Author:
Allen Robert H.,Islam Rushnan,Sant’Anna Marhino Caio,Allen Edith Gurewitsch
Abstract
Objective
The aim of the study is to determine diagnostic traction for shoulder dystocia and to assess whether applied traction is modifiable with force training.
Methods
We tethered a force-measuring fetal mannequin (PROMPT, Limbs & Things) within a simulated pelvis such that it would not deliver. We asked participants to apply traction to diagnose shoulder dystocia then stop. Blinded from participants’ view, we recorded the peak traction. We then asked them to apply what they perceived to be 20 lb (89 N) traction. Each participant estimated the traction s/he applied. The actual force applied was then revealed to the participants and another blinded sequence was performed. We then allowed participants to view actual force measurements in real time while they practiced getting to their diagnostic traction and to 20 lb (89 N); this was followed by another blinded sequence of traction applications and estimations. Median diagnostic traction and injury threshold values (20 lb [89 N]), and mean ratio of estimated to actual force applied were compared pretraining and posttraining, using Wilcoxon signed rank sum test and t test. Rates of clinical shoulder dystocia and associated brachial plexus injury before and after the study period were compared using chi-square. Significance was set at P < 0.05.
Results
One hundred participants demonstrated a range of diagnostic traction. For 23 participants, traction exceeded injury thresholds, but the average was lowered with training. Before training, participants underestimated their own applied traction by an average of 30%.
Conclusions
Subjective diagnosis of shoulder dystocia during simulation training varies widely and exceeds possible injury threshold for 22% of participants. Accuracy of self-assessment applied delivery traction improves significantly with force training as does clinical diagnosis of shoulder dystocia and decrease in brachial plexus injury incidence.
Publisher
Ovid Technologies (Wolters Kluwer Health)