Long-Term Opioid Therapy in Spine Center Outpatients: Protocol for the Spinal Pain Opioid Cohort (SPOC) Study
Bibliographic record
Abstract
BACKGROUND: Spinal pain is the leading cause of patient-years lived with chronic pain and disability worldwide. Although opioids are well documented as an effective short-term pain-relieving medication, more than a few weeks of treatment may result in a diminishing clinical effect as well as the development of addictive behavior. Despite recognition of opioid addiction in pain patients as a major problem commonly experienced in the clinic, no reference material exists on the scope of long-term problems in novel opioid users and the link to clinical outcomes. OBJECTIVE: The main aims of this study are to describe baseline and follow-up characteristics of the Spinal Pain Opioid Cohort (SPOC), to evaluate the general use of opioids in spinal pain when an acute pain episode occurs, and to demonstrate the prevalence of long-term opioid therapy (LTOT). METHODS: Prospective clinical registry data were collected from an outpatient spine center setting during 2012-2013 including patients with a new spinal pain episode lasting for more than 2 months, aged between 18 and 65 years who had their first outpatient visit in the center. Variables include demographics, clinical data collected in SpineData, the Danish National Patient Register, and The Danish National Prescription Registry. The primary outcome parameter is long-term prescription opioid use registered from 4 years before the first spine center visit to 5 years after. RESULTS: This is an ongoing survey. It is estimated that more than 8000 patients fulfill the SPOC inclusion criteria. In 2019, we began the intellectual process of identifying the most relevant supplementary data available from the wide range of existing national registries available in Denmark. We have now begun merging SpineData with relevant opioid data from Danish national registers and will continue to extract data up to 2021-2022. We will also be looking at data regarding somatic or psychiatric hospitalization patterns, patient usage of health care resources, as well as their working status and disability pensions. CONCLUSIONS: To our knowledge, this survey will be the first to document the scope of long-term problems regarding LTOT and opioid addiction following new spinal pain episodes and comparing descriptive follow-up data between substance users and nonusers. TRIAL REGISTRATION: ISRCTN Registry ISRCTN69685117; http://www.isrctn.com/ISRCTN69685117. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/21380.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".