Quantitative Methods for Improving Medical Decision-Making

Innovation in causal inference and implementation of electronic health record systems are rapidly transforming medical care. In this dissertation, we present three examples in which use of methods in causal inference and large electronic health record data address existign challenges in medical decision-making. First, we use principles of causal inference to examine the structure of randomized trials of biomarker targets, which have produced divergent results and controversial clinical guidelines for management of hypertension and other chronic diseases. We discuss four key threats to the validity of trials of this design. Second, we use methods in causal inference for adjustment of time-varying confounding to estimate the effect of time-varying treatment strategies for hypertension. We report the results of a study which used longitudinal electronic health record data from a prospective virtual cohort of veterans. Third, we use individual-level electronic health record data to predict the need for critical care resources during surges in COVID-19 cases, to aid hospital administrators with resource allocation in periods of crisis

Postantibiotic effects with Bacteroides fragilis determined by viable counts and CO2 generation

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldOBJECTIVE: To study the postantibiotic effect (PAE) for Bacteroides fragilis after exposure to common anaerobic antimicrobials with two different methods, by viable counting and by measuring CO2 generation in a BACTEC(R) blood culture system. METHODS: Four strains of B. fragilis were exposed for 1, 2 and 4 h to cefoxitin, chloramphenicol, clindamycin, imipenem or metronidazole at concentrations from 1 to 16 x MIC. The drugs were removed by dilution into BACTEC 7A(R) vials and growth determined with viability counts and CO2 production. RESULTS: The durations of the PAEs determined by the two methods correlated well (r=0.913, p<0.005). PAEs of up to 4-5 h were induced by imipenem and metronidazole with achievable concentrations and exposure durations. Chloramphenicol induced short or no PAEs, but cefoxitin and clindamycin induced PAEs up to 2 h with high AUC values. The imipenem PAEs and the short cefoxitin and clindamycin PAEs were dependent on AUC. CONCLUSIONS: Significant PAEs against B. fragilis were induced by imipenem and metronidazole. Determining PAE by measuring CO2 production is an accurate and less time-consuming alternative to the conventional method of viable counts

Discriminable spatial patterns of activation for faces and bodies in the fusiform gyrus

Functional neuroimaging studies consistently report that the visual perception of faces and bodies strongly activates regions within ventral occipitotemporal cortex (VOTC) and, in particular, within the mid-lateral fusiform gyrus. One unresolved issue is the degree to which face and bodies activate discrete or overlapping cortical regions within this region. Here, we examined VOTC activity to faces and bodies at high spatial resolution, using univariate and multivariate analysis approaches sensitive to differences in both the strength and spatial pattern of activation. Faces and bodies evoked substantially overlapping activations in the fusiform gyrus when each was compared to the control category of houses. No discrete regions of activation for faces and bodies in the fusiform gyrus survived a direct statistical comparison using standard univariate statistics.However, multi-voxel pattern analysis differentiated faces and bodies in regions where univariate analysis found no significant difference in the strength of activation. Using a whole-brain multivariate searchlight approach, we also found that extensive regions in VOTC beyond those defined as fusiform face and body areas using standard criteria where the spatial pattern of activation discriminated faces and bodies. These findings provide insights into the spatial distribution of face- and body-specific activations in VOTC and the identification of functionally specialized regions