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Record W3134586758 · doi:10.1177/1203475421995130

Pharmacologic Treatment of Idiopathic Chilblains (Pernio): A Systematic Review

2021· review· en· W3134586758 on OpenAlexaff
M.E. Pratt, Farhan Mahmood, Mark G. Kirchhof

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2021
Typereview
Languageen
FieldMedicine
TopicDermatological and COVID-19 studies
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicinePentoxifyllineNifedipineMinoxidilPlaceboDermatologySuperficial thrombophlebitisPopulationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Idiopathic chilblains is a cold-induced inflammatory condition that causes significant morbidity. When preventative measures alone are inadequate, oral nifedipine is generally recommended as first-line pharmacologic therapy. Given the natural course of this spontaneously remitting/relapsing condition, controls are needed to critically appraise studies and determine the value of treatments. We report a systematic review of placebo-controlled or comparative therapeutic trials for the treatment of idiopathic chilblains. Our search of PubMed, Embase, and Cochrane databases, identified 11 studies that met our inclusion criteria for a combined study population n = 576. Therapies included nifedipine, pentoxifylline, tadalafil, topical glyceryl trinitrate (GTN), topical minoxidil, diltiazem, corticosteroids, and vitamin D. There was moderate evidence to support the use of nifedipine and pentoxifylline in the treatment of severe or refractory cases of idiopathic chilblains, while other therapies had inadequate evidence or nonsignificant results compared to placebo.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.123
GPT teacher head0.395
Teacher spread0.272 · 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

Citations24
Published2021
Admission routes1
Has abstractyes

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