Quantitative Assessment of Chronic Postsurgical Pain Using the McGill Pain Questionnaire
Bibliographic record
Abstract
OBJECTIVES: The McGill Pain Questionnaire (MPQ) provides a quantitative profile of 3 major psychologic dimensions of pain: sensory-discriminative, motivational-affective, and cognitive-evaluative. Although the MPQ is frequently used as a pain measurement tool, no studies to date have compared the characteristics of chronic post-surgical pain after different surgical procedures using a quantitative scoring method. METHODS: Three separate questionnaire surveys were administered to patients who had undergone surgery at different time points between 1990 and 2000. Surgical procedures selected were mastectomy (n = 511 patients), inguinal hernia repair (n = 351 patients), and cardiac surgery via a central chest wound with or without saphenous vein harvesting (n = 1348 patients). A standard questionnaire format with the MPQ was used for each survey. The IASP definition of chronic pain, continuously or intermittently for longer than 3 months, was used with other criteria for pain location. The type of chronic pain was compared between the surgical populations using 3 different analytical methods: the Pain Rating Intensity score using scale values, (PRI-S); the Pain Rating Intensity using weighted rank values multiplied by scale value (PRI-R); and number of words chosen (NWC). RESULTS: The prevalence of chronic pain after mastectomy, inguinal herniorrhaphy, and median sternotomy with or without saphenectomy was 43%, 30%, and 39% respectively. Chronic pain most frequently reported was sensory-discriminative in quality with similar proportions across different surgical sites. Average PRI-S values after mastectomy, hernia repair, sternotomy (without postoperative anginal symptoms), and saphenectomy were 14.06, 13.00, 12.03, and 8.06 respectively. Analysis was conducted on cardiac patients who reported anginal symptoms with chronic post-surgical pain (PRI-S value 14.28). Patients with moderate and severe pain were more likely to choose more than 10 pain descriptors, regardless of the operative site (P < 0.05). DISCUSSION: The prevalence and characteristics of chronic pain was remarkably similar across different operative groups. This study is the first to quantitatively compare chronic post-surgical pain using similar methodologies in heterogeneous post-surgical populations.
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 | 0.047 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".