About

Andrew I-Wei Chin, M.D., is a Health Sciences Clinical Professor and Interim Chief of Nephrology at UC Davis Health within the Department of Internal Medicine. He specializes in nephrology, offering care for adults with kidney diseases, including those on dialysis. His clinical approach emphasizes building understanding in partnership with patients and applying evidence-based, holistic treatments. Dr. Chin's research focuses on outcomes for individuals with advanced chronic kidney disease, the transition of care for dialysis patients, and aspects of hemodialysis care, particularly maintaining residual kidney function. His academic background includes a B.A. in Ecology and Evolutionary Biology from Princeton University and an M.D. from UC Davis School of Medicine. He completed his internship, residency, and chief residency in internal medicine at Scripps Mercy Hospital and Medical Center, followed by a nephrology fellowship at UC Davis. Dr. Chin has contributed to the field through research on dialysis catheter malfunction, glomerular filtration rate decline, oxidative stress in nephrology, cardiovascular health in CKD, and other topics related to kidney disease and dialysis management.

Research topics

• Medicine
• Computer Science
• Data science
• Environmental health
• Internal medicine
• Internet privacy
• Nursing
• Business
• World Wide Web
• Immunology
• Intensive care medicine
• Virology
• Actuarial science

Selected publications

• Adverse outcomes post-COVID-19 hospitalization among ESRD patients: A retrospective cohort study in 5 California university medical centers

  PLoS ONE · 2025-09-18

  articleOpen accessCorresponding

  BACKGROUND: Individuals with end-stage renal disease (ESRD) hospitalized for COVID-19 may have a higher risk for adverse post discharge events. To investigate these risks, we examined a large database of individuals admitted for COVID-19 and discharged alive, to see if ESRD was independently associated with higher risk for death within 180 days or for 30-day hospital readmission. METHODS: We retrospectively compared risks for hospital, non-hospital, and overall death within 180 days and 30-day hospital readmission between individuals with and without ESRD. We studied individuals hospitalized with COVID-19 between January 6, 2020 and August 3, 2023, at any of the 5 University of California medical centers and discharged alive. RESULTS: Of 11,406 individuals hospitalized with COVID-19 who were discharged alive, 713 (6.3%) had ESRD. Compared to individuals without ESRD, those with ESRD had a significantly higher hazard of hospital and overall death within 180 days post-discharge in the unadjusted analyses, but not in the analyses adjusted for demographic variables, hospitalization period, and comorbid conditions (adjusted Wald chi-square hazard ratio (HR) 1.36, 95% Wald CI 0.78-2.37; adjusted HR 1.05, 95% CI 0.73-1.51, respectively). Those with ESRD did not have a significantly higher hazard of non-hospital death within 180 days post-discharge in either the unadjusted or the adjusted analyses (adjusted HR 0.89, 95% CI 0.55-1.44), but did have a significantly higher hazard of 30-day hospital readmission in both the unadjusted and the adjusted analyses (adjusted HR 1.36, 95% CI 1.14-1.63, p = 0.001). CONCLUSIONS: ESRD patients hospitalized with COVID-19 had a higher unadjusted risk of hospital and overall death within 180 days and of 30-day hospital readmission than individuals without ESRD. After adjusting for demographic factors, hospitalization period, and comorbidities, presence of ESRD was not found to significantly increase the risk for hospital, non-hospital, or overall death within 180 days post-discharge, but was found to significantly increase the risk of 30-day hospital readmission.

  PublisherDOI

• Estimating braking and propulsion forces during overground running in and out of the lab

  PLoS ONE · 2025-09-04 · 1 citations

  articleOpen accessCorresponding

  Accurately estimating kinetic metrics, such as braking and propulsion forces, in real-world running environments enhances our understanding of performance, fatigue, and injury. Wearable inertial measurement units (IMUs) offer a potential solution to estimate kinetic metrics outside the lab when combined with machine learning. However, current IMU-based kinetic estimation models are trained and evaluated within a single environment, often on lab treadmills. The transferability of these treadmill-trained models during overground running in and out of the lab is underexplored, and the individualization and validation of such models remain a challenge. Toward bridging this gap, we trained a generalized model on treadmill data of 15 recreational runners and evaluated braking and propulsion force estimates during overground running in and out of the lab. We explored fine-tuning with individual data from lab-based overground running to quantify model performance improvements with individualization. The generalized and fine-tuned models were extrapolated to outdoor running for a subset of five participants, and estimates were compared to lab-based overground measurements. Evaluating the generalized model with a leave-one-out cross validation yielded overground braking and propulsion force root mean squared error of 4.3 ± 1.1 % bodyweight (%BW). Fine-tuning this model with eight strides reduced error to 2.6 ± 0.5 %BW. Outdoor force predictions from the fine-tuned model better aligned with expected linear trends between braking/propulsion impulses and speed than the generalized model. These results provide insights into the accuracy and applicability of IMU data-driven models for braking and propulsion estimation during overground running, facilitating the development of practical, individualized biomechanical analysis tools for real-world use.

  PublisherOA PDFDOI

• Protocol for a patient-derived preclinical platform to model tumor-immune interactions and evaluate therapeutic efficacy

  STAR Protocols · 2025-02-06 · 1 citations

  articleOpen access

  Here, we present a protocol for a preclinical ex vivo platform combining experimental flexibility with preservation of the tumor microenvironment. We outline steps for isolating human peripheral blood mononuclear cells (PBMCs), preparing patient-derived precision-cut tumor slices (PCTSs), cryopreserving the samples, and setting up the co-culture system. We provide instructions for treatment applications, interactions, and analyzing therapy responses. By preserving tumor architecture and heterogeneity, this model is applicable for evaluating tumor characteristics, immune interactions, and treatment efficacy in translational cancer research. • Integration of PCTS and PBMCs to model patient-specific tumor-immune environments • Steps to cryopreserve PCTS and PBMCs for flexible scheduling and long-term storage • Procedures to evaluate therapeutic efficacy within one week of co-culture experiments • Guidance on diverse analyses using a patient-derived ex vivo co-culture model Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Here, we present a protocol for a preclinical ex vivo platform combining experimental flexibility with preservation of the tumor microenvironment. We outline steps for isolating human peripheral blood mononuclear cells (PBMCs), preparing patient-derived precision-cut tumor slices (PCTSs), cryopreserving the samples, and setting up the co-culture system. We provide instructions for treatment applications, interactions, and analyzing therapy responses. By preserving tumor architecture and heterogeneity, this model is applicable for evaluating tumor characteristics, immune interactions, and treatment efficacy in translational cancer research.

  PublisherDOI

• Multi-Modal Sensing for Propulsion Estimation in People Post-Stroke Across Speeds

  IEEE Transactions on Neural Systems and Rehabilitation Engineering · 2025-01-01 · 1 citations

  articleOpen access

  Gait rehabilitation is critical for regaining locomotor independence after neuromotor injuries like stroke. Rehabilitation literature indicates the need for such therapy to continue beyond the clinic in order to maintain motor function and support recovery. However, implementing community-based rehabilitation requires the ability to monitor gait in the real-world with clinically relevant accuracies. Despite advances in machine learning, achieving this performance with single sensing modalities has been challenging using wearable sensors like inertial measurement units (IMUs) and pressure insoles. Here, we investigate the benefits of multi-modal sensing by integrating IMU and insole data to develop individualized machine learning models in people post-stroke that estimate propulsion, a key biomechanical variable. We show that in the lab, IMU + Insole models improve performance relative to IMU only and Insole only models, with an average root-mean-squared-error (RMSE) of 0.80 %bodyweight (%BW) across the stance phase. We obtain RMSEs of 0.71%BW for peak paretic propulsion and 0.19%BW s for paretic propulsion impulse, which are within corresponding clinical thresholds. We then explore the application of this algorithm to track propulsion changes in the real-world for two participants during variable-speed walking and two participants during active gait interventions, either functional electrical stimulation or exosuit-applied resistance. For these participants, we observe similar changes in measured propulsion in the lab and estimated propulsion out of the lab across speeds and interventions. Overall, this work aims to address the challenges in applying machine learning methods for individuals post-stroke and presents an investigation into the feasibility of developing estimation methods for real-world propulsion estimation during gait rehabilitation.

  PublisherDOI

• Retrospective Analysis of Clinical Effects Following Reduction in Dialysate Sodium in Patients on Long-Term Hemodialysis

  Journal of the American Society of Nephrology · 2025-10-01

  articleSenior author

  Background: Dialysate sodium (NaD) influences fluid balance and blood pressure (BP) in hemodialysis (HD). While lowering NaD has been associated with improved BP control and reduced IDWG, the underlying mechanisms are not fully understood. We explored the clinical and biochemical effects of reducing NaD in a long-term HD population. Methods: This was a retrospective study of chronic, thrice-weekly (TIW) ICHD patients at an urban Northern California center before and after NaD reduction from 145 to 138 mEq/L. Included patients had no residual kidney function and ≥1 year of HD on both NaD levels. Data on weight (wt), inter-dialytic weight gain (IDWG), pre-/post-HD BP, and anti-HTN lists were collected for 1 year before and after the change. During low NaD period, patients were observed by whether serum sodium (NaS) was above or below NaD to assess differences in fluid status and BP. Serum osmolality (osm) was calculated from monthly labs. Paired and unpaired t-tests were used where appropriate. Results: We identified 130 patients on TIW ICHD who met inclusion criteria. Mean lab, hemodynamic, and wt data are shown in Table 1. Anti-HTN medication list did not differ significantly before vs. after the NaD change. During the low NaD period, 67 patients had pre-HD serum sodium (NaS) ≤ NaD and showed persistently lower serum osmolality compared to those with NaS > NaD, both before and after the NaD change. Conclusion: Lower NaD was associated with improved BP control and reduced IDWG. While serum osm had statistically significant decrease after NaD change, the difference was small. Patients maintained similar serum Na and osm across both NaD periods, suggesting that the benefits of lower NaD may not be driven by serum osm and that patients may have individual osm set points. Table 1 - High NaD Low NaD p-value Serum Sodium (mEq/L) 138.2 ± 2.9 138.3 ± 2.6 0.67 Serum Albumin (g/dL) 3.8 ± 0.4 3.8 ± 0.4 0.93 Post HD Wt (kg) 71.0 ± 24.2 71.1 ± 25.4 0.89 IDWG (kg) 3.4 ± 1.8 2.7 ± 1.1 <0.001 Calculated Serum Osm 302 ± 8 300 ± 8 0.02 Pre-HD Systolic BP 157 ± 18 152 ± 20 <0.001 Pre-HD Diastolic BP 85 ± 12 81 ± 13 <0.001 Post-HD Systolic BP 144 ± 16 138 ± 16 <0.001 Post-HD Diastolic BP 78 ± 9 74 ± 11 <0.001 Pre-HD MAP 109 ± 13 104 ± 14 <0.001 Post-HD MAP 100 ± 11 95 ± 11 <0.001

  PublisherDOI

• Noninvasive Prediction Models of First Decompensation in Compensated Advanced Chronic Liver Disease: A Meta-Analysis

  Clinical Gastroenterology and Hepatology · 2025-10-10 · 2 citations

  review
  PublisherDOI

• 620P Novel outcome measures to quantify longitudinal changes in motor function in FSHD

  Neuromuscular Disorders · 2024-10-01

  article
  PublisherDOI

• Propulsion Modulation Methods in People Post-Stroke during Resistive Ankle Exosuit Use

  2024-09-01

  article

  Locomotion requires careful coordination across the various joints and muscles of the body, which can be disrupted after neuromotor injuries such as stroke. People post-stroke often have weakness in their paretic, or more impaired, ankle plantarflexors and a corresponding reliance on the hip joint to generate sufficient forward propulsion. The field of robotic rehabilitation has developed wearable systems that provide joint-and task-specific training for survivors of stroke, and in turn, increase use of the ankle muscles. However, capturing ankle use at the plantarflexor level remains a challenge with conventional tools given the unknown relative contributions of the dorsiflexor muscles. Moreover, variability across individuals complicates the interpretation of user response to these robotic interventions. In this work, we used standard biomechanical analysis as well as shear wave tensiometry in five people post-stroke to gain insight into user-specific ankle and hip adaptations in response to three levels of targeted plantarflexion exosuit resistance. We show that at a group and individual-level, evidence suggests a shift in biomechanical strategy from relying on the hip to using the ankle to modulate propulsion, with a subset of participants completely shifting to the ankle by the end of training. This work represents a step towards exploring more individualized methods for characterizing user response during adaptation to wearable robotic training interventions.

  PublisherDOI

• Soft robotic apparel to avert freezing of gait in Parkinson’s disease

  Nature Medicine · 2024-01-01 · 67 citations

  article
  PublisherDOI

• Hospitalizations Increase Medication Complexity in Patients on Long-Term Hemodialysis

  Journal of the American Society of Nephrology · 2024-10-01

  articleSenior author

  Background: End stage kidney disease (ESKD) patients are medically complex with significant polypharmacy. Medication regimen complexity index (MRCI) is a validated, non-disease-specific tool that considers medication form, frequency, and special instructions. MRCI has not been well studied in this population. We compared pre and post hospitalization MRCI in hemodialysis (HD) patients. Methods: This retrospective study included 60 adult patients on HD admitted to a large academic medical center. Data collection included: age; dialysis vintage; hospital length of stay (LOS); admission diagnosis; number of prescriptions and MRCI before hospitalization and at discharge (excluding medications administered at the dialysis clinic). Paired t-test was used to analyze the number of prescriptions and MRCI, comparing pre and post hospitalization. We also examined age, vintage, and LOS for association with MRCI. Results: Mean age was 63.0 ± 12.7 years, median vintage 5 years (interquartile range 2 to 7), and median LOS 10 days (interquartile range 3 to 19). MRCI was significantly higher post-hospitalization than pre-hospitalization (mean 52.7 versus 48.7; p=0.008). Total medication complexity was driven by both an increase in the number of prescriptions as well as an increase in average prescription complexity (see Table 1). We found no association between pre-hospital MRCI with age, vintage, or LOS. Conclusion: In ESKD patients on HD, there is a significant increase in MRCI post-hospitalization that is driven by an increase in number of medications as well as average medication complexity. Whether higher MRCI in this population is associated with more adverse outcomes, such as mortality or increased hospital readmissions, remains unanswered.Table 1: Pre and post hospitalization MRCI and prescription analysis

  PublisherDOI

Frequent coauthors

• Inga Duignan

  65 shared

• Munira Xaymardan

  University of Sydney

  56 shared

• Jay M. Edelberg

  Bristol-Myers Squibb (United States)

  54 shared

• Jingang Zheng

  China-Japan Friendship Hospital

  53 shared

• Mun K. Hong

  Bassett Medical Center

  50 shared

• Jinho Shin

  Anyang University

  49 shared

• Yi Mu

  18 shared

• Heejung Bang

  University of California, Davis

  14 shared

Labs

• NephrologyPI

Education

• Mechanical Engineering

  University of Rochester

  2020