OILMAP and ArcGIS provide qualitative validation of USCG Sector Geographic Response Strategies

With the promulgation of the Coast Guard's requirement for Geographic Response Strategies (GRS) Tiered Validation levels, oil spill modeling transitioned from being a reactive tool to a predictive instrument that can guide the placement of limited mission critical resources (boom, boats, personnel, skimmers, etc.) based on threats from current or forecasted operations. In collaboration with the RPS Group, the Coast Guard's Sector Delaware Bay and District Five, members of the Coast Guard Academy employed the OILMAP Oil Spill Modelling Program with ArcGIS to test and validate operational Area Contingency Plan's (ACP) Geographic Response Strategies (GRS). OILMAP is a rapid and effective modelling system that allows for accurate observation of oil movement and weathering. The scenarios were manipulated to effectively test the booming strategies currently in place and worst-case winds at 5 and 10 knots were utilized. The project also identified discrepancies with projected strategies due to changes in the environment. In subsequent studies, the OILMAP output layers of shoreline oiling and oil particle location were combined with the publicly available Environmental Sensitivity Index (ESI) shoreline data to quantify the impact of booming strategies. The success observed in both the qualitative and quantitative analysis show great promise in the future of establishing a methodology to optimize booming strategies based on data-driven scenarios tailored to each unique spill, season and weather condition.

High NEMO score values in nailfold videocapillaroscopy are predictive of future development of ischemic digital ulcers in patients with systemic sclerosis

BackgroundNailfold videocapillaroscopy (NVC) is a feasible method that allows the observation of the microvascular changes that mark the course of systemic sclerosis (SSc). In previous studies we demonstrated that the NEMO score, i.e., the cumulative number of microhaemorrhages and microthromboses, is a good indicator of the steady state level and overtime changes of disease activity (DA) in SSc.ObjectivesTo verify whether high NEMO scores, which mirror a very active microvascular derangement in the fingers, may predict the subsequent development of ischemic digital ulcers (IDUs).Methods The NEMO score was assessed at baseline (T0) in 98 patients with SSc, all classified according to the ACR-EULAR criteria. Of them, 90 were females, 48 had the limited and 50 the diffuse cutaneous variant of SSc. Afterwards, the patients were closely followed up for two years, and the appearance of new IDUs recorded at any time of the follow up.The T0-NEMO score values of patients who developed IDUs were compared to those of patients who did not. A receiver operating curve (ROC) was constructed, and the area under the curve (AUC) calculated by plotting the sensitivity and 1-specificity of the different NEMO score values in predicting the subsequent development of IDUs.Results During the follow-up 38 out of 98 patients developed one or more IDUs. The NEMO score at T0 was significantly higher in those who developed IDUs with respect to those who did not [median 14.5 (95%CI 11.0-21.5), and 4.5 (95%CI 4.0-6.0), respectively, p<.0001]. The ROC curve derived from different T0-NEMO score values had an AUC of 0.79 (95%CI 0.69-0.86, p<0.0001)]. A NEMO score of ≥12 had a sensitivity of 83.3% (95%CI 71.5-91.7), and a specificity of 63.2% (95%CI 46.0-78.2), with positive (P) and negative (N) predictive (PV) values of 58.9% (95%CI 44.7-72.2), and 85.6% (71.8-94.4), respectively. A NEMO score of ≥16 had a sensitivity of 95.0% (95%CI 86.1-99.0), and a NPV of 93.4% (77.5-99.2).ConclusionsBeing a valid tool to measure DA levels in SSc, the NEMO score also appears to be good predictive instrument to predict future development of IDUs in this disease.

An example of medical device-based projection of clinical trial enrollment: Use of electrocardiographic data to identify candidates for a trial in acute coronary syndromes

Background:To identify potential participants for clinical trials, electronic health records (EHRs) are searched at potential sites. As an alternative, we investigated using medical devices used for real-time diagnostic decisions for trial enrollment.Methods:To project cohorts for a trial in acute coronary syndromes (ACS), we used electrocardiograph-based algorithms that identify ACS or ST elevation myocardial infarction (STEMI) that prompt clinicians to offer patients trial enrollment. We searched six hospitals’ electrocardiograph systems for electrocardiograms (ECGs) meeting the planned trial’s enrollment criterion: ECGs with STEMI or > 75% probability of ACS by the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI). We revised the ACI-TIPI regression to require only data directly from the electrocardiograph, the e-ACI-TIPI using the same data used for the original ACI-TIPI (development set n = 3,453; test set n = 2,315). We also tested both on data from emergency department electrocardiographs from across the US (n = 8,556). We then used ACI-TIPI and e-ACI-TIPI to identify potential cohorts for the ACS trial and compared performance to cohorts from EHR data at the hospitals.Results:Receiver-operating characteristic (ROC) curve areas on the test set were excellent, 0.89 for ACI-TIPI and 0.84 for the e-ACI-TIPI, as was calibration. On the national electrocardiographic database, ROC areas were 0.78 and 0.69, respectively, and with very good calibration. When tested for detection of patients with > 75% ACS probability, both electrocardiograph-based methods identified eligible patients well, and better than did EHRs.Conclusion:Using data from medical devices such as electrocardiographs may provide accurate projections of available cohorts for clinical trials.