Pratik Bhattacharya

Background Survival after malignant middle cerebral artery infarcts is dismal. In 2007, a pooled analysis of randomised trials in Europe demonstrated a substantial survival benefit from decompressive hemicraniectomy, with a number needed to treat of 2 for survival. Our objective was to review factors driving the nationwide utilisation of this potentially lifesaving procedure in the USA. Methods Data from the Nationwide Inpatient Sample for 2001–2009 were reviewed. Hospitalisations with a discharge diagnosis of an acute ischaemic stroke were included. Hemicraniectomy utilisation was determined within this subset. Nationwide estimates of utilisation were calculated for each year. Trends across the years were estimated for various subgroups. Results From 2001 to 2009, there were an estimated 4 909 519 acute ischaemic stroke discharges. The estimated frequency of hemicraniectomy increased from 118 (0.02% of stroke discharges in 2001) to 804 (0.15% of stroke discharges in 2009) (trend pConclusion Utilisation of hemicraniectomy in the USA has increased significantly, in line with compelling results from European clinical trials. Early transfer of patients with malignant infarctions to urban teaching centres could potentially extend the survival benefit to a larger population.

Background: Use of resident case logs has been considered by the Residency Review Committee for Neurology of the Accreditation Council for Graduate Medical Education (ACGME). Objective: This study explores the effectiveness of a data-mining program for creating resident logs and compares the results to a manual data-entry system. Other potential applications of data mining to enhancing resident education are also explored. Design/Methods: Patient notes dictated by residents were extracted from the Hospital Information System and analyzed using an unstructured mining program. History, examination and ICD codes were obtained and compared to the existing manual log. The automated data History, examination, and ICD codes were gathered for a 30-day period and compared to manual case logs. Results: The automated method extracted all resident dictations with the dates of encounter and transcription. The automated data-miner processed information from all 19 residents, while only 4 residents logged manually. The manual method identified only broad categories of diseases; the major categories were stroke or vascular disorder 53 (27.6%), epilepsy 28 (14.7%), and pain syndromes 26 (13.5%). In the automated method, epilepsy 114 (21.1%), cerebral atherosclerosis 114 (21.1%), and headache 105 (19.4%) were the most frequent primary diagnoses, and headache 89 (16.5%), seizures 94 (17.4%), and low back pain 47 (9%) were the most common chief complaints. More detailed patient information such as tobacco use 227 (42%), alcohol use 205 (38%), and drug use 38 (7%) were extracted by the data-mining method. Conclusions: Manual case logs are time-consuming, provide limited information, and may be unpopular with residents. Data mining is a time-effective tool that may aid in the assessment of resident experience or the ACGME core competencies or in resident clinical research. More study of this method in larger numbers of residency programs is needed.