Early surgery for sciatica

Schmid, Annina; Dove, Lucy; Ridgway, Lucy; Price, Christine

doi:10.1136/bmj.p791

Cited by 2 publications

(2 citation statements)

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“…We argue that patients at high risk of not achieving a substantial benefit from surgery should be recommended other treatment pathways, but an impact study is needed to examine potential outcomes following nonsurgical treatment. We also acknowledge that important questions remain regarding the optimal timing of surgery, 45 which we were not able to shed light on within our study design.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Models for Predicting Disability and Pain Following Lumbar Disc Herniation Surgery

Berg,

Gorosito,

Fjeld

et al. 2024

JAMA Netw Open

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ImportanceLumber disc herniation surgery can reduce pain and disability. However, a sizable minority of individuals experience minimal benefit, necessitating the development of accurate prediction models.ObjectiveTo develop and validate prediction models for disability and pain 12 months after lumbar disc herniation surgery.Design, Setting, and ParticipantsA prospective, multicenter, registry-based prognostic study was conducted on a cohort of individuals undergoing lumbar disc herniation surgery from January 1, 2007, to May 31, 2021. Patients in the Norwegian Registry for Spine Surgery from all public and private hospitals in Norway performing spine surgery were included. Data analysis was performed from January to June 2023.ExposuresMicrodiscectomy or open discectomy.Main Outcomes and MeasuresTreatment success at 12 months, defined as improvement in Oswestry Disability Index (ODI) of 22 points or more; Numeric Rating Scale (NRS) back pain improvement of 2 or more points, and NRS leg pain improvement of 4 or more points. Machine learning models were trained for model development and internal-external cross-validation applied over geographic regions to validate the models. Model performance was assessed through discrimination (C statistic) and calibration (slope and intercept).ResultsAnalysis included 22 707 surgical cases (21 161 patients) (ODI model) (mean [SD] age, 47.0 [14.0] years; 12 952 [57.0%] males). Treatment nonsuccess was experienced by 33% (ODI), 27% (NRS back pain), and 31% (NRS leg pain) of the patients. In internal-external cross-validation, the selected machine learning models showed consistent discrimination and calibration across all 5 regions. The C statistic ranged from 0.81 to 0.84 (pooled random-effects meta-analysis estimate, 0.82; 95% CI, 0.81-0.84) for the ODI model. Calibration slopes (point estimates, 0.94-1.03; pooled estimate, 0.99; 95% CI, 0.93-1.06) and calibration intercepts (point estimates, −0.05 to 0.11; pooled estimate, 0.01; 95% CI, −0.07 to 0.10) were also consistent across regions. For NRS back pain, the C statistic ranged from 0.75 to 0.80 (pooled estimate, 0.77; 95% CI, 0.75-0.79); for NRS leg pain, the C statistic ranged from 0.74 to 0.77 (pooled estimate, 0.75; 95% CI, 0.74-0.76). Only minor heterogeneity was found in calibration slopes and intercepts.ConclusionThe findings of this study suggest that the models developed can inform patients and clinicians about individual prognosis and aid in surgical decision-making.

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Section: Discussionmentioning

confidence: 99%

Machine Learning Models for Predicting Disability and Pain Following Lumbar Disc Herniation Surgery

Berg,

Gorosito,

Fjeld

et al. 2024

JAMA Netw Open

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“…Editorialists Annina Schmid and colleagues warn against extrapolating these results to patients in primary care settings, most of whom recover in a few months (doi:10.1136/bmj.p791). 2 The value of surgery is mainly confined to patients referred to secondary care with clear discogenic sciatica when rapid pain relief is a priority. For those patients, the results of this review “challenge the stepped care approach that offers the least invasive options first to everyone with sciatica.”…”

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confidence: 99%

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Loder¹

2023

BMJ

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Early surgery for sciatica

Abstract: Does new evidence challenge a stepped care approach for all patients?

Cited by 2 publications

References 16 publications

Machine Learning Models for Predicting Disability and Pain Following Lumbar Disc Herniation Surgery

Machine Learning Models for Predicting Disability and Pain Following Lumbar Disc Herniation Surgery

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