Dataset Information

Autologistic models for benchmark risk or vulnerability assessment of urban terrorism outcomes.

ABSTRACT: We develop a quantitative methodology to characterize vulnerability among 132 U.S. urban centers ('cities') to terrorist events, applying a place-based vulnerability index to a database of terrorist incidents and related human casualties. A centered autologistic regression model is employed to relate urban vulnerability to terrorist outcomes and also to adjust for autocorrelation in the geospatial data. Risk-analytic 'benchmark' techniques are then incorporated into the modeling framework, wherein levels of high and low urban vulnerability to terrorism are identified. This new, translational adaptation of the risk-benchmark approach, including its ability to account for geospatial autocorrelation, is seen to operate quite flexibly in this socio-geographic setting.

SUBMITTER: Liu J

PROVIDER: S-EPMC5994772 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Autologistic models for benchmark risk or vulnerability assessment of urban terrorism outcomes.

Liu Jingyu J Piegorsch Walter W WW Schissler A Grant AG Cutter Susan L SL

Journal of the Royal Statistical Society. Series A, (Statistics in Society) 20171010 3

We develop a quantitative methodology to characterize vulnerability among 132 U.S. urban centers ('cities') to terrorist events, applying a place-based vulnerability index to a database of terrorist incidents and related human casualties. A centered autologistic regression model is employed to relate urban vulnerability to terrorist outcomes and also to adjust for autocorrelation in the geospatial data. Risk-analytic 'benchmark' techniques are then incorporated into the modeling framework, where ...[more]

PMID: 29904240

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Project description:BACKGROUND:Two large, randomized trials are underway evaluating transcatheter aortic valve replacement (AVR) against conventional surgical AVR. We analyzed contemporary, real-world outcomes of surgical AVR in low-risk patients to provide a practical benchmark of outcomes and cost for evaluating current and future transapical AVR technology. METHODS:From 2010 to 2015, 2,505 isolated AVR operations were performed for severe aortic stenosis at 18 statewide cardiac institutions. Of these, 2,138 patients had a Society of Thoracic Surgeons predicted risk of mortality of less than 4%, and 1,119 met other clinical and hemodynamic criteria as outlined in the PARTNER 3 (The Placement of Transcatheter Aortic Valves) protocol. Patients with endocarditis, end-stage renal disease, ejection fraction of less than 0.45, bicuspid valves, and previous valve replacements were excluded. Outcomes of interest included operative death and postoperative adverse events. RESULTS:The median Society of Thoracic Surgeons predicted risk of mortality for the study-eligible patients was 1.44%, with a median age of 72 years (interquartile range [IQR], 65 to 78 years). Operative mortality was 1.3%, permanent stroke was 1.3%, and pacemaker requirement was 4.2%. The most common adverse events were transfusion of 2 or more units of red blood cells (18%) and atrial fibrillation (28%). The median length of stay was 6 days (IQR, 5 to 8 days). Median total hospital cost was $37,999 (IQR, $30,671 to $46,138). Examination of complications by age younger than 65 vs 65 or older demonstrated a significantly lower need for transfusion (11.2%, p < 0.001) and incidence of atrial fibrillation (17.1%, p < 0.001) but no difference in operative mortality (2.2% vs 0.9%, p = 0.1), major morbidity (10.4% vs 12.6%, p = 0.3), or total hospital costs. CONCLUSIONS:Low-risk patients undergoing surgical AVR in the current era have excellent results. The most common complications were atrial fibrillation and bleeding. These real-world results should provide additional context for upcoming transcatheter clinical trial data.

Dataset Information

Autologistic models for benchmark risk or vulnerability assessment of urban terrorism outcomes.

Publications

Autologistic models for benchmark risk or vulnerability assessment of urban terrorism outcomes.

Similar Datasets

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