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Objective functional impairment in lumbar degenerative disease: concurrent validity of the baseline severity stratification for the five-repetition sit-to-stand test

Anita M. Klukowska, Marc L. Schröder, Martin N. Stienen, and Victor E. Staartjes

OBJECTIVE

The five-repetition sit-to-stand (5R-STS) test provides a new dimension of clinical assessment by capturing objective functional impairment (OFI). Through the utilization of data from two prospective studies, the authors sought to evaluate the concurrent validity of the proposed 5R-STS baseline severity stratification (BSS) for OFI with the following levels based on time to completion in seconds: none, ≤ 10.4; mild, 10.5–15.2; moderate, 15.3–22.0; and severe, > 22.0 seconds.

METHODS

Patients with degenerative diseases of the spine performed the 5R-STS test and completed visual analog scales (VASs) for back and leg pain, the Oswestry Disability Index (ODI), the Roland-Morris Disability Questionnaire (RMDQ), and EQ-5D questionnaires. The degree of OFI severity was assessed based on the previously proposed BSS, and its association with patient-reported scales was evaluated using ANOVA as well as crude and adjusted linear regression models.

RESULTS

Our sample included 240 patients, of whom 101 exhibited no OFI, whereas 80, 34, and 25 were judged to have mild, moderate, and severe OFI, respectively. A higher baseline severity was strongly associated with loss of working ability (p < 0.001), as well as results of all patient-reported scales (p ≤ 0.001), with the exception of the VAS for leg pain (p = 0.556). Crude and adjusted regression analyses corroborated these findings, although only patients with moderate and severe OFI as judged by using the 5R-STS BSS demonstrated clinically relevant differences compared with patients without OFI.

CONCLUSIONS

The degree of OFI—based on the 5R-STS BSS—is strongly associated with measures of back pain, subjective functional impairment, and health-related quality of life. However, leg pain severity is not reflected within the dimension of OFI measured by the 5R-STS. The proposed BSS appears to be a concurrently valid and clinically relevant measure of OFI in patients with degenerative spinal pathologies.

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Conflicts of interest in randomized controlled trials reported in neurosurgical journals

Victor E. Staartjes, Anita M. Klukowska, Elena L. Sorba, and Marc L. Schröder

OBJECTIVE

Randomized controlled trials (RCTs) form the basis of today’s evidence-based approach to medicine, and play a critical role in guidelines and the drug and device approval process. Conflicts of interest (COIs) are commonplace in medical research, but little is known about their influence. The authors aimed to evaluate the extent and influence of COIs in recent RCTs published in core neurosurgical journals using a cross-sectional analysis.

METHODS

Through review of 6 general neurosurgical journals, all interventional RCTs published from January 2009 to January 2019 were identified. Because it is difficult to objectively assess study outcome, the authors opted for a strict rating approach based on the statistical significance of unambiguously reported primary endpoints, and the reported statistical protocol.

RESULTS

A total of 129 RCTs met the inclusion criteria. During the study period, the Journal of Neurosurgery published the largest number of RCTs (n = 40, 31%). Any potential COI was disclosed by 57%, and a mean of 12% of authors had a personal COI. Nonfinancial industry involvement was reported in 10%, while 31% and 20% received external support and sponsoring, respectively. Study registration was reported by 56%, while 51% of studies were blinded. Registration showed an increasing trend from 17% to 76% (p < 0.001). The median randomized sample size was 92 (interquartile range 50–153), and 8% were designed to investigate noninferiority or equality. Sixty-three RCTs (49%) unambiguously reported a primary endpoint, of which 13% were composite primary endpoints. In 43%, study outcome was positive, which was associated with a noninferiority design (31% vs 3%, p = 0.007) and a composite primary endpoint (46% vs 9%, p = 0.002). Potential COIs were not significantly associated with study positivity (69% vs 59%, p = 0.433). In the multivariate analysis, only a composite primary endpoint remained predictive of a positive study outcome (odds ratio 6.34, 95% confidence interval 1.51–33.61, p = 0.017).

CONCLUSIONS

This analysis provides an overview of COIs and their potential influence on recent trials published in core neurosurgical journals. Reporting of primary endpoints, study registration, and uniform disclosure of COIs are crucial to ensure the quality of future neurosurgical randomized trials. COIs do not appear to significantly influence the outcome of randomized neurosurgical trials.

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Machine learning–augmented objective functional testing in the degenerative spine: quantifying impairment using patient-specific five-repetition sit-to-stand assessment

Victor E. Staartjes, Anita M. Klukowska, Moira Vieli, Christiaan H. B. van Niftrik, Martin N. Stienen, Carlo Serra, Luca Regli, W. Peter Vandertop, and Marc L. Schröder

OBJECTIVE

What is considered “abnormal” in clinical testing is typically defined by simple thresholds derived from normative data. For instance, when testing using the five-repetition sit-to-stand (5R-STS) test, the upper limit of normal (ULN) from a population of spine-healthy volunteers (10.5 seconds) is used to identify objective functional impairment (OFI), but this fails to consider different properties of individuals (e.g., taller and shorter, older and younger). Therefore, the authors developed a personalized testing strategy to quantify patient-specific OFI using machine learning.

METHODS

Patients with disc herniation, spinal stenosis, spondylolisthesis, or discogenic chronic low-back pain and a population of spine-healthy volunteers, from two prospective studies, were included. A machine learning model was trained on normative data to predict personalized “expected” test times and their confidence intervals and ULNs (99th percentiles) based on simple demographics. OFI was defined as a test time greater than the personalized ULN. OFI was categorized into types 1 to 3 based on a clustering algorithm. A web app was developed to deploy the model clinically.

RESULTS

Overall, 288 patients and 129 spine-healthy individuals were included. The model predicted “expected” test times with a mean absolute error of 1.18 (95% CI 1.13–1.21) seconds and R2 of 0.37 (95% CI 0.34–0.41). Based on the implemented personalized testing strategy, 191 patients (66.3%) exhibited OFI. Type 1, 2, and 3 impairments were seen in 64 (33.5%), 91 (47.6%), and 36 (18.8%) patients, respectively. Increasing detected levels of OFI were associated with statistically significant increases in subjective functional impairment, extreme anxiety and depression symptoms, being bedridden, extreme pain or discomfort, inability to carry out activities of daily living, and a limited ability to work.

CONCLUSIONS

In the era of “precision medicine,” simple population-based thresholds may eventually not be adequate to monitor quality and safety in neurosurgery. Individualized assessment integrating machine learning techniques provides more detailed and objective clinical assessment. The personalized testing strategy demonstrated concurrent validity with quality-of-life measures, and the freely accessible web app (https://neurosurgery.shinyapps.io/5RSTS/) enabled clinical application.