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Yuan L, Liu Y, Zeng Y, Chen Z, Li W. Impact of preoperative clinical state on 2-year clinical outcomes following degenerative lumbar scoliosis surgery. J Orthop Res 2024; 42:1335-1342. [PMID: 38151818 DOI: 10.1002/jor.25780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 12/10/2023] [Accepted: 12/18/2023] [Indexed: 12/29/2023]
Abstract
To assess the preoperative clinical state's impact on clinical outcomes after surgery for degenerative lumbar scoliosis (DLS) based on the minimal clinically important difference (MCID). Preoperative and follow-up (FU) scores in each Scoliosis Research Society-22 (SRS-22) domain were compared with age- and sex-matched normative references. At baseline, patients were classified by differences from normative values in four groups: Worst, Severe, Poor, and Moderate. At 2 years postoperative FU, patients were divided into four groups (Worst Severe Poor Asymptomatic) based on the difference in MCID between postoperative and normal values. The changes in MCID were considered as the criterion for surgical efficacy. In addition, we calculated the classification of preoperative and FU clinical symptom severity in each domain in same patient. The distinction among curve types was also performed based on the SRS-Schwab classification. A total of 123 patients were included. During FU, patients with more severe preoperative clinical symptoms were more likely to achieve clinical changes (>1 MCID, p < 0.05), but the rate of reaching "asymptomatic" was lower (p < 0.05). Kendall's tau-b correlation analysis found that preoperative clinical severity was correlated with clinical changes category in Activity (Tau-b = 0.252; p = 0.002), Pain (Tau-b = 0.230; p = 0.005), Appearance (Tau-b = 0.307; p < 0.001), and Mental (Tau-b = 0.199; p = 0.016), and it also was correlated with FU clinical severity in Activity (Tau-b = 0.173; p = 0.023), Pain (Tau-b = 0.280; p < 0.001), and Mental (Tau-b = 0.349; p < 0.001). There was a correlation between preoperative clinical severity and FU SRS-22 score outcomes. Patients with severe preoperative clinical symptoms can experience better treatment outcomes during FU, but it is also more difficult to recover to the normal reference.
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Affiliation(s)
- Lei Yuan
- Department of Orthopedics, Peking University Third Hospital, Beijing, China
- Beijing Key Laboratory of Spinal Disease Research, Peking University Third Hospital, Beijing, China
- Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China
| | - Yinhao Liu
- Department of Orthopedics, Peking University Third Hospital, Beijing, China
- Beijing Key Laboratory of Spinal Disease Research, Peking University Third Hospital, Beijing, China
- Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China
- Peking University Health Science Center, Beijing, China
| | - Yan Zeng
- Department of Orthopedics, Peking University Third Hospital, Beijing, China
- Beijing Key Laboratory of Spinal Disease Research, Peking University Third Hospital, Beijing, China
- Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China
| | - Zhongqiang Chen
- Department of Orthopedics, Peking University Third Hospital, Beijing, China
- Beijing Key Laboratory of Spinal Disease Research, Peking University Third Hospital, Beijing, China
- Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China
| | - Weishi Li
- Department of Orthopedics, Peking University Third Hospital, Beijing, China
- Beijing Key Laboratory of Spinal Disease Research, Peking University Third Hospital, Beijing, China
- Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China
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Nuckols TK, Chen PG, Shetty KD, Brara HS, Anand N, Qureshi N, Skaggs DL, Doctor JN, Pevnick JM, Mannion AF. Surgical appropriateness nudges: Developing behavioral science nudges to integrate appropriateness criteria into the decision making of spine surgeons. PLoS One 2024; 19:e0300475. [PMID: 38640131 PMCID: PMC11029649 DOI: 10.1371/journal.pone.0300475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 02/20/2024] [Indexed: 04/21/2024] Open
Abstract
BACKGROUND Substantial variation exists in surgeon decision making. In response, multiple specialty societies have established criteria for the appropriate use of spine surgery. Yet few strategies exist to facilitate routine use of appropriateness criteria by surgeons. Behavioral science nudges are increasingly used to enhance decision making by clinicians. We sought to design "surgical appropriateness nudges" to support routine use of appropriateness criteria for degenerative lumbar scoliosis and spondylolisthesis. METHODS The work reflected Stage I of the NIH Stage Model for Behavioral Intervention Development and involved an iterative, multi-method approach, emphasizing qualitative methods. Study sites included two large referral centers for spine surgery. We recruited spine surgeons from both sites for two rounds of focus groups. To produce preliminary nudge prototypes, we examined sources of variation in surgeon decision making (Focus Group 1) and synthesized existing knowledge of appropriateness criteria, behavioral science nudge frameworks, electronic tools, and the surgical workflow. We refined nudge prototypes via feedback from content experts, site leaders, and spine surgeons (Focus Group 2). Concurrently, we collected data on surgical practices and outcomes at study sites. We pilot tested the refined nudge prototypes among spine surgeons, and surveyed them about nudge applicability, acceptability, and feasibility (scale 1-5, 5 = strongly agree). RESULTS Fifteen surgeons participated in focus groups, giving substantive input and feedback on nudge design. Refined nudge prototypes included: individualized surgeon score cards (frameworks: descriptive social norms/peer comparison/feedback), online calculators embedded in the EHR (decision aid/mapping), a multispecialty case conference (injunctive norms/social influence), and a preoperative check (reminders/ salience of information/ accountable justification). Two nudges (score cards, preop checks) incorporated data on surgeon practices and outcomes. Six surgeons pilot tested the refined nudges, and five completed the survey (83%). The overall mean score was 4.0 (standard deviation [SD] 0.5), with scores of 3.9 (SD 0.5) for applicability, 4.1 (SD 0.5) for acceptability, and 4.0 (SD 0.5), for feasibility. Conferences had the highest scores 4.3 (SD 0.6) and calculators the lowest 3.9 (SD 0.4). CONCLUSIONS Behavioral science nudges might be a promising strategy for facilitating incorporation of appropriateness criteria into the surgical workflow of spine surgeons. Future stages in intervention development will test whether these surgical appropriateness nudges can be implemented in practice and influence surgical decision making.
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Affiliation(s)
- Teryl K. Nuckols
- RAND Corporation, Santa Monica, CA, United States of America
- Cedars-Sinai Medical Center, Los Angeles, CA, United States of America
| | - Peggy G. Chen
- RAND Corporation, Santa Monica, CA, United States of America
| | | | - Harsimran S. Brara
- Kaiser Permanente, Los Angeles Medical Center, Los Angeles, CA, United States of America
| | - Neel Anand
- Cedars-Sinai Medical Center, Los Angeles, CA, United States of America
| | - Nabeel Qureshi
- RAND Corporation, Santa Monica, CA, United States of America
| | - David L. Skaggs
- Cedars-Sinai Medical Center, Los Angeles, CA, United States of America
| | - Jason N. Doctor
- Leonard D. Schaeffer Center for Health Policy & Economics, University of Southern California, Los Angeles, Los Angeles, CA, United States of America
| | - Joshua M. Pevnick
- Cedars-Sinai Medical Center, Los Angeles, CA, United States of America
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Anwar FN, Roca AM, Loya AC, Medakkar SS, Nie JW, Hartman TJ, MacGregor KR, Oyetayo OO, Zheng E, Federico VP, Sayari AJ, Lopez GD, Singh K. The influence of preoperative Veterans RAND-12 physical composite score in patients undergoing anterior lumbar interbody fusion [Retrospective Review]. J Clin Neurosci 2024; 123:36-40. [PMID: 38522109 DOI: 10.1016/j.jocn.2024.03.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 02/19/2024] [Accepted: 03/18/2024] [Indexed: 03/26/2024]
Abstract
No study has evaluated the preoperative impact of Veterans RAND-12 Physical Composite Score (VR-12 PCS) on anterior lumbar interbody fusion (ALIF) patients. This study examines its influence on physical function, mental health, pain, and disability outcomes. Two cohorts of ALIF patients with preoperative VR-12 PCS scores were formed using a single-surgeon registry: VR-12 PCS < 30 and VR-12 PCS ≥ 30. Demographics, perioperative characteristics, and patient-reported outcome measures (PROMs) were collected. PROMs of VR-12 PCS/Mental Composite Score (MCS), Short Form-12 (SF-12) PCS/MCS, Patient-Reported Outcomes Measurement Information System-Physical Function (PROMIS-PF), Patient Health Questionnaire-9 (PHQ-9), Visual Analog Scale-Back/Leg Pain (VAS-BP/LP), and Oswestry Disability Index (ODI) were collected pre/postoperatively up to 2-years. Demographics, perioperative characteristics, and preoperative PROMs were compared. Intercohort postoperative 6-week/final PROMs and improvements were compared. Of 80 patients, there were 41 in the VR-12 PCS < 30 cohort. Besides VR-12 PCS, VR-12 PCS < 30 patients reported inferior preoperative VR-12 MCS/SF-12 PCS/PROMIS-PF/PHQ-9/ODI scores (p ≤ 0.003, all). At 6-weeks postoperatively, VR-12 PCS < 30 reported inferior VR-12 PCS/SF-12 PCS/PROMIS-PF/PHQ-9 (p ≤ 0.030, all). There was greater improvement up to 6-weeks postoperatively in VR-12 PCS < 30 for VR-12 PCS/MCS and SF-12 PCS (p ≤ 0.020, all). VR-12 PCS < 30 reported superior improvement by final follow-up in VR-12 PCS/SF-12 PCS/PHQ-9 (p ≤ 0.006, all). MCID achievement rates were higher in VR-12 PCS < 30 for PHQ-9 and ODI (p ≤ 0.013, both). VR-12 PCS < 30 patients reported inferior postoperative physical function, mental health, and disability, yet superior magnitude of improvement in physical function and mental health. Rates of clinically meaningful improvement for VR-12 PCS < 30 were greater in mental health and disability.
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Affiliation(s)
- Fatima N Anwar
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Andrea M Roca
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Alexandra C Loya
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Srinath S Medakkar
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - James W Nie
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Timothy J Hartman
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Keith R MacGregor
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Omolabake O Oyetayo
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Eileen Zheng
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Vincent P Federico
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Arash J Sayari
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Gregory D Lopez
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA
| | - Kern Singh
- Department of Orthopaedic Surgery, Rush University Medical Center, 1611 W. Harrison St. Suite #300, Chicago, IL, 60612, USA.
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Cazzulino A, Bach K, Cordero R, Swarup I. Patient Expectations and Satisfaction in Pediatric Orthopedics. Curr Rev Musculoskelet Med 2023:10.1007/s12178-023-09869-5. [PMID: 37728727 DOI: 10.1007/s12178-023-09869-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/04/2023] [Indexed: 09/21/2023]
Abstract
PURPOSE OF REVIEW The purpose of the current review is to analyze the current literature regarding the tools available to evaluate patient expectations and satisfaction. There have been an increasing number of tools that have been developed and validated for various orthopedic procedures. Despite the growing number of tools, there are a limited number of tools available for pediatric patients. RECENT FINDINGS Several tools have been developed in orthopedics to evaluate patient expectations. However, there are no tools that have been validated in the pediatric population. In addition, pediatric patient expectations should be collected in conjunction with parent/caregiver expectations. Although not specifically validated for pediatric patients, there are several tools available that may pertain to pediatric patients including the HSS ACL Expectations Survey, HSS Shoulder Expectations Survey, HSS Knee Surgery Expectations Survey, HSS Foot and Ankle Surgery Expectation Survey, Sunnybrook Surgery Expectations Survey, Musculoskeletal Outcomes Data Evaluation and Management System (MODEMS) Instruments, Quick DASH, and DASH. In terms of patient satisfaction, there are even fewer tools available. Several tools have been developed to evaluate patient satisfaction and five additional tools within orthopedics. Of these tools, there are two that have been validated for pediatric patients: The Swedish Parents Satisfaction Questionnaire and the Scoliosis Research Society-22. There are a growing number of tools to evaluate patient's expectations and satisfaction in the orthopedic literature. Given most of these tools pertain to adult patients, there is a need for further development of tools specifically validated for pediatric patients and their parents/caregivers. Through the measurement of expectations and satisfaction, medical professionals can hope to improve satisfaction and outcomes.
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Affiliation(s)
- Alejandro Cazzulino
- Department of Orthopedic Surgery, University of California San Francisco, 500 Parnassus Ave. Millberry Union MU 320 W, San Francisco, CA, USA.
| | - Katherine Bach
- Department of Orthopedic Surgery, University of California San Francisco, 500 Parnassus Ave. Millberry Union MU 320 W, San Francisco, CA, USA
| | | | - Ishaan Swarup
- Department of Orthopedic Surgery, University of California San Francisco Benioff Children's Hospital Oakland, Oakland, CA, USA
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Benzakour A, Altsitzioglou P, Lemée JM, Ahmad A, Mavrogenis AF, Benzakour T. Artificial intelligence in spine surgery. INTERNATIONAL ORTHOPAEDICS 2023; 47:457-465. [PMID: 35902390 DOI: 10.1007/s00264-022-05517-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 07/11/2022] [Indexed: 01/28/2023]
Abstract
The continuous progress of research and clinical trials has offered a wide variety of information concerning the spine and the treatment of the different spinal pathologies that may occur. Planning the best therapy for each patient could be a very difficult and challenging task as it often requires thorough processing of the patient's history and individual characteristics by the clinician. Clinicians and researchers also face problems when it comes to data availability due to patients' personal information protection policies. Artificial intelligence refers to the reproduction of human intelligence via special programs and computers that are trained in a way that simulates human cognitive functions. Artificial intelligence implementations to daily clinical practice such as surgical robots that facilitate spine surgery and reduce radiation dosage to medical staff, special algorithms that can predict the possible outcomes of conservative versus surgical treatment in patients with low back pain and disk herniations, and systems that create artificial populations with great resemblance and similar characteristics to real patients are considered to be a novel breakthrough in modern medicine. To enhance the body of the related literature and inform the readers on the clinical applications of artificial intelligence, we performed this review to discuss the contribution of artificial intelligence in spine surgery and pathology.
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Affiliation(s)
- Ahmed Benzakour
- Centre Orléanais du Dos - Pôle Santé Oréliance, Saran, France
| | - Pavlos Altsitzioglou
- First Department of Orthopaedics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Jean Michel Lemée
- Department of Neurosurgery, University Hospital of Angers, Angers, France
| | | | - Andreas F Mavrogenis
- First Department of Orthopaedics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece.
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Point of View: "Correlates of Google Search Rankings for Spine Surgeons: An Analysis of Academic Pedigree, Social Media Presence, and Patient Ratings". Spine (Phila Pa 1976) 2020; 45:1382. [PMID: 32925822 DOI: 10.1097/brs.0000000000003601] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
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Durand WM, Daniels AH, Hamilton DK, Passias P, Kim HJ, Protopsaltis T, LaFage V, Smith JS, Shaffrey C, Gupta M, Klineberg E, Schwab F, Burton D, Bess S, Ames C, Hart R. Artificial Intelligence Models Predict Operative Versus Nonoperative Management of Patients with Adult Spinal Deformity with 86% Accuracy. World Neurosurg 2020; 141:e239-e253. [PMID: 32434029 DOI: 10.1016/j.wneu.2020.05.099] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 05/09/2020] [Accepted: 05/11/2020] [Indexed: 12/23/2022]
Abstract
OBJECTIVE Patients with ASD show complex and highly variable disease. The decision to manage patients operatively is largely subjective and varies based on surgeon training and experience. We sought to develop models capable of accurately discriminating between patients receiving operative versus nonoperative treatment based only on baseline radiographic and clinical data at enrollment. METHODS This study was a retrospective analysis of a multicenter consecutive cohort of patients with ASD. A total of 1503 patients were included, divided in a 70:30 split for training and testing. Patients receiving operative treatment were defined as those undergoing surgery up to 1 year after their baseline visit. Potential predictors included available demographics, past medical history, patient-reported outcome measures, and premeasured radiographic parameters from anteroposterior and lateral films. In total, 321 potential predictors were included. Random forest, elastic net regression, logistic regression, and support vector machines (SVMs) with radial and linear kernels were trained. RESULTS Of patients in the training and testing sets, 69.0% (n = 727) and 69.1% (n = 311), respectively, received operative management. On evaluation with the testing dataset, performance for SVM linear (area under the curve =0.910), elastic net (0.913), and SVM radial (0.914) models was excellent, and the logistic regression (0.896) and random forest (0.830) models performed very well for predicting operative management of patients with ASD. The SVM linear model showed 86% accuracy. CONCLUSIONS This study developed models showing excellent discrimination (area under the curve >0.9) between patients receiving operative versus nonoperative management, based solely on baseline study enrollment values. Future investigations may evaluate the implementation of such models for decision support in the clinical setting.
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Affiliation(s)
- Wesley M Durand
- Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Alan H Daniels
- Department of Orthopaedics, Division of Spine Surgery, Alpert Medical School of Brown University, Providence, Rhode Island, USA.
| | - David K Hamilton
- Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Peter Passias
- Department of Orthopedics, New York University Langone Orthopedic Hospital, New York, New York, USA
| | - Han Jo Kim
- Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, New York, USA
| | | | - Virginie LaFage
- Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, New York, USA
| | - Justin S Smith
- Department of Neurosurgery, University of Virginia Health System, Charlottesville, Virginia, USA
| | | | - Munish Gupta
- Department of Orthopaedic Surgery, Washington University, St. Louis, Missouri, USA
| | - Eric Klineberg
- Department of Orthopaedic Surgery, University of California-Davis, Sacramento, California, USA
| | - Frank Schwab
- Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, New York, USA
| | - Doug Burton
- Department of Orthopaedic Surgery, University of Kansas Hospital, Kansas City, Kansas, USA
| | - Shay Bess
- Department of Orthopaedic Surgery, Denver International Spine Center, Denver, Colorado, USA
| | - Christopher Ames
- Department of Neurosurgery, University of California-San Francisco, California, USA
| | - Robert Hart
- Division of Spine Surgery, Swedish Neuroscience Institute, Seattle, Washington, USA
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