| Literature DB >> 30194469 |
Lukas Berglund1, Anders Stålman2, Elisabeth Dungner3, Abdul Rashid Qureshi4, Maritha Kumlin3, Li Felländer-Tsai3.
Abstract
PURPOSE: Factors associated with post-surgical pain are not fully explored. The aim of this study was to identify determinants of postoperative pain after arthroscopic surgery of the knee. Synovial tissue metabolism was analysed by microdialysis and the association with individual and peri-surgical factors to identify determinants important for pain management and thus patient satisfaction.Entities:
Keywords: Arthroscopy; Forecasting; Glucose; Glycerol; Microdialysis; Pain; Postoperative; Prostaglandins E; Synovial membrane; Visual analogue scale
Mesh:
Substances:
Year: 2018 PMID: 30194469 PMCID: PMC6394548 DOI: 10.1007/s00167-018-5125-x
Source DB: PubMed Journal: Knee Surg Sports Traumatol Arthrosc ISSN: 0942-2056 Impact factor: 4.342
Baseline characteristics of the study population
| Variables | Rescue medication with opioids (RM) ( | No rescue medication with opioids (NRM) ( | |
|---|---|---|---|
| Age (years) | 29 (18–40) | 41 (18–58) | 0.04* |
| Female, | 5 (50) | 17 (36) | n.s |
| Height (cm) | 174 (165–190) | 178 (162–188) | n.s |
| Weight (kg) | 71 (64–87) | 82 (64–106) | 0.02* |
| Body mass index (kg/m2) | 24 (22–29) | 26 (21–34) | 0.04* |
| Operating time (min) | 39 (16–108) | 34 (20–138) | n.s |
| ACL/arthroscopy, | 2/8 (20) | 14/33 (30) | n.s |
| Tourniquet, yes/no, | 2/8 (20) | 18/29 (38) | n.s |
| Cryo cuff, yes/no, | 2/8 (20) | 14/33 (42) | n.s |
| Osteoarthritis, yes/no, | 2/8 (20) | 17/30 (36) | n.s |
| Smoking, yes/no, | 5/5 (50) | 7/40 (15) | 0.02* |
Continuous variables are presented as median (10–90 percentiles). Categorical variables are presented as percentage
Statistical significance (*) was set at the level of p < 0.05. Patients with rescue medication were significantly younger (p = 0.04), with a lower body weight (p = 0.02), a lower BMI (p = 0.04) and a higher frequency of smoking (p = 0.02)
Fig. 1Microdialysis procedure timeline
Fig. 2Patient flowchart
Fig. 3Correlation analysis between pain (VAS), duration of surgery (operation time min), PGE2, glucose and glycerol. There was a significant correlation between pain (VAS) and duration of surgery (p = 0.007), but no significant correlations between PGE2, glucose or glycerol and VAS
Significant predictors of pain in a multinomial logistic regression (n = 57). Pseudo r2 = 0.24; p = 0.003
| Parameter | Estimate | Standard error | |
|---|---|---|---|
| Presence of smoking | − 1.34 | 0.54 | 0.01* |
| Gender (female vs male) | 0.70 | 0.49 | n.s |
| 1-SD increase of age (years) | − 1.63 | 0.73 | 0.02* |
| 1-SD increase of BMI (kg/m2) | − 0.62 | 0.71 | n.s |
Statistical significance (*) was set at the level of p < 0.05. Results show the added predictive value of using 1-SD increase of age (p = 0.02), and smoking (p = 0.01)
Fig. 4Difference in PGE2 between NRM group (without opioids) and RM group (with opioids) over time. Statistical significance (*) was set at the level of p < 0.05. The visual difference that can be noted between the curves of the RM and NRM groups failed to reach statistical significance. However, there is a statistically significant decline of PGE2 levels between 40 min and 120–240 min in both groups post-surgery