Erik van Zwet
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5 records found
1
Enhancing feedback on performance measures
The difference in outlier detection using a binary versus continuous outcome funnel plot and implications for quality improvement
We suggest short range stiffness (SRS) at the elbow joint as an alternative diagnostic for EMG to assess cocontraction.Elbow SRS is compared between obstetric brachial plexus lesion (OBPL) patients and healthy subjects (cross-sectional study design). Seven controls (median 28. years) and five patients (median 31. years) isometrically flexed and extended the elbow at rest and three additional torques [2.1,. 4.3,. 6.4. N. m] while a fast stretch stimulus was applied. SRS was estimated in silico using a neuromechanical elbow model simulating the torque response from the imposed elbow angle.SRS was higher in patients (250. ±. 36. N. m/rad) than in controls (150. ±. 21. N. m/rad, p = 0.014), except for the rest condition. Higher elbow SRS suggested greater cocontraction in patients compared to controls. SRS is a promising mechanical alternative to assess cocontraction, which is a frequently encountered clinical problem in OBPL due to axonal misrouting.
Identification of risk factors in minimally invasive surgery
A prospective multicenter study
Background: Since the introduction of minimally invasive surgery (MIS), concerns for patient safety are more often brought to the attention. Knowledge about and awareness of patient safety risk factors are crucial in order to improve and enhance the surgical team, the environment, and finally surgical performance. The aim of this study was to identify and quantify patient safety risk factors in laparoscopic hysterectomy and to determine their influence on surgical outcomes. Methods: A prospective multicenter study was conducted from April 2014 to January 2016, participating gynecologists registered their performed laparoscopic hysterectomies (LHs). If deemed necessary, gynecologists could fill out a checklist with validated patient safety risk factors. Association between procedures with and without an occurred risk factor(s) and the surgical outcomes (blood loss, operative time, and complications) were assessed, using multivariate logistic regression and generalized estimation equations. Results: Eighty-five gynecologists participated in the study, registering a total of 2237 LHs. For 627(28 %) procedures, the checklist was entered (in total 920 items). The most reported risk factors were related to the surgeon (19.6 %), the surgical team (14.4 %), technology (16.6 %), and the patient (26.8 %). The procedures where a risk factor was registered had significantly less favorable outcomes, higher complication rate (10.5 vs. 4.8 % (p = 0.002), longer operative time [114 vs. 95 min (p < 0.001)], and more blood loss [110 vs. 168 mL (p = 0.047)], which was mainly due to the technological and patient-related risk factors. Conclusion: Technological incidents are the most important and clinically relevant risk factors affecting surgical outcomes of LH. Future improvements of MIS need to focus on this. As awareness of safety risk factors in MIS is important, embedding of a safety risk factor checklist in registration systems will help surgeons to evaluate and improve their individual performance. This will inherently improve the surgical outcomes and thus patient safety.