Assessing the Seasonality of Lab Tests Among Patients with Alzheimer's Disease and Related Dementias in OneFlorida Data Trust
Han, W.; Bhasuran, B.; Muse, V.; Brunak, S.; Lin, L.; Hanna, K.; Huang, Y.; Bian, J.; He, Z.
Show abstract
About 1 in 9 older adults over 65 has Alzheimers disease (AD), many of whom also have multiple other chronic conditions such as hypertension and diabetes, necessitating careful monitoring through laboratory tests. Understanding the patterns of laboratory tests in this population aids our understanding and management of these chronic conditions along with AD. In this study, we used an unimodal cosinor model to assess the seasonality of lab tests using electronic health record (EHR) data from 34,303 AD patients from the OneFlorida+ Clinical Research Consortium. We observed significant seasonal fluctuations--higher in winter in lab tests such as glucose, neutrophils per 100 white blood cells (WBC), and WBC. Notably, certain leukocyte types like eosinophils, lymphocytes, and monocytes are elevated during summer, likely reflecting seasonal respiratory diseases and allergens. Seasonality is more pronounced in older patients and varies by gender. Our findings suggest that recognizing these patterns and adjusting reference intervals for seasonality would allow healthcare providers to enhance diagnostic precision, tailor care, and potentially improve patient outcomes.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Olfactory Response as a Marker for Alzheimer's Disease: Evidence from Perceptual and Frontal Oscillation Coherence Deficit 93%
- Examining heterogeneity in dementia using data-driven unsupervised clustering of cognitive profiles 93%
- CohortDiagnostics: phenotype evaluation across a network of observational data sources using population-level characterization 93%
Similar papers in this journal
- Close contact infection dynamics over time: insights from a second large-scale social contact survey in Flanders, Belgium, in 2010-2011 90%
- Explanation of Hand, Foot, and Mouth Disease Cases in Japan Using Google Trends Before and During the COVID-19: Infodemiology Study 90%
- Seroprevalence of SARS-CoV-2 antibodies in social housing areas in Denmark 89%
Similar papers in this journal
- Characterizing subgroup performance of probabilistic phenotype algorithms within older adults: A case study for dementia, mild cognitive impairment, and Alzheimer’s and Parkinson’s diseases 93%
- Trajectories: a framework for detecting temporal clinical event sequences from health data standardized to the OMOP Common Data Model 91%
- Clinical interpretation of machine learning models for prediction of diabetic complications using electronic health records 90%
Similar papers in this journal
Similar papers in this journal
- Detection of cognitive decline using a single-channel EEG with an interactive assessment tool 91%
- Phenotyping Neuropsychiatric Symptoms Profiles of Alzheimer's Disease Using Cluster Analysis on EEG Power 90%
- Biological and Disease Hallmarks of Alzheimer’s Disease Defined by Alzheimer’s Disease Genes 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.