A One-Minute Screening Tool for Predicting Postcesarean Section Pain
Abstract Number: 67
Abstract Type: Original Research
Introduction: Severity of acute pain after delivery has been shown to independently predict persistent pain and depression up to 2 months after discharge.1 If high risk pts can be identified, aggressive management may prevent depressed mood, impaired bonding, poor sleep, and chronic pain in new mothers.1 Previous promising research has focused on experimental pain and psychological surveys that require additional resources to interpret.2 This study evaluates the ability of a 1-minute, 3-question screening tool to predict postcesarean pain.
Methods: Elective C/S pts completed an assessment battery including a 3-question screening tool asking them to rate their level of anticipated pain (0-100), anxiety regarding their upcoming surgery (0-100), and expected pain medication usage. These questions were chosen based on prior research suggesting the importance of state anxiety, expectations of analgesic requirements, and anticipated, rather than preexisting, pain in predicting pain and narcotic usage.2 Pain with movement was assessed at 24 hrs after surgery. The predictive value of the screening tool on evoked pain was determined using linear regression models.
Results: 192 parturients underwent elective C/S with spinal morphine (100-250mcg). Avg pain with movement at 24 hrs was 44(SD=26), and 24 hr morphine equivalents ranged from 0 to 98mg(Avg18.6, SD=20.8). Anxiety, anticipated pain, and expected medication usage were all significantly related to evoked pain and 24 hr morphine equivalents by zero-order correlations. The general linear model showed a significant main effect for anticipated pain, as well as significant 2 and 3-way interactions, suggesting the effect of anticipated pain depends on anxiety level and amount of predicted medication usage. The overall model was significant (p<.01) and accounted for 22% of the variance in evoked pain at 24 hrs. Using the regression equation, the screening tool can accurately predict individuals with the highest pain scores (top 20%) with a sensitivity of 67% and specificity of 72% (Fig 1).
Conclusion: These results suggest that a 1-minute, 3-question screening tool can effectively predict evoked pain scores following C/S. The derived formula can be used to help identify pts at risk for severe acute pain and subsequent complications who may benefit from earlier intervention. Additional research is ongoing to validate the screening tool in other surgical populations.