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Record W4360810261 · doi:10.4103/ijp.ijp_673_21

Efficacy and safety of levamisole in childhood nephrotic syndrome

2023· review· en· W4360810261 on OpenAlexaff
Girish Chandra Bhatt, Bhupeshwari Patel, Rashmi Ranjan Das, Shikha Malik, Martin Bitzan, Nihar Ranjan Mishra

Bibliographic record

VenueIndian Journal of Pharmacology · 2023
Typereview
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsLevamisoleMedicineMeta-analysisPlaceboRelative riskConfidence intervalCochrane LibraryNephrotic syndromeInternal medicineRandomized controlled trialPediatricsAlternative medicinePathology

Abstract

fetched live from OpenAlex

Present evidence regarding the efficacy and safety of levamisole in childhood nephrotic syndrome (NS), particularly the steroid-sensitive NS (SSNS), is limited. We searched relevant databases such as PubMed/MEDLINE, Embase, Google Scholar, and Cochrane CENTRAL till June 30, 2020. We included 12 studies for evidence synthesis (5 were clinical trials that included 326 children). The proportion of children without relapses at 6–12 months was higher in the levamisole group as compared to steroids (relative risk [RR]: 5.9 [95% Confidence interval (CI): 0.13–264.8], I 2 = 85%). Levamisole as compared to the control increased the proportion of children without relapses at 6–12 months (RR: 3.55 [95% CI: 2.19–5.75], I 2 = 0%). The GRADE evidence was of “very-low certainty” except for the comparison of levamisole with control, the latter being of “moderate certainty.” To conclude, levamisole given to children with SSNS is beneficial in preventing relapses and achieving remission as compared to placebo or low-dose steroids. Good-quality trials are needed to provide a robust evidence in this regard. PROSPERO Registration number: CRD42018086247.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.888
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.362
Teacher spread0.332 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations6
Published2023
Admission routes1
Has abstractyes

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