Screening Tool Predicted Pain After C-Section


From the Annual Meeting of the Society for Obstetric Anesthesia and Perinatology

Major Finding: A 1-minute, 3-question screening tool predicted individuals in the top 20th percentile of pain scores, with a sensitivity of 67% and a specificity of 72%.

Data Source: Study of 192 women who underwent elective C-sections with spinal morphine.

Disclosures: None was reported.

SAN ANTONIO — A 1-minute, three-question screening tool accurately predicted post–cesarean section pain in a study of 192 women who underwent elective cesarean sections with spinal morphine.

The quick, simple screen was nearly as sensitive and specific in predicting pain after delivery as was a 120-minute battery of tests used in a previous study (Anesthesiology 2006;104:417-25).

“We were looking for a simple, clinically useful way to identify patients at high risk for severe acute pain and subsequent complications who might benefit from earlier intervention,” said Dr. Ashley M. Tonidandel of Wake Forest University, Winston-Salem, N.C.

The three screening questions that were used in the investigation addressed the three strongest independent predictors of postcesarean pain and narcotic usage identified in the study published in Anesthesiology and in another study (Clin. J. Pain 2009;25:455-60).

Those predictors were anticipated pain levelafollowing surgery (on a scale of 0-100), anxiety regarding the upcoming surgery (1-100), and estimated pain medication usage (much less to much more than average).

The study participants had a mean age of 30 years and a mean body mass index of 34 kg/m

At 24 hours following surgery, the mean evoked pain score was 44 (out of 100). The patients used an average of 19 morphine equivalents over 24 hours. More than half of the participants (54%) received a total of 200 mcg of spinal morphine, according to Dr. Tonidandel.

Anxiety, anticipated pain, and expected medication usage were all significantly related to evoked pain and 24-hour morphine equivalents, with high scores on any two of the three items significantly predicting high pain scores.

Overall, the model accounted for 22% of the variance in predicted pain scores, which is “pretty good considering the 22%-28% of variance from the 120-minute battery of questions,” Dr. Tonidandel commented at the meeting.

Using a regression equation, the screening tool predicted individuals in the top 20th percentile of pain scores with a sensitivity of 67% and a specificity of 72%. With the 120-minute screen, those values were 70% and 76%, respectively, she said.

Identifying women at high risk for severe postpartum pain is especially important because previous studies have shown that women who have it are in turn at greater risk for the development of chronic pain (Pain 2008;140:87-94).

In the future, adding genetic information to the model might further increase its accuracy, although “our aim was to simplify,” she said.

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