The Effect of Sunlight on Postoperative Analgesic Medication Use: A Prospective Study of Patients Undergoing Spinal Surgery
Bibliographic record
Abstract
Objective: Exposure to natural sunlight has been associated with improvement in mood, reduced mortality among patients with cancer, and reduced length of hospitalization for patients who have experienced myocardial infarction. Our aim was to evaluate whether the amount of sunlight in a hospital room modifies a patient’s psychosocial health, the quantity of analgesic medication used, and the pain medication cost. Methods: A prospective study of pain medication use was conducted in 89 patients undergoing elective cervical and lumbar spinal surgery where they were housed on either the “bright” or “dim” side of the same hospital unit. Analgesic medication was converted to standard morphine equivalents for interpatient comparison. The intensity of sunlight in each hospital room was measured daily and psychologic questionnaires were administered on the day after surgery and at discharge. Results: Patients staying on the bright side of the hospital unit were exposed to 46% higher-intensity sunlight on average (p = .005). Patients exposed to an increased intensity of sunlight experienced less perceived stress (p = .035), marginally less pain (p = .058), took 22% less analgesic medication per hour (p = .047), and had 21% less pain medication costs (p = .047). Age quartile was the only other variable found to be a predictor of analgesic use, with a significant negative correlation (p <.001). However, patients housed on the bright side of the hospital consistently used less analgesic medications in all age quartiles. Conclusion: The exposure postoperatively of patients who have undergone spinal surgery to increased amounts of natural sunlight during their hospital recovery period may result in decreased stress, pain, analgesic medication use, and pain medication costs. ACCF = anterior cervical corpectomy and fusion; ACDF = anterior cervical discectomy and fusion; AEDET = Achieving Excellence Design Evaluation Toolkit; CES-D = Center for Epidemiological Studies–Depression Scale; CNS = central nervous system; DS = degenerative spondylolisthesis; LOS = length of stay; LOT-R = Life Orientation Test-Revised; LS = lumbar stenosis; MPQ = McGill Pain Questionnaire; OR = operating room; PACU = postanesthesia care unit; PCA = patient-controlled analgesia; PFI = Private Finance Initiative; POMS = Reduced POMS–Anxiety Scale; PRN = as needed; PSS = Perceived Stress Scale; SAD = seasonal affective disorder; TCAs = tricyclic antidepressants; UK = United Kingdom.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".