Don’t Throw the ‘Bio’ out of the Bio-Psycho-Social Model: Editorial for Spine Rehabilitation in 2022 and Beyond

Harrison, Deed E.; Oakley, Paul A.; Moustafa, Ibrahim M.

doi:10.3390/jcm12175602

Cited by 3 publications

References 59 publications

(164 reference statements)

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Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction

Moustafa,

Ozsahin,

Mustapha

et al. 2024

Sci Rep

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This study explored the application of machine learning in predicting post-treatment outcomes for chronic neck pain patients undergoing a multimodal program featuring cervical extension traction (CET). Pre-treatment demographic and clinical variables were used to develop predictive models capable of anticipating modifications in cervical lordotic angle (CLA), pain and disability of 570 patients treated between 2014 and 2020. Linear regression models used pre-treatment variables of age, body mass index, CLA, anterior head translation, disability index, pain score, treatment frequency, duration and compliance. These models used the sci-kit-learn machine learning library within Python for implementing linear regression algorithms. The linear regression models demonstrated high precision and accuracy, and effectively explained 30–55% of the variability in post-treatment outcomes, the highest for the CLA. This pioneering study integrates machine learning into spinal rehabilitation. The developed models offer valuable information to customize interventions, set realistic expectations, and optimize treatment strategies based on individual patient characteristics as treated conservatively with rehabilitation programs using CET as part of multimodal care.

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Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction

Moustafa,

Ozsahin,

Mustapha

et al. 2024

Sci Rep

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Rotations and Translations of Head Posture Parameters as a Predictor of the Rehabilitation Management Outcomes in Patients with Chronic Nonspecific Neck Pain: A Multicenter Prospective Case Series

Anwar,

Moustafa,

Ahbouch

et al. 2024

Preprint

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A multicenter, prospective consecutive case series study was conducted in 5 physiotherapy clinics in the UAE from January 2021 to March 2023 to assess rotations and translations of head posture parameters as potential predictors of conservative therapy outcomes in patients with chronic non-specific neck pain (CNSNP). Eighty-six patients (mean age 35 yrs., 65% male) with CNSNP underwent conservative therapy. All participants received a detailed examination including a computerized cervical spine posture analysis and demographic data was collected. Interventions included specific exercises, diathermy, longitudinal traction, education, a detailed exercise program, ergonomic advice, and medications. Interventions were applied 3 times per week for 8 weeks. Follow-up was 6-months after final treatment. A successful outcome was based on a minimum improvement of the following four outcomes using the patient centered outcome questionnaire (PCOQ): (1) reduction of pain by 17.5 points (0–100 NRS); (2) fatigue reduction by 7.5 points; (3) distress reduction by 5 points; and (4) interference reduction by 9.5 points. At 6-month follow-up it was found that success rates for pain, fatigue, distress, and interference were above 60% for the total participants. The logistic regression for predicting overall success in combined outcomes based on age, gender, smoking status, marital status, and sagittal head translation was: 1) Age: the odds ratio (0.69) suggests that as age increases, the likelihood of overall success decreases (p = 0.001); 2) Sex: females have higher odds of overall success compared to males (OR = 2.71, p < 0.001); 3) Smoking status and marital status: neither of these factors were statistically significant predictors of overall success; 4) Sagittal head translation: each unit increase (more anterior) in this abnormal posture reduced the odds of success by 13%, showing a strong and significant effect (OR = 0.13, p < 0.001). Overall, our findings indicate that younger age, female sex, and better posture alignment of the cervical spine all had a substantial impact on the likelihood of success of 6-month outcomes in patients suffering CNSNP.

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Sagittal Full-Spine vs. Sectional Cervical Lateral Radiographs: Are the Measurements of Cervical Alignment Interchangeable?

Haas,

Oakley,

Betz

et al. 2024

JCM

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(1) Background: This study assessed the relationship between cervical spine parameters taken on standing full-spine lateral radiographic images compared to sectional lateral cervical radiographs. (2) Methods: Full-spine (FS) and sectional lateral cervical (LC) radiographs from four spine treatment facilities across the USA retrospectively provided data collected on 220 persons to assess the comparison of three sagittal cervical radiographic measurements between the two views. The measures included cervical lordosis using the absolute rotation angle from C2-C7, sagittal cervical translation of C2-C7, and atlas plane angle to horizontal. Linear correlation and R2 models were used for statistical comparison of the measures for the two views. (3) Results: The mean values of the three measurements were statistically different from each other: C2-C7 translation (FS = 19.84 ± 11.98 vs. LC = 21.18 ± 11.8), C2-C7 lordosis (FS = −15.3 ± 14.63 vs. LC = −18.32 ± 13.16), and atlas plane (FS = −19.99 ± 8.88 vs. LC = −22.56 ± 8.93), where all values were p < 0.001. Weak-to-moderate-to-strong correlations existed between the full-spine and sectional lateral cervical radiographic variables. The R2 values varied based on the measurement were R2 = 0.768 (p < 0.001) for sagittal cervical translation of C2-C7 (strong), R2 = 0.613 (p < 0.001) for the absolute rotation angle C2-C7 (moderate), and R2 = 0.406 (p < 0.001) for the atlas plane line (weak). Though a linear correlation was identified, there were consistent intra-person differences between the measurements on the full spine versus sectional lateral cervical radiographic views, where the full-spine view consistently underestimated the magnitude of the variables. (4) Conclusion: Key sagittal cervical radiographic measurements on the full spine versus sectional lateral cervical radiographic views show striking intra-person differences. The findings of this study confirm that full spine versus sectional lateral cervical radiographic views provide different biomechanical magnitudes of cervical sagittal alignment, and caution should be exercised by health care providers as these are not interchangeable. We recommend the LC view for measurement of cervical sagittal alignment variables.

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Don’t Throw the ‘Bio’ out of the Bio-Psycho-Social Model: Editorial for Spine Rehabilitation in 2022 and Beyond

Abstract: Spinal injuries, disorders and disabilities are among the leading causes for work loss, suffering, and health care expenditures throughout the industrialized world [...]

Cited by 3 publications

References 59 publications

Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction

Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction

Rotations and Translations of Head Posture Parameters as a Predictor of the Rehabilitation Management Outcomes in Patients with Chronic Nonspecific Neck Pain: A Multicenter Prospective Case Series

Sagittal Full-Spine vs. Sectional Cervical Lateral Radiographs: Are the Measurements of Cervical Alignment Interchangeable?

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