Development and Evaluation of a Score to Predict Difficult Epidural Placement During Labor. Issue 3 (1st May 2013) - Guglielminotti, Jean; Mentré, France; Bedairia, Ennoufous; Montravers, Philippe; Longrois, Dan
Abstract : Background and Objectives: Difficult epidural placement (DEP) during labor may be distressing for the patient and may increase the risk of dural puncture. A score predicting DEP based on the combination of individual risk factors could identify high-risk patients. This study aimed to identify risk factors for DEP and build a prediction score. Methods: Three hundred thirty patients were prospectively included. Difficult epidural placement was defined as more than 1 skin puncture with a Tuohy needle. Dura puncture occurrence was recorded. The population was randomly split into a training set and a validation set. In the training set, risk factors were identified with logistic regression and used to build a score defining 3 risk groups. Model and score discrimination was assessed with the C-index and clinical usefulness of the score with decision curves. Results: Difficult epidural placement frequency was 30% (95% confidence interval [95% CI], 25%–35%). Dural puncture was more frequent in DEP patients (4% vs 0%, P = 0.007). Three independent risk factors for DEP were identified: difficult interspinous space palpation (odds ratio [OR], 6.1; 95% CI, 2.8–13.9), spinal deformity (OR, 2.4; 95% CI, 1.1–5.3), and inability to flex the back (OR, 3.0; 95% CI, 1.2–7.8). The C-index of the model was 0.81 (95% CI, 0.74–0.88) in the training set and 0.78 (95% CI, 0.70–0.86) in the validation set. A 5-point score was created to define groups with low risk (score 0), intermediate risk (score 1–2), and high risk (score 3–4), with predicted rates of DEP of 9.7%, 30.3%, and 68.9%, respectively. The C-index of the score was 0.79 (95% CI, 0.72–0.86) in the training set and 0.76 (95% CI, 0.69–0.84) in the validation set. Decision curves support the clinical usefulness of the score. Conclusions: This study confirms risk factors for DEP and proposes a score to predict DEP. The score identifies high-risk patients who may benefit from an intervention to decrease DEP. This hypothesis should be evaluated in an impact study.