Related Experiment Videos
Using latent class analysis to identify subgroups of postoperative older adults
Kevin H McLaughlin1, Amie Bettencourt2, Daniel Young3
1Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
SAGE Open Medicine
|June 18, 2026
Summary
Latent class analysis identified three distinct subgroups among older adults after surgery. These patient subgroups, based on frailty and mobility, may help tailor postoperative care and improve outcomes.
Area of Science:
- Geriatric Medicine
- Health Services Research
- Data Science in Healthcare
Background:
- Older adults undergoing surgery represent a heterogeneous population with varying postoperative outcomes.
- Routinely collected patient data offers a valuable resource for understanding patient heterogeneity.
- Traditional measures may not fully capture the complexity of patient recovery post-surgery.
Purpose of the Study:
- To identify distinct subgroups of older adults (65+ years) after surgery using latent class analysis (LCA).
- To examine differences in hospital outcomes, including length of stay (LOS), discharge disposition, and therapy utilization, among identified subgroups.
- To leverage routinely collected patient data for a more nuanced understanding of postoperative recovery.
Main Methods:
- Retrospective analysis of routinely collected data from 2,036 older adults (≥65 years) post-surgery.
- Latent class analysis (LCA) was employed to define subgroups based on frailty, mobility, activities of daily living, and general health status.
- Hospital outcomes, including extended LOS, discharge disposition (home vs. non-home), and physical/occupational therapy (PT/OT) visit frequency, were compared across subgroups.
Main Results:
- Three patient subgroups were identified: Low Frailty-High Mobility (LF-HM, 15.3%), High Frailty-Low Mobility (HF-LM, 27.6%), and Low Frailty-Low Mobility (LF-LM, 57.1%).
- The HF-LM group experienced the highest rates of extended LOS (27%) and non-home discharge (23%), and the highest PT/OT utilization.
- The LF-HM group had the best outcomes, with 99% home discharge and only 6% extended LOS.
Conclusions:
- Latent class analysis successfully identified three distinct subgroups of postoperative older adults based on routinely collected data.
- These identified subgroups may explain variations in hospital outcomes not captured by single measures.
- The findings support the development of tailored postoperative care strategies for older adult surgical patients.
Related Concept Videos
01:20Comparing the Survival Analysis of Two or More Groups
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
01:16Stratified Sampling Method
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
To choose a stratified sample, divide the population into groups called strata and then take a...
02:20Longitudinal Research
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...