Balavenkatesh Kanna

Predicting performance using background characteristics of international medical graduates in an inner-city university-affiliated Internal Medicine residency training program

BackgroundIMGs constitute about a third of the United States (US) internal medicine graduates. US residency training programs face challenges in selection of IMGs with varied background features. However data on this topic is limited. We analyzed whether any pre-selection characteristics of IMG residents in our internal medicine program are associated with selected outcomes, namely competency based evaluation, examination performance and success in acquiring fellowship positions after graduation.MethodsWe conducted a retrospective study of 51 IMGs at our ACGME accredited teaching institution between 2004 and 2007. Background resident features namely age, gender, self-reported ethnicity, time between medical school graduation to residency (pre-hire time), USMLE step I & II clinical skills scores, pre-GME clinical experience, US externship and interest in pursuing fellowship after graduation expressed in their personal statements were noted. Data on competency-based evaluations, in-service exam scores, research presentation and publications, fellowship pursuance were collected. There were no fellowships offered in our hospital in this study period. Background features were compared between resident groups according to following outcomes: (a) annual aggregate graduate PGY-level specific competency-based evaluation (CBE) score above versus below the median score within our program (scoring scale of 1 – 10), (b) US graduate PGY-level specific resident in-training exam (ITE) score higher versus lower than the median score, and (c) those who succeeded to secure a fellowship within the study period. Using appropriate statistical tests & adjusted regression analysis, odds ratio with 95% confidence intervals were calculated.Results94% of the study sample were IMGs; median age was 35 years (Inter-Quartile range 25th – 75th percentile (IQR): 33–37 years); 43% women and 59% were Asian physicians. The median pre-hire time was 5 years (IQR: 4–7 years) and USMLE step I & step II clinical skills scores were 85 (IQR: 80–88) & 82 (IQR: 79–87) respectively. The median aggregate CBE scores during training were: PG1 5.8 (IQR: 5.6–6.3); PG2 6.3 (IQR 6–6.8) & PG3 6.7 (IQR: 6.7 – 7.1). 25% of our residents scored consistently above US national median ITE scores in all 3 years of training and 16% pursued a fellowship.Younger residents had higher aggregate annual CBE score than the program median (p < 0.05). Higher USMLE scores were associated with higher than US median ITE scores, reflecting exam-taking skills. Success in acquiring a fellowship was associated with consistent fellowship interest (p < 0.05) and research publications or presentations (p <0.05). None of the other characteristics including visa status were associated with the outcomes.ConclusionBackground IMG features namely, age and USMLE scores predict performance evaluation and in-training examination scores during residency training. In addition enhanced research activities during residency training could facilitate fellowship goals among interested IMGs.

Ethnic disparity in mortality after diagnosis of colorectal cancer among inner city minority New Yorkers

Ethnic disparities in colorectal cancer (CRC) mortality are observed in the United States. The authors studied this among minority New Yorkers with CRC.

Giant J Wave on 12-Lead Electrocardiogram in Hypothermia

Findings on standard 12‐lead electrocardiogram in patients with hypothermia include sinus bradycardia, prolonged QT and PR interval, wide QRS complex, supraventricular and ventricular arrhythmia, and the most striking electrocardiographic abnormality, the J wave. Although characteristic of hypothermia, J wave also occurs in other conditions. The electro‐physiologic basis of J wave in hypothermia has been recently elucidated. We present a case of giant J wave due to accidental hypothermia and in addition discuss the features, mechanism, and significance of J wave in hypothermia.          A.N.E. 2003; 8(3):262‐265

Efficacy and Safety of Inhaled Insulin Therapy

TO THE EDITOR: The study by Rosenstock and colleagues (1) included patients with type 2 diabetes who had a wide range of body mass index (BMI) measurements. In patients with type 2 diabetes, obesity is associated with poor treatment response to insulin (2). Because higher BMI may be a potential confounder of the studys primary outcome (change in hemoglobin A1c level from baseline), we recommend an analysis that is based on predefined BMI strata to distinguish the effects of inhaled insulin among patients of various body types. In addition, analysis of the confounding effects of dietary restriction and exercise regimens on diabetes control is necessary. As in any open-label study, performance and observation biases of the investigators and the unblinded patients who received the new inhaled insulin treatment may substantially affect outcome measurements (3). Furthermore, mean outcome hemoglobin A1c levels are affected by outlying measurements that can increase error rates and cause alteration of estimates in statistical testing (4). Therefore, readers would benefit from knowing the distribution of the hemoglobin A1c levels of the study groups before and after treatment.

Data analysis and interpretation of results in DATAS trial

Regarding the DATAS randomized study by Almendral et al. , 1 we would like to comment on methodological issues that may limit the validity of the results of this trial. The investigators have created clinically significant adverse events (CSAEs) scoring system2 based on assigning arbitrary weights to actual events that may artificially change the value of the analysed events, …