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Record W6943952791 · doi:10.17605/osf.io/ua8re

Is Hidradenitis Suppurativa associated with a lower socioeconomic status compared to the general population: A systematic review and meta-analysis.

2020· other· en· W6943952791 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2020
Typeother
Languageen
FieldMedicine
TopicHidradenitis Suppurativa and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsHidradenitis suppurativaSocioeconomic statusPopulationMEDLINEScopusSystematic review

Abstract

fetched live from OpenAlex

1. * Review title. Is Hidradenitis Suppurativa associated with a lower socioeconomic status compared to the general population: A systematic review and meta-analysis. 2. * Anticipated or actual start date. 05/02/2020 3. * Anticipated completion date. 07/04/2020 4. * Stage of review at time of this submission. Review stage Started Completed Preliminary searches Completed Piloting of the study selection process Completed Formal screening of search results against eligibility criteria Completed 5. * Named contact. Adrian Bailey 6. * Named contact email. abail082@uottawa.ca 7. Named contact address 4512 Appleton Side Road 8. Named contact phone number. 6138585029 9. * Organisational affiliation of the review. University of Ottawa 10. * Funding sources/sponsors. None 11. * Conflicts of interest. None 12. * Review question. Is Hidradenitis Suppurativa associated with a lower socioeconomic status compared to the general population? P = Adult patients with Hidradenitis Suppurativa I = N/A C = The general adult population (or a reference population that is representative of the general population) O = Socioeconomic status 13. * Searches. PubMed and Scopus (April 3rd 2020). No date restrictions. English articles only. 14. * Condition or domain being studied. Low socioeconomic status (SES) has been shown to be associated with hidradenitis suppurativa (HS); however, the literature lacks an assessment of this association across a variety of populations and recommendations for future research. Here, we plan toi systematically review and meta-analyse the current evidence on HS and SES. 15. * Participants/population. Inclusion: -Adult patients (16 years or older) with Hidradenitis Suppurativa Exclusion: -Paediatric patients -Animal studies 16. * Intervention(s), exposure(s). -Not applicable. 17. * Comparator(s)/control. -General population (ex. other dermatology patients) 18. * Types of study to be included. Eligible study designs included population-based retrospective cohort, cross sectional, and case-control studies. Grey literature and other study designs were excluded. An Odds ratio will be used to measure the association between low socioeconomic status and patients with Hidradenitis Suppurativa compared to a reference population (a representative sample of the general population). Studies that do not provide this data, data necessary to calculate an Odds ratio, or their corresponding author was not able to provide this data will be excluded. 19. * Main outcome(s). -Socioeconomic status. Any definition and stratification of SES will be accepted, such as income, postal code, occupation, insurance status, and census data. * Measures of effect -An Odds ratio will be used to measure the association between low socioeconomic status and patients with Hidradenitis Suppurativa compared to a reference population. 20. * Data extraction (selection and coding). -Study Characteristics = setting, date range of data collection, population size, socioeconomic status measure used, if an adjusted model was used, and what factors were accounted for if an adjusted model was used. -Odds ratio or raw data that can be used to calculate the Odds ratio of the association of low socioeconomic status and patients with Hidradenitis Suppurativa, compared to a reference population. 21. * Risk of bias (quality) assessment. The risk of bias will be determined using the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. 22. * Strategy for data synthesis. The inverse variance model with the fixed effects model, to account for variations in study size, will be used to estimate the Odds ratio and confidence intervals for each study. Heterogeneity across studies will be assessed using the I² statistic. 23. * Analysis of subgroups or subsets. None planned 24. Language. English 25. * Country. Canada 26. Dissemination plans. Publication to a major journal. 27. Current review status. Ongoing.

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)0.010
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.017
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.002
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 head0.059
GPT teacher head0.362
Teacher spread0.304 · 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 designMeta-analysis
Domainnot available
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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