We describe a most straightforward synthetic method for preparing neurokinin‐1 (NK1) receptor antagonist derivatives by asymmetric hydrogenation of 3‐amido‐2‐arylpyridinium salts using dinuclear iridium complexes with enantiopure diphosphine ligands, affording the corresponding chiral piperidines in high cis‐diastereoselectivity (>95:5) and moderately high enantioselectivity (up to 86%). Deprotection treatments afforded the NK‐1 receptor antagonist (+)‐CP‐99,994 (83% ee). In addition, we observed unique additive effects of 10‐camphorsulfonic acid in the asymmetric hydrogenation of 3‐amido‐2‐arylpyridinium salts.

Background Patients in general medical-surgical wards who experience unplanned transfer to the intensive care unit (ICU) show evidence of physiologic derangement 6–24 h prior to their deterioration. With increasing availability of electronic medical records (EMRs), automated early warning scores (EWSs) are becoming feasible. Objective To describe the development and performance of an automated EWS based on EMR data. Materials and methods We used a discrete-time logistic regression model to obtain an hourly risk score to predict unplanned transfer to the ICU within the next 12 h. The model was based on hospitalization episodes from all adult patients (18 years) admitted to 21 Kaiser Permanente Northern California (KPNC) hospitals from 1/1/2010 to 12/31/2013. Eligible patients met these entry criteria: initial hospitalization occurred at a KPNC hospital; the hospitalization was not for childbirth; and the EMR had been operational at the hospital for at least 3 months. We evaluated the performance of this risk score, called Advanced Alert Monitor (AAM) and compared it against two other EWSs (eCART and NEWS) in terms of their sensitivity, specificity, negative predictive value, positive predictive value, and area under the receiver operator characteristic curve (c statistic). Results A total of 649,418 hospitalization episodes involving 374,838 patients met inclusion criteria, with 19,153 of the episodes experiencing at least one outcome. The analysis data set had 48,723,248 hourly observations. Predictors included physiologic data (laboratory tests and vital signs); neurological status; severity of illness and longitudinal comorbidity indices; care directives; and health services indicators (e.g. elapsed length of stay). AAM showed better performance compared to NEWS and eCART in all the metrics and prediction intervals. The AAM AUC was 0.82 compared to 0.79 and 0.76 for eCART and NEWS, respectively. Using a threshold that generated 1 alert per day in a unit with a patient census of 35, the sensitivity of AAM was 49% (95% CI: 47.6–50.3%) compared to the sensitivities of eCART and NEWS scores of 44% (42.3–45.1) and 40% (38.2–40.9), respectively. For all three scores, about half of alerts occurred within 12 h of the event, and almost two thirds within 24 h of the event. Conclusion The AAM score is an example of a score that takes advantage of multiple data streams now available in modern EMRs. It highlights the ability to harness complex algorithms to maximize signal extraction. The main challenge in the future is to develop detection approaches for patients in whom data are sparser because their baseline risk is lower.

BACKGROUND: Adherence to evidence-based recommendations for acute myocardial infarction (AMI) remains unsatisfactory.

Objective: The objective of this study is to determine the prevalence of placenta previa among different racial and ethnic groups.Study Design: We conducted a retrospective cohort study to examine the prevalence of placenta previa among five major racial and ethnic groups: African American, Asian, Caucasian, Hispanic and Native American. We included all deliveries X20 weeks gestation from a large northern Californian Health Maintenance Organization from 1995-2006. A multivariable logistic regression model was used to control for potential confounders.Result: Of the 394 083 deliveries in our cohort, 1580 (0.40%) were complicated by placenta previa. The prevalence of placenta previa was: Asian 0.64%, Native American 0.60%, African American 0.44%, Caucasian 0.36%, Hispanic 0.34% and unknown 0.31% (P<0.001). In our multivariable logistic regression model, only Asians (odds ratio (OR) 1.73, 95% confidence intervals (CI) 1.53-1.95) and African Americans (OR 1.43, 95% CI 1.19-1.72) were at increased risk for having placenta previa, compared with Caucasians. Conclusion:Asian women have the highest prevalence of placenta previa.

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