Association Between Pain Catastrophizing and Pain and Cardiovascular Changes During a Cold-Pressor Test in Athletes
Bibliographic record
Abstract
CONTEXT: Athletes are often exposed to pain due to injury and competition. Using preliminary evidence, researchers have shown that cardiovascular measures could be an objective measure of pain, but the cardiovascular response can be influenced by psychological factors, such as catastrophizing. OBJECTIVE: To use a painful cold-pressor test (CPT) to measure the relationship among catastrophizing, pain, and cardiovascular variables in athletes. DESIGN: Cohort study. SETTING: Laboratory. PATIENTS OR OTHER PARTICIPANTS: A total of 36 male rugby athletes (age = 24.0 ± 4.6 years, height = 180.0 ± 6.1 cm, mass = 90.5 ± 13.8 kg). MAIN OUTCOME MEASURE(S): We measured catastrophizing using the Pain Catastrophizing Scale and pain using a numeric pain rating scale. Cardiovascular measures were heart rate, systolic and diastolic blood pressure, and heart rate variability. RESULTS: During the CPT, participants experienced increases in pain (from 0 to 4.1 ± 2.2), systolic blood pressure (from 126.7 ± 16.5 to 149.7 ± 23.4 mm Hg), diastolic blood pressure (from 76.9 ± 8.3 to 91.9 ± 11.5 mm Hg), and heart rate variability (from 0.0164 ± 0.0121 to 0.0400 ± 0.0323 milliseconds; all P values < .001). In addition, we observed a decrease in heart rate after the CPT (P = .04). We found a correlation between athletes' pain catastrophizing and both pain intensity and change in heart rate during the CPT (P = .02 and P = .003, respectively). Linear regression indicated that pain and catastrophizing explained 29% of the variance in the change in heart rate (P = .003). CONCLUSIONS: Athletes who had catastrophizing thoughts were more likely to experience higher levels of pain and a greater cardiovascular response during a painful stimulus. The change in cardiovascular variables may be a good objective measure of pain in athletes in the future.
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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 | 0.004 | 0.001 |
| 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".