Bibliographic record
Abstract
Postoperative pain is characterized as an acute pain, prevalent inside the hospital environment, commonly associated with tissue damage. This study had, as a general objective, the evaluation of post-operative pain in clients who have undergone to cardiac surgery by sternotomy, according to the occurrence, intensity (measured at rest and on deep inspiration), location and quality, 1st, 2nd and 3rd. This is a cohort, prospective study, developed in a general hospital in the countryside of the State of Goiás, in the period from January to August 2008. Pain intensity was measured by means of verbal numerical scale (0-10); quality was measured by the McGill Pain Questionnaire (MPQ-SF), the location was measured by body diagrams, and preoperative anxiety was measured via STAI (State/Trait Anxiety Inventory). Numerical vares were explored by descriptive measures of centrality (mean and median) and dispersion (minimum, maximum, standard deviation). The categorical variables were explored by simple absolute frequencies and percentages. The associations between variables were explored using non-parametric association tests, such as chi-square, Spearman coefficient, Kruskal-Wallis and Mann-Whitney with α = 5%. 62 clients participated, 56.5% men, 67.7% white, 42% of socioeconomic class C and 72.6% married. The mean age was 54.8 years, SD = 12.1 years, and the predominant age group (29.0%) from 51 to 60 years. The prevalent surgery was valve surgery (46.8%), followed by myocardial revascularization (40.3%). The postoperative anxiety level was medium to 92.0% of the clients. Pain intensity at rest and deep inspiration had a decrease as days passed by, (p<0.05), being classified as mild-moderate (MD [median]=0,0-3,0; Q1 [quartile 1]=0,0-1,0; Q3 [quartile 3]=2,0-6,0; MAX [maximum]=8,0-10,0; MIN [minimum]=0,0-0,0) at rest and moderate-intense (MD=2,0-5,0; Q1=0,75-2,75; Q3=3,0-7,25; MAX=9,0-10,0; MIN=0,0-0,0) at deep inspiration. The chest region was the region in where there was the greatest pain occurrence in the 4 days of PO (40,3%-53,2%).The words which were most frequently chosen to describe postoperative pain were tiring/exhaustive (83,9%- 95,2%), painful (88,7%-91,9%), persistent (85,5%-87,1%) and splitting (72,6%- 82,3%). Splitting, was the one which received the greatest attribution (score 3) from the sensory-discriminative group, in numerical scale (0-3), both at POI as in the 1st and 2nd PO. The PRI (Pain Rating Index), results from the MPQ-SF, for the sensory group (PRI-S) , the affective group (PRI-A) and total (PRI-T) showed a reduction in the scores over the 4 days of PO (p<0.001). The correlation between the pain intensity and PRI scores in the 4 days of PO was positive and significant both for the PRI-S (0.52-0.34; p<0.001), and PRI-A (0.52-0.30; p<0.001) as to PRI-T (0.56-0.36; p<0.001). Postoperative pain at rest intensity was consistent to the one observed in other studies. However, postoperative pain at deep inspiration is still intense, being able to generate greatest losses in the clients early recovery. Even tough it isn t significantly associated to pain intensity, it is stressed that all the clients presented some degree of anxiety, a natural stimulus which can influence the endogenous pain modulation system, which may exacerbate the pain. In terms of quality, pain was described through words from the sensory and affective MPQ group, pointing to the multidimensionality of the painful experience. It is stressed the importance of the evaluation/measure and the postoperative pain systematic record as essential items to the adequate relief of this experience in the surgical environment.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".