Author reply to “Regarding ‘Operative Versus Nonoperative Treatment of Femoroacetabular Impingement Syndrome: A Meta‐analysis of Short‐Term Outcomes’”
Bibliographic record
Abstract
We thank Kim et al. for their comments regarding our article.1Dwyer T. Whelan D. Shah P.S. Ajrawat P. Hoit G. Chahal J. Operative versus nonoperative treatment of femoroacetabular impingement syndrome: A meta-analysis of short-term outcomes.Arthroscopy. 2020; 36: 263-273Abstract Full Text Full Text PDF PubMed Scopus (34) Google Scholar We sought to perform a meta-analysis of treatment outcomes in patients with femoroacetabular impingement syndrome (FAIS) comparing operative and nonoperative treatment. When possible, we focused on 12-month outcomes given that this is the time frame of important clinical decision making such as evaluation of surgical success and return to sport.2Ishoi L. Thorborg K. Kraemer O. Holmich P. Return to sport and performance after hip arthroscopy for femoroacetabular impingement in 18- to 30-year-old athletes: A cross-sectional cohort study of 189 athletes.Am J Sports Med. 2018; 46: 2578-2587Crossref PubMed Scopus (64) Google Scholar,3Sardana V. Philippon M.J. de Sa D. et al.Revision hip arthroscopy indications and outcomes: A systematic review.Arthroscopy. 2015; 31: 2047-2055Abstract Full Text Full Text PDF PubMed Scopus (120) Google Scholar However, the included study by Palmer et al.4Palmer A.J.R. Ayyar Gupta V. Fernquest S. et al.Arthroscopic hip surgery compared with physiotherapy and activity modification for the treatment of symptomatic femoroacetabular impingement: Multicentre randomised controlled trial.BMJ. 2019; 364: l185Crossref PubMed Scopus (150) Google Scholar only reported outcomes after 8 months of randomization. These results were included in our meta-analysis after a post-protocol decision, and we do agree that it induces a degree of clinical heterogeneity in our analyses. Although we also agree a 6-month pooled analysis would have been a complementary adjunct to our article, we would argue that 6-month outcomes do not provide significant value in clinical decision making postoperatively.5Shin J.J. de Sa D.L. Burnham J.M. Mauro C.S. Refractory pain following hip arthroscopy: Evaluation and management.J Hip Preserv Surg. 2018; 5: 3-14Crossref PubMed Google Scholar Kim et al. also questioned our pooling of adjusted and unadjusted mean differences in International Hip Outcome Tool 33 (iHOT-33) scores. We agree with the authors that under ideal circumstances, we would not have combined unadjusted and adjusted data. However, Palmer et al.4Palmer A.J.R. Ayyar Gupta V. Fernquest S. et al.Arthroscopic hip surgery compared with physiotherapy and activity modification for the treatment of symptomatic femoroacetabular impingement: Multicentre randomised controlled trial.BMJ. 2019; 364: l185Crossref PubMed Scopus (150) Google Scholar reported only adjusted mean differences between treatment groups, whereas Mansell et al.6Mansell N.S. Rhon D.I. Marchant B.G. Slevin J.M. Meyer J.L. Two-year outcomes after arthroscopic surgery compared to physical therapy for femoracetabular impingement: A protocol for a randomized clinical trial.BMC Musculoskelet Disord. 2016; 17: 60Crossref PubMed Scopus (19) Google Scholar reported only unadjusted mean differences. Griffin et al.7Griffin D.R. Dickenson E.J. Wall P.D.H. et al.Hip arthroscopy versus best conservative care for the treatment of femoroacetabular impingement syndrome (UK FASHIoN): A multicentre randomised controlled trial.Lancet. 2018; 391: 2225-2235Abstract Full Text Full Text PDF PubMed Scopus (300) Google Scholar reported confidence intervals only for their adjusted mean differences and gave an unadjusted point estimate, which was higher than their adjusted mean difference. If we had used the unadjusted mean difference in our analysis, the pooled treatment effect would have more substantially favored surgery over nonoperative care, not the opposite, as Kim et al. suggest. If estimates and confidence intervals had been available for all studies, we would have included only unadjusted differences. Kim et al. also critique our use of a fixed-effects model for pooling results. We do not share the same view that a random-effects model is always more appropriate, and in fact, their stated consensus of avoiding fixed effects in medical research is not borne out in the literature.8Wang X. Liu S. Zhao X. Fang E. Zhao X. The value of C-reactive protein as an independent prognostic indicator for disease-specific survival in patients with soft tissue sarcoma: A meta-analysis.PLoS One. 2019; 14e0219215PubMed Google Scholar, 9Wei F. Does an extreme age (>/=80 years) affect outcomes in patients after liver cancer surgery? A meta-analysis.ANZ J Surg. 2019; 89: 25-31Crossref PubMed Scopus (4) Google Scholar, 10Becker M. Buhn S. Breuing J. et al.The role of icodextrin in peritoneal dialysis: Protocol for a systematic review and meta-analysis.Syst Rev. 2019; 8: 35Crossref PubMed Scopus (5) Google Scholar, 11Becker C. Lecheler L. Hochstrasser S. et al.Association of communication interventions to discuss code status with patient decisions for do-not-resuscitate orders: A systematic review and meta-analysis.JAMA Netw Open. 2019; 2e195033Crossref PubMed Scopus (24) Google Scholar, 12Zhang X. Wang C. Dou Q. Zhang W. Yang Y. Xie X. Sarcopenia as a predictor of all-cause mortality among older nursing home residents: A systematic review and meta-analysis.BMJ Open. 2018; 8e021252Crossref PubMed Scopus (57) Google Scholar, 13Lynch T.S. O'Connor M. Minkara A.A. Westermann R.W. Rosneck J.T. Biomarkers for femoroacetabular impingement and hip osteoarthritis: A systematic review and meta-analysis.Am J Sports Med. 2019; 47: 2242-2250Crossref PubMed Scopus (5) Google Scholar Previous statistical guides have advocated for the use of fixed-effects models provided that the I2 value indicates low heterogeneity across studies, as well as when the relative number of subjects included in the meta-analysis is small.14Higgins J.P. Thompson S.G. Deeks J.J. Altman D.G. Measuring inconsistency in meta-analyses.BMJ. 2003; 327: 557-560Crossref PubMed Scopus (40126) Google Scholar,15Hedges L.V. Olkin I. Statistical methods for meta-analysis. Academic Press, London1985Google Scholar Additionally, it is well documented that the use of random-effects models will disproportionately give higher weight to studies with smaller sample sizes,16Borenstein M. Hedges L.V. Higgins J.P. Rothstein H.R. A basic introduction to fixed-effect and random-effects models for meta-analysis.Res Synth Methods. 2010; 1: 97-111Crossref PubMed Scopus (0) Google Scholar which in our study would be the least generalizable trial with the most methodologic concerns.1Dwyer T. Whelan D. Shah P.S. Ajrawat P. Hoit G. Chahal J. Operative versus nonoperative treatment of femoroacetabular impingement syndrome: A meta-analysis of short-term outcomes.Arthroscopy. 2020; 36: 263-273Abstract Full Text Full Text PDF PubMed Scopus (34) Google Scholar,6Mansell N.S. Rhon D.I. Marchant B.G. Slevin J.M. Meyer J.L. Two-year outcomes after arthroscopic surgery compared to physical therapy for femoracetabular impingement: A protocol for a randomized clinical trial.BMC Musculoskelet Disord. 2016; 17: 60Crossref PubMed Scopus (19) Google Scholar Ultimately, our meta-analysis found statistically significant improvement in patient-reported outcomes among surgically treated FAIS patients, as shown by their pooled iHOT-33 scores. The iHOT-33 is a robustly developed, valid, reliable, and responsive patient-reported outcome measure for health-related quality of life specifically for patients with FAIS.17Mohtadi N.G. Griffin D.R. Pedersen M.E. et al.The development and validation of a self-administered quality-of-life outcome measure for young, active patients with symptomatic hip disease: The International Hip Outcome Tool (iHOT-33).Arthroscopy. 2012; 28 (quiz 606-610.e1): 595-605Abstract Full Text Full Text PDF PubMed Scopus (280) Google Scholar Given the breadth of the iHOT-33 and its consistent performance with external psychometric evaluation,18Kemp J.L. Collins N.J. Roos E.M. Crossley K.M. Psychometric properties of patient-reported outcome measures for hip arthroscopic surgery.Am J Sports Med. 2013; 41: 2065-2073Crossref PubMed Scopus (300) Google Scholar we do believe that these results are generalizable to patient-reported hip-related outcomes. However, these results are inclusive of only 3 studies with relatively small sample sizes and do not include objective clinical measures such as strength and stability—a limitation well stated within our article. Clarity as to the true treatment differences, especially with long-term outcomes, will be derived only from future, well-powered randomized controlled trials. Download .pdf (2.26 MB) Help with pdf files ICMJE author disclosure forms
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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 | 0.030 | 0.246 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.028 | 0.025 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".