Evaluation of analgesic use in orthopaedic postoperative acute pain management / Khairul Barriah Mat Salleh
Bibliographic record
Abstract
Objective: The main purpose of this study is determine the pain score profile of patients prescribed with analgesic using the Short Form McGill Pain Questionnaire and to assess the use of analgesic drugs in orthopedic post operative patients is appropriate. Method : A cross sectional study was conducted on 102 patients undergoing orthopaedic surgeries in Hospital Kajang, Selangor. The data was collected between August and November 2011. Data collection was carried out using the Short-Form McGill Pain Questionnaire (SF-MPQ). Patients pain score was measured using VAS pain score (1 to 10), on day 1 of operation (Dl), day 3 (D3) and on last day of treatment (DL). Descriptive statistics were used to describe demographic data. Pearson Chi-square was used for all categorical data. The Independent T-test was applied to compare mean pain score with two categorical variables. One-way analysis of variance (ANOVA) was used to compare mean pain score with categorical variables of more than 2 groups. For the cost of medications taken by patients during their hospitalization, Spearman's Rho Correlation Coefficient was used to see the correlation between drug costs and pain score with other numerical variables. Repeated Measure ANOVA was used to investigate the pattern or changes in pain score from day 1(D1) to last day of treatment (DL) in different categorical variables. Mean and standard deviations value for Sensory and Affective Descriptors was also calculated. A p value of <0.05 was considered statistically significant with a confidence interval of 95%. Results: This study found that the mean difference between the 3 days after operation was significantly different (p <0.001). The mean pain score was 6:52 ±2:18 on Dl, 3.72 ± 1.69 on D3 and 0.93 ± 0.85 on DL of treatment respectively. There were no significant difference in total pain score between male (133.37± 93.23) and female patients (158.94± 77.20). Further analysis with Repeated Measure ANOVA found a significant reduction (p<0.05) of pain score between male and female (p=0.0109) on Dl to DL. There was a significant reduction (p<0.05) of pain score between duration of treatment (p=0.016) on Dl to DL. There was also a low, positive correlation between Analgesia Drug Cost and Patients' Pain Score(r = 0.311, n = 102, P = 0.001), Analgesia Cost and Duration of Treatment (r = 0.468, n = 102, P - < 0.001) and Analgesia Cost and Duration of Operation (r = 0.383, n = 102, P = < 0.001). Conclusions: This study found that there was a significant reduction in pain levels of patients from Dl to DL after surgery. This illustrates that the use of proper medication can produce positive outcome. The selection of appropriate drugs is important to ensure the effectiveness of treatment, to achieve patient satisfaction and to reduce side effects of drugs and complications after surgery.
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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 | 0.001 | 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".