Nociceptive and Neuropathic Pain Qualities in Men and Women with Acute Coronary Syndromes: A Complex Pain Presentation
Bibliographic record
Abstract
Background: Cardiac pain arising from acute coronary syndrome (ACS) is a multi-factorial phenomenon. Historically, episodes of cardiac pain have been captured using a one-dimensional numeric pain rating scale. Lacking in clinical practice are acute pain assessments that employ a comprehensive evaluation of an emergent ACS episode. Aim: To examine the sensory-discriminative, motivational-affective and cognitive-evaluative dimensions of ACS-related pain. Methods: A descriptive-correlational, repeated-measure design was used to collect data on 121 ACS patients of their cardiac pain intensity. The (numeric rating scale-NRS 0-10 scale) measured chest pain “Now” and “Worst pain in the previous 2 hours over 8 hours” and the McGill Pain Questionnaire Short-Form (MPQ-SF) measured pain at 4 hours. Results: Mean age was 67.6 ± 13, 50% were male, 60% had unstable angina and 40% had Non-ST-elevation myocardial infarction. Cardiac pain intensity scores remained in the mild range from 1.1 ± 2.2 to 2.4 ± 2.7. MPQ-SF: 66% described pain as distressing and 26% reported pain was horrible or excruciating. Participants described ACS pain quality as acute injury (nociceptive pain: heavy, cramping, stabbing), as nerve damage (neuropathic: gnawing, hot-burning, shooting) and as a mixture of acute and chronic pain qualities (aching, tender and throbbing). Conclusions: Patients reported both nociceptive and neuropathic cardiac pain. It is unclear if pain perceptions are due to: i) pathophysiology of clot formation, ii) occurrence of a first or repeated ACS episode, or iii) complex co-morbidities. Pain arising from ACS requires an understanding of the interplay of ischemic, metabolic and neuropathophysiological mechanisms that contribute to complex cardiac pain experiences.
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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 | 0.002 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".