Optimal and/or Efficient Two treatment Crossover Designs for Five Carryover Models

Crossover designs robust to changes in carryover models are useful in clinical trials where the nature of carryover effects is not known in advance. The designs have been characterized for being optimal and efficient under no carryover-, traditional-, and, self and mixed carryover- models, however, ignoring the number of subjects, which has significant impact on both optimality and administrative convenience. In this article, adding two more practical models, the traditional, and, self and mixed carryover models having carryover effect only for the new or test treatment, a 5M algorithm is presented. The 5M algorithm based computer code searches all possible two treatment crossover designs under the five carryover models and list those which are optimal and /or efficient to all the five carryover models. The resultant exhaustive list consists of optimal and/or efficient crossover designs in two, three, and four periods, having 4 to 20 subjects of which 24 designs are new optimal for one of the established carryover models, and 34 designs are optimal for newly added models.

First Diagnosis of Atrial Fibrillation at the Time of Stroke

Background: Atrial fibrillation (AF) is a major cause of ischemic stroke. Individuals with undiagnosed AF lack the stroke protection afforded by oral anticoagulants. We obtained a contemporary estimate of the percentage of AF patients newly diagnosed at the time of stroke. Methods: We identified patients admitted to the Massachusetts General Hospital (MGH) from January 1, 2010 to December 31, 2013 with acute ischemic stroke and either previously or newly diagnosed AF using hospital stroke registry data and stroke and AF ICD-9 code searches of hospital databases. Reviewers categorized AF as previously known or newly diagnosed, and collected comorbidity and outcome data. To confirm AF as newly diagnosed, we searched patients' pre-event electronic medical records (EMRs) for AF terms. Results: AF was considered newly diagnosed in 156/856 patients (18%; 95% CI 16-21). In 136/156 cases, AF was diagnosed using 12-lead EKG, telemetry, or rhythm strips. New AF strokes had a median NIH stroke scale of 12; 60% had mRankin ≥3 at discharge, including 15% deaths. Pre-stroke CHA2DS2-VASc score was ≥2 in 89%. About half (76/156) had prior records in the MGH EMR. Evidence of pre-stroke AF, often peri-procedural, was found in 8/76, but the AF diagnosis was not carried forward. Conclusions: In this contemporary cohort, nearly one in 5 AF-related strokes occurred without a pre-stroke AF diagnosis. AF was readily diagnosed using standard rhythm monitoring. The vast majority of patients with newly diagnosed AF were at high enough pre-stroke risk to merit anticoagulation. In conclusion, our findings support screening for AF before stroke. Patients with past transient AF may merit more intensive screening.

Efficiency of International Classification of Diseases, Ninth Revision, Billing Code Searches to Identify Emergency Department Visits for Blood or Body Fluid Exposures through a Statewide Multicenter Database

Background.Blood and body fluid exposures are frequently evaluated in emergency departments (EDs). However, efficient and effective methods for estimating their incidence are not yet established.Objective.Evaluate the efficiency and accuracy of estimating statewide ED visits for blood or body fluid exposures using International Classification of Diseases, Ninth Revision (ICD-9), code searches.Design.Secondary analysis of a database of ED visits for blood or body fluid exposure.Setting.EDs of 11 civilian hospitals throughout Rhode Island from January 1, 1995, through June 30, 2001.Patients.Patients presenting to the ED for possible blood or body fluid exposure were included, as determined by prespecified ICD-9 codes.Methods.Positive predictive values (PPVs) were estimated to determine the ability of 10 ICD-9 codes to distinguish ED visits for blood or body fluid exposure from ED visits that were not for blood or body fluid exposure. Recursive partitioning was used to identify an optimal subset of ICD-9 codes for this purpose. Random-effects logistic regression modeling was used to examine variations in ICD-9 coding practices and styles across hospitals. Cluster analysis was used to assess whether the choice of ICD-9 codes was similar across hospitals.Results.The PPV for the original 10 ICD-9 codes was 74.4% (95% confidence interval [CI], 73.2%–75.7%), whereas the recursive partitioning analysis identified a subset of 5 ICD-9 codes with a PPV of 89.9% (95% CI, 88.9%–90.8%) and a misclassification rate of 10.1%. The ability, efficiency, and use of the ICD-9 codes to distinguish types of ED visits varied across hospitals.Conclusions.Although an accurate subset of ICD-9 codes could be identified, variations across hospitals related to hospital coding style, efficiency, and accuracy greatly affected estimates of the number of ED visits for blood or body fluid exposure.

Fast comparison of IS radar code sequences for lag profile inversion

A fast method for theoretically comparing the posteriori variances produced by different phase code sequences in incoherent scatter radar (ISR) experiments is introduced. Alternating codes of types 1 and 2 are known to be optimal for selected range resolutions, but the code sets are inconveniently long for many purposes like ground clutter estimation and in cases where coherent echoes from lower ionospheric layers are to be analyzed in addition to standard F-layer spectra. The method is used in practice for searching binary code quads that have estimation accuracy almost equal to that of much longer alternating code sets. Though the code sequences can consist of as few as four different transmission envelopes, the lag profile estimation variances are near to the theoretical minimum. Thus the short code sequence is equally good as a full cycle of alternating codes with the same pulse length and bit length. The short code groups cannot be directly decoded, but the decoding is done in connection with more computationally expensive lag profile inversion in data analysis. The actual code searches as well as the analysis and real data results from the found short code searches are explained in other papers sent to the same issue of this journal. We also discuss interesting subtle differences found between the different alternating codes by this method. We assume that thermal noise dominates the incoherent scatter signal.