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Record W4406924001 · doi:10.1016/j.jdrv.2025.01.010

Renal safety of biologic and systemic therapies for psoriasis: A systematic review

2025· review· en· W4406924001 on OpenAlexaff
Ryan S.Q. Geng, Siddhartha Sood, Jihad Waked, Nabil Merchant, Jensen Yeung, Asfandyar Mufti

Bibliographic record

VenueJAAD reviews. · 2025
Typereview
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsProbity Medical ResearchHealth Sciences CentreSunnybrook Health Science CentreWestern UniversityWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsPsoriasisMedicineSystemic therapyIntensive care medicineDermatologyInternal medicineCancer

Abstract

fetched live from OpenAlex

Psoriasis is a chronic inflammatory disease mainly driven by T-helper-17 dysregulation. Despite increasing use of biologics and nonbiologic systemic therapies for moderate-to-severe psoriasis, data remain limited regarding the renal safety of these therapies.1 This systematic review investigates evidence regarding the impact of biologics and conventional systemic therapies on estimated glomerular filtration rate (eGFR).

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)0.006
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 score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.156
GPT teacher head0.458
Teacher spread0.301 · 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

Citations0
Published2025
Admission routes1
Has abstractno

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