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BackgroundTransfusion-related acute lung injury (TRALI) and transfusion-associated circulatory overload (TACO) are leading causes of transfusion-related mortality. Notably, poor syndrome recognition and underreporting likely result in an underestimate of their true attributable burden. We aimed to develop accurate electronic health record-based screening algorithms for improved detection of TRALI/transfused acute lung injury (ALI) and TACO.Study design and methodsThis was a retrospective observational study. The study cohort, identified from a previous National Institutes of Health-sponsored prospective investigation, included 223 transfused patients with TRALI, transfused ALI, TACO, or complication-free controls. Optimal case detection algorithms were identified using classification and regression tree (CART) analyses. Algorithm performance was evaluated with sensitivities, specificities, likelihood ratios, and overall misclassification rates.ResultsFor TRALI/transfused ALI detection, CART analysis achieved a sensitivity and specificity of 83.9% (95% confidence interval [CI], 74.4%-90.4%) and 89.7% (95% CI, 80.3%-95.2%), respectively. For TACO, the sensitivity and specificity were 86.5% (95% CI, 73.6%-94.0%) and 92.3% (95% CI, 83.4%-96.8%), respectively. Reduced PaO2 /FiO2 ratios and the acquisition of posttransfusion chest radiographs were the primary determinants of case versus control status for both syndromes. Of true-positive cases identified using the screening algorithms (TRALI/transfused ALI, n = 78; TACO, n = 45), only 11 (14.1%) and five (11.1%) were reported to the blood bank by physicians, respectively.ConclusionsElectronic screening algorithms have shown good sensitivity and specificity for identifying patients with TRALI/transfused ALI and TACO at our institution. This supports the notion that active electronic surveillance may improve case identification, thereby providing a more accurate understanding of TRALI/transfused ALI and TACO epidemiology.

Regression equations are presented for converting the non-K-corrected raw scores on the Minnesota Multiphasic Personality Inventory (MMPI) basic scales to an estimated optimism-pessimism score. This score describes an individual's explanatory style on a continuum from optimistic to pessimistic, These equations will enable clinicians and researchers to estimate an optimism-pessimism score if the MMPI item responses are not accessible or if computer scoring facilities for individual items are unavailable.

This article reports adolescent norms for the Optimism-Pessimism (PSM) scale of the Minnesota Multiphasic Personality Inventory (MMPI). The PSM scale measures explanatory style on a continuum from optimistic to pessimistic by using 298 MMPI items. It is based on Seligman's theory of explanatory style and was constructed by applying the Content Analysis of Verbatim Explanations (CAVE) technique to the MMPI item pool. The normative equations are based on a random sample of 624 normal boys and 691 normal girls ages 13 through 17 years. Reliability estimates of .94 demonstrate that the PSM scale can accurately assess explanatory style in adolescents. These norms may identify a personality factor associated with poorer physical and mental health and lower levels of achievement.

The Revised Optimism-Pessimism (PSM-R) scale permits researchers to use MMPI and MMP-2 tests to learn about the relationship between explanatory style and probable treatment results. Such a style is given a score between optimistic and pessimistic by using 263 MMPI items for the optimism-pessmism scale. Reliability estimates show that the PSM-R scale is as reliable as the original PSM scale. Norms are based on a random sample of adults.

The Common Alcoholic Logistic Revised Scale (CAL-R), which is developed to screen patients treated for alcoholism, can be used with both MMPI and MMPI-2. Tests of a criterion group of 1221 alcoholics and a contrast sample of 7621 non-alcoholic patients proved that CAL-R is as effective as CAL.

Experiments based on Seligman's attributional model indicate that persons who have a pessimistic approach to life need medical and mental health facilities. A bipolar MMPI Optimism-Pessimism (PSM) scale, following the Content Analysis of Verbatim Explanation (CAVE) technique, shows a high degree of consistency with Seligman's theory. This scale will help future research in exploring the relation between explanatory styles and various outcome variables.

Abstract Background Acute lung injury (ALI) is an example of a critical care syndrome with limited treatment options once the condition is fully established. Despite improved understanding of pathophysiology of ALI, the clinical impact has been limited to improvements in supportive treatment. On the other hand, little has been done on the prevention of ALI. Olmsted County, MN, geographically isolated from other urban areas offers the opportunity to study clinical pathogenesis of ALI in a search for potential prevention targets. Methods/Design In this population-based observational cohort study, the investigators identify patients at high risk of ALI using the prediction model applied within the first six hours of hospital admission. Using a validated system-wide electronic surveillance, Olmsted County patients at risk are followed until ALI, death or hospital discharge. Detailed in-hospital (second hit) exposures and meaningful short and long term outcomes (quality-adjusted survival) are compared between ALI cases and high risk controls matched by age, gender and probability of developing ALI. Time sensitive biospecimens are collected for collaborative research studies. Nested case control comparison of 500 patients who developed ALI with 500 matched controls will provide an adequate power to determine significant differences in common hospital exposures and outcomes between the two groups. Discussion This population-based observational cohort study will identify patients at high risk early in the course of disease, the burden of ALI in the community, and the potential targets for future prevention trials.