, and conference proceedings up to 25 August 2023. We applied no restrictions on publication language or status. SELECTION CRITERIA: We included randomised (or quasi-randomised) controlled trials (RCTs) assessing the effects of NSAIDs in the management of renal colic adult patients (i.e. study participants over 16 years of age). We included studies that compared NSAIDs versus placebo, one NSAID versus another, or different doses or routes of administration of the same NSAID. DATA COLLECTION AND ANALYSIS: Two review authors independently classified studies and abstracted data from the included studies. Primary outcomes included pain up to one hour after treatment as measured by a validated patient-reported tool, the need for rescue medication up to six hours after treatment, and serious adverse events up to one week after treatment. Secondary outcomes included pain recurrence, significant pain relief, and minor adverse events. We performed meta-analysis using the random-effects model. We rated the certainty of evidence according to the GRADE approach. MAIN RESULTS: = 42%; 2 studies, 134 participants; moderate-certainty evidence). Intravenous NSAIDs may reduce the need for rescue medication within 30 minutes compared to rectal NSAIDs (RR 0.35, 95% CI 0.14 to 0.88; 1 study, 116 participants; low-certainty evidence). The evidence is uncertain regarding the potential harms of NSAIDs. Risk of bias We judged the risk of bias in the studies to be moderate to high. This was due to a high proportion of unknown risk judgments for concealment bias and a high risk of selective reporting bias. AUTHORS' CONCLUSIONS: NSAIDs may reduce pain in adult patients with renal colic compared to placebo. Comparing one NSAID against another, IV ketorolac may be less effective than IV ibuprofen, and pirprofen may result in less need for rescue medication than indomethacin. The intravenous route of administration is probably similar to the intramuscular route but may be better than the rectal route. The evidence is uncertain regarding the potential harms of NSAIDs. We were not able to perform subgroup analysis based on our predefined criteria because there were no eligible 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)0.007
metaresearch head score (Gemma)0.027
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: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.004
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.063
GPT teacher head0.401
Teacher spread0.338 · 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
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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