Neurosurgical procedures performed during residency in Europe-preliminary numbers and time trends.

作者: Martin N. Stienen , , Jiri Bartek , Marcus A. Czabanka , Christian F. Freyschlag

DOI: 10.1007/S00701-019-03888-3

关键词: Time trendsNeurosurgeryInterventional radiologyPostgraduate trainingBoard certificationConfidence intervalRelevant informationPreliminary analysisFamily medicineMedicine

摘要: Differences in the postgraduate training programs of neurosurgical residents are suspected throughout Europe. The influence working hour restrictions by European Working Time Directive (WTD) 2003/88/EC on number surgical procedures remains unclear. We designed a survey to collect information procedures, performed trainees during residency. This article reports preliminary data. An electronic was distributed among Association Neurosurgical Societies (EANS) member countries national delegates committee, as well members Young Neurosurgeons’ committee. EANS mailing list individual also used for distribution. All responses received between 04/2018 and 12/2018 were considered. From n = 180 received, 42 omitted responders still residency 58 relevant missing. final sample n = 80, with mean responder’s age 43.0 years (SD 8.6) 88.8% being male. Responses came from 16 countries; board certification years 1976–2018. numbers independently 511 (mean, 95% confidence interval (CI) 413–610), supervised 514 (95%CI 360–668) assisted 752 485–1019) More detailed specific procedure types reported article. Independently cranial outnumbered spinal (p < 0.006), adult pediatric (p < 0.001). There strong decrease caseload 1976 2018, performing average 65 cases less each calendar year increase (95% CI − 116 − 15, p = 0.012). Trainees graduating before introduction WTD participated more than those afterwards (mean 2797 vs. 1418, p = 0.005). analysis first 80 now provides reference frame that can be current future critically compare their own operative to. decline over time, after had exposure. open, we invite further neurosurgeons provide data order get even robust estimates.

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