Disparities in Outcomes for Blacks versus Whites Undergoing Total Hip Arthroplasty: A Systematic Literature Review
Bibliographic record
Abstract
OBJECTIVE: Total hip replacement (THA) surgery is a successful procedure, yet blacks in the United States undergo THA less often and reflect poorer outcomes than whites. The purpose of this study is to systematically review the literature on health-related quality of life after THA, comparing blacks and whites. METHODS: A librarian-assisted search was performed in Medline through PubMed, Embase, and Cochrane Library on February 27, 2017. Original cohort studies examining pain, function, and satisfaction in blacks and whites 1 year after elective THA were included. Using the Patient/Population-Intervention-Comparison/Comparator-Outcome (PICO) process format, our population of interest was US black adults, our intervention was elective THA, our comparator was white adults, and our outcomes of interest were pain, function, and satisfaction after elective THA. The protocol was registered under the PROSPERO international register, and the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines were followed. RESULTS: Of the articles, 4739 were screened by title, 180 by abstract, 25 by full text, and 4 remained for analysis. The studies represented 1588 THA patients, of whom 240 (15%) were black. All studies noted more pain and worse function for blacks; although differences were statistically significant, they were not clinically significant. One study sought and identified less satisfaction for blacks after THA, and 1 study showed worse fear and anxiety scores in blacks. CONCLUSION: When measured, there are small differences in THA outcomes between blacks and whites, but most studies do not analyze/collect race. Future studies should address the effect of race and socioeconomic factors on healthcare disparities.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".