Person:

Kosuri, Pallav

Background: Readmission rates for patients with heart failure (HF) remain high. Many efforts to identify patients at high risk for readmission focus on patient demographics or on measures taken in the hospital. We evaluated a method for risk assessment that depends on patient self-report following discharge from the hospital. Methods: In this study, we investigated whether automated calls could be used to identify patients who are at a higher risk of readmission within 30 days. An automated multi-call follow-up program was deployed with 1095 discharged HF patients. During each call, the patient reported his or her general health status. Patients were grouped by the trend of their responses over the two calls, and their unadjusted 30-day readmission rates were compared. Pearson’s chi-square test was used to evaluate whether readmission risk was independent of response trend. Results: Of the 1095 patients participating in the program, 837 (76%) responded to the general status question in at least one of the calls and 515 (47%) patients responded to the general status question in both calls. Out of the 89 patients exhibiting a negative response trend, 37% were readmitted. By contrast, the 97 patients showing a positive trend and the 329 patients showing a neutral trend were readmitted at rates of 16% and 14% respectively. The dependence of readmission on trend group was statistically significant (P < 0.0001). Conclusions: Patients at an elevated risk of readmission can be identified based on the trend of their responses to automated follow-up calls. This presents a simple method for risk stratification based on patient self-assessment.

Many genome-processing reactions, including transcription, replication and repair, generate DNA rotation. Methods that directly measure DNA rotation, such as rotor bead tracking angular optical trapping and magnetic tweezers, have helped to unravel the action mechanisms of a range of genome-processing enzymes that includes RNA polymerase (RNAP), gyrase2, a viral DNA packaging motor and DNA recombination enzymes8. Despite the potential of rotation measurements to transform our understanding of genome-processing reactions, measuring DNA rotation remains a difficult task. The time resolution of existing methods is insufficient for tracking the rotation induced by many enzymes under physiological conditions, and the measurement throughput is typically low. Here we introduce origami-rotor-based imaging and tracking (ORBIT), a method that uses fluorescently labelled DNA origami rotors to track DNA rotation at the single-molecule level with a time resolution of milliseconds. We used ORBIT to track the DNA rotations that result from unwinding by the RecBCD complex, a helicase that is involved in DNA repair9, as well as from transcription by RNAP. We characterized a series of events that occur during RecBCD-induced DNA unwinding—including initiation, processive translocation, pausing and backtracking—and revealed an initiation mechanism that involves reversible ATP-independent DNA unwinding and engagement of the RecB motor. During transcription by RNAP, we directly observed rotational steps that correspond to the unwinding of single base pairs. We envisage that ORBIT will enable studies of a wide range of interactions between proteins and DNA.