Physiological Indices of Stress Prior to and Following Total Knee Arthroplasty Predict the Occurrence of Severe Post-Operative Pain
Bibliographic record
Abstract
OBJECTIVE: The severe pain and disability associated with osteoarthritis often motivate individuals to undergo arthroplastic surgery. However, a significant number of surgical patients continue to experience pain following surgery. Prior research has implicated both the hypothalamic-pituitary-adrenal (HPA) axis and sympathetic nervous system (SNS) in the sensitization of pain receptors and chronic pain conditions. This study uses a prospective, observational, cohort design to examine whether physiological stress responses before and after surgery could predict post-operative pain severity. SUBJECTS: Participants included 110 patients undergoing total knee arthroplasty. METHODS: Physiological indices of stress included the measurement of catecholamine and cortisol levels in 15-hour urine samples collected prior to and 1 month following surgery, as well as in-hospital heart rate and blood pressure (before and after surgery), which were abstracted from medical records. Patients completed the pain subscale of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) [Bellamy et al., J Orthop Rheumatol 1: , 95 (1988)] 2.5 weeks prior to surgery and at a 3-month follow-up. RESULTS: Contrary to expectations, lower stress hormone levels at baseline were related to more severe post-operative pain. Data at later time points, however, supported our hypothesis: cardiovascular tone shortly before surgery and urinary levels of epinephrine 1 month following surgery were positively related to pain severity 3 months later. CONCLUSION: Results suggest that the occurrence of post-operative pain can be predicted on the basis of stress physiology prior to and following arthroplastic surgery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".