A Retrospective Study of the Association between Pain Intensity and Opioid Use with Length of Stay during Musculoskeletal Inpatient Rehabilitation after Primary Knee and Hip Arthroplasty
Bibliographic record
Abstract
BACKGROUND: The relationship between pain intensity, opioid consumption, and length of stay (LOS) has received little attention in primary, lower extremity joint arthroplasty patients admitted to inpatient musculoskeletal rehabilitation. OBJECTIVE: To assess how initial pain and other clinical factors are associated with rehabilitation LOS. DESIGN: Retrospective chart review. SETTING: Rehabilitation hospital. PARTICIPANTS: One hundred ninety nine patients admitted for inpatient rehabilitation. INTERVENTIONS: Not Applicable. MAIN OUTCOME MEASURES: Pain intensities on the Numeric Rating Scale (NRS) were completed 3 times daily and total daily opioid consumption recorded in terms of morphine equivalents (MEQ). Confounding variables included patient demographics, medical comorbidity burden using the Charlson Comorbidity Index (CCI), and early functional status as measured by the motor subscale from the Functional Independence Measure (FIM). RESULTS: Mean day 3 NRS values of ≥5.2 and total day 3 opioid consumption of >50 MEQ were associated with a prolonged LOS by nearly 3 and 2 days, respectively. Within a multivariate linear regression, age, mean day 3 pain, comorbidity burden, and early motor functional status accounted for 36% of the variability seen in joint replacement rehabilitation LOS. With all other variables remaining constant, for every unit increase in mean day 3 pain and CCI, this amounted to an additional 5% and 4% increase to LOS, whereas each unit increase in admission motor FIM decreased estimated LOS by 3%. CONCLUSION: Mean pain intensity and total opioid consumption on day 3 of inpatient rehabilitation is associated with LOS. For the rehabilitation physician, this is useful information as the earlier identification of patients with poorly controlled pain can lead to directed intervention, better patient care, and significant cost savings.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".