Predicting the Risk of Subsequent Hip Surgery Before Primary Hip Arthroscopy for Femoroacetabular Impingement Syndrome: A Machine Learning Analysis of Preoperative Risk Factors in Hip Preservation.

التفاصيل البيبلوغرافية
العنوان:	Predicting the Risk of Subsequent Hip Surgery Before Primary Hip Arthroscopy for Femoroacetabular Impingement Syndrome: A Machine Learning Analysis of Preoperative Risk Factors in Hip Preservation.
المؤلفون:	Haeberle HS; Orthopaedic Machine Learning Laboratory, Cleveland Clinic, Cleveland, Ohio, USA.; Sports Medicine & Hip Preservation Service, Hospital for Special Surgery, New York, New York, USA., Ramkumar PN; Orthopaedic Machine Learning Laboratory, Cleveland Clinic, Cleveland, Ohio, USA.; Sports Medicine & Hip Preservation Service, Hospital for Special Surgery, New York, New York, USA.; Department of Orthopaedics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA., Karnuta JM; Orthopaedic Machine Learning Laboratory, Cleveland Clinic, Cleveland, Ohio, USA., Sullivan S; Sports Medicine & Hip Preservation Service, Hospital for Special Surgery, New York, New York, USA., Sink EL; Sports Medicine & Hip Preservation Service, Hospital for Special Surgery, New York, New York, USA., Kelly BT; Sports Medicine & Hip Preservation Service, Hospital for Special Surgery, New York, New York, USA., Ranawat AS; Sports Medicine & Hip Preservation Service, Hospital for Special Surgery, New York, New York, USA., Nwachukwu BU; Sports Medicine & Hip Preservation Service, Hospital for Special Surgery, New York, New York, USA.
المصدر:	The American journal of sports medicine [Am J Sports Med] 2021 Aug; Vol. 49 (10), pp. 2668-2676. Date of Electronic Publication: 2021 Jul 07.
نوع المنشور:	Journal Article
اللغة:	English
بيانات الدورية:	Publisher: Sage Publications Country of Publication: United States NLM ID: 7609541 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1552-3365 (Electronic) Linking ISSN: 03635465 NLM ISO Abbreviation: Am J Sports Med Subsets: MEDLINE
أسماء مطبوعة:	Publication: 2004- : Thousand Oaks, CA : Sage Publications Original Publication: Baltimore, Williams & Wilkins.
مواضيع طبية MeSH:	Femoracetabular Impingement/diagnostic imaging , Femoracetabular Impingement/surgery, Activities of Daily Living ; Arthroscopy ; Cohort Studies ; Follow-Up Studies ; Hip Joint/diagnostic imaging ; Hip Joint/surgery ; Humans ; Machine Learning ; Retrospective Studies ; Risk Factors ; Treatment Outcome
مستخلص:	Background: The number of patients requiring reoperation has increased as the volume of hip arthroscopy for femoroacetabular impingement syndrome (FAIS) has increased. The factors most important in determining patients who are likely to require reoperation remain elusive. Purpose: To leverage machine learning to better characterize the complex relationship across various preoperative factors (patient characteristics, radiographic parameters, patient-reported outcome measures [PROMs]) for patients undergoing primary hip arthroscopy for FAIS to determine which features predict the need for future ipsilateral hip reoperation, namely, revision hip arthroscopy, total hip arthroplasty (THA), hip resurfacing arthroplasty (HRA), or periacetabular osteotomy (PAO). Study Design: Cohort study; Level of evidence, 3. Methods: A cohort of 3147 patients undergoing 3748 primary hip arthroscopy procedures were included from an institutional hip preservation registry. Preoperative computed tomography of the hip was obtained for each patient, from which the following parameters were calculated: the alpha angle; the coronal center-edge angle; the neck-shaft angle; the acetabular version angle at 1, 2, and 3 o'clock; and the femoral version angle. Preoperative PROMs included the modified Harris Hip Score (mHHS), the Hip Outcome Score (HOS)-Activities of Daily Living subscale (HOS-ADL) and the Sport Specific subscale, and the international Hip Outcome Tool (iHOT-33). Random forest models were created for revision hip arthroscopy, the THA, the HRA, and the PAO. Area under the curve (AUC) for the receiver operating characteristic curve and accuracy were calculated to evaluate each model. Results: A total of 171 patients (4.6%) underwent subsequent hip surgery after primary hip arthroscopy for FAIS. The AUC and accuracy, respectively, were 0.77 (fair) and 76% for revision hip arthroscopy (mean, 26.4-month follow-up); 0.80 (good) and 81% for THA (mean, 32.5-month follow-up); 0.62 (poor) and 69% for HRA (mean, 45.4-month follow-up); and 0.76 (fair) and 74% for PAO (mean, 30.4-month follow-up). The most important factors in predicting reoperation after primary hip arthroscopy were higher body mass index (BMI) and lower preoperative HOS-ADL for revision hip arthroscopy, greater age and lower preoperative iHOT-33 for THA, increased BMI for HRA, and larger neck-shaft angle and lower preoperative mHHS for PAO. Conclusion: Despite the low failure rate of hip arthroscopy for FAIS, our study demonstrated that machine learning has the capability to identify key preoperative risk factors that may predict subsequent ipsilateral hip surgery before the index hip arthroscopy. Knowledge of these demographic, radiographic, and patient-reported outcome data may aid in preoperative counseling and expectation management to better optimize hip preservation.
فهرسة مساهمة:	Keywords: femoroacetabular impingement; hip arthroscopy; machine learning; patient-reported outcome measures; radiographic indices
تواريخ الأحداث:	Date Created: 20210707 Date Completed: 20210809 Latest Revision: 20210809
رمز التحديث:	20221213
DOI:	10.1177/03635465211024964
PMID:	34232753
قاعدة البيانات:	MEDLINE

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تدمد:	1552-3365
DOI:	10.1177/03635465211024964