Lily Koffman- Master of Science
- PhD Candidate at Johns Hopkins Bloomberg School of Public Health
Lily Koffman
- Master of Science
- PhD Candidate at Johns Hopkins Bloomberg School of Public Health
PhD Candidate in Biostatistics at Johns Hopkins Bloomberg School of Public Health
About
15
Publications
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34
Citations
Current institution
Publications
Publications (15)
Purpose
To quantify the relative performance of step counting algorithms in studies that collect free-living high-resolution wrist accelerometry data and to highlight the implications of using these algorithms in translational research.
Methods
Five step counting algorithms (four open source and one proprietary) were applied to the publicly availa...
We consider the problem of predicting an individual’s identity from accelerometry data collected during walking. In a previous paper, we transformed the accelerometry time series into an image by constructing the joint distribution of the acceleration and lagged acceleration for a vector of lags. Predictors derived by partitioning this image into g...
BACKGROUND
Prior studies identified thresholds for mean arterial pressure (MAP <65 mm Hg) and central venous pressure (CVP >12 mm Hg) beyond which risk for cardiac surgery-associated acute kidney injury (AKI) increases. Optimal hemodynamic targets—that is, where active protection from AKI is observed—are unclear; however, current guidelines suggest...
Background
Step counting from wrist accelerometry data is widely used in physical activity research and practice. While several open-source algorithms can estimate steps from high-resolution accelerometry data, there is a critical need to compare these algorithms and provide practical recommendations for their use in older adults.
Methods
1,282 At...
Purpose: To quantify the relative performance of step counting algorithms in studies that collect free-living high-resolution wrist accelerometry data and to highlight the implications of using these algorithms in translational research. Methods: Five step counting algorithms (four open source and one proprietary) were applied to the publicly avail...
BACKGROUND
Continuous cardiac output monitoring is not standard practice during cardiac surgery, even though patients are at substantial risk for systemic hypoperfusion. Thus, the frequency of low cardiac output during cardiac surgery is unknown.
METHODS
We conducted a prospective cohort study at a tertiary medical center from July 2021 to Novembe...
Background : Walking-based metrics, including step count and total time walking, are easily interpretable measures of physical activity. Algorithms can estimate steps from accelerometry, which increasingly is measured with accelerometers located on the wrist. However, many existing step counting algorithms have not been validated in free-living set...
Background
Low physical activity (PA) is associated with poor health outcomes after stroke. Step counts are a common metric of PA; however, other physiologic signals (eg, heart rate) may help to identify subgroups of individuals poststroke at varying levels of risk of poor health outcomes. Here, we aimed to identify clinically relevant subgroups of...
Background
Toenails are a promising matrix for chronic metal exposure assessment, but there are currently no standard methods for collection and analysis. Questions remain about sample mass requirements and the extent to which metals measured in this matrix are representative of chronic body burden.
Objective
This study proposes a method to maximi...
Background:
Identifying an individual from accelerometry data collected during walking without reliance on step-cycle detection has not been achieved with high accuracy.
Research question:
We propose an open-source reproducible method to: (1) create a unique, person-specific "walking fingerprint" from a sample of un-landmarked high-resolution da...
Background
To determine the impact of an intensive perioperative nutritional and lifestyle support protocol on long-term outcomes of bariatric surgery.MethodsA retrospective observational study was conducted of 955 patients who underwent gastric bypass surgery between 2005 and 2015. Patients were divided into two cohorts: (1) 2005 through August 20...
PurposeMissing data is common in electronic health records (EHR)-based obesity research. To avoid bias, it is critical to understand mechanisms that underpin missingness. We conducted a survey among bariatric surgery patients in three integrated health systems to (i) investigate predictors of disenrollment and (ii) examine differences in weight bet...
