Predicting work ability impairment in post COVID-19 patients: a machine learning model based on clinical parameters.

Predicting work ability impairment in post COVID-19 patients: a machine learning model based on clinical parameters.

Publication date: Jan 16, 2025

The Post COVID-19 condition (PCC) is a complex disease affecting health and everyday functioning. This is well reflected by a patient’s inability to work (ITW). In this study, we aimed to investigate factors associated with ITW (1) and to design a machine learning-based model for predicting ITW (2) twelve months after baseline. We selected patients from the post COVID care study (PCC-study) with data on their ability to work. To identify factors associated with ITW, we compared PCC patients with and without ITW. For constructing a predictive model, we selected nine clinical parameters: hospitalization during the acute SARS-CoV-2 infection, WHO severity of acute infection, presence of somatic comorbidities, presence of psychiatric comorbidities, age, height, weight, Karnofsky index, and symptoms. The model was trained to predict ITW twelve months after baseline using TensorFlow Decision Forests. Its performance was investigated using cross-validation and an independent testing dataset. In total, 259 PCC patients were included in this analysis. We observed that ITW was associated with dyslipidemia, worse patient reported outcomes (FSS, WHOQOL-BREF, PHQ-9), a higher rate of preexisting psychiatric conditions, and a more extensive medical work-up. The predictive model exhibited a mean AUC of 0. 83 (95% CI: 0. 78; 0. 88) in the 10-fold cross-validation. In the testing dataset, the AUC was 0. 76 (95% CI: 0. 58; 0. 93). In conclusion, we identified several factors associated with ITW. The predictive model performed very well. It could guide management decisions and help setting mid- to long-term treatment goals by aiding the identification of patients at risk of extended ITW.

Open Access PDF

Concepts Keywords
Dyslipidemia COVID-19
Hospitalization Infectious disease
Pcc Long COVID
Trained Mental health
Post COVID
Post COVID-19 syndrome
Work ability

Semantics

Type Source Name
disease MESH COVID-19
drug DRUGBANK Factor IX Complex (Human)
pathway REACTOME SARS-CoV-2 Infection
disease IDO acute infection
disease MESH dyslipidemia
disease MESH Infection
disease MESH syndrome
disease MESH Long COVID
disease MESH obesity
disease IDO country
disease MESH severe acute respiratory syndrome
disease IDO blood
disease MESH hyperlipidemia
disease MESH depression
disease MESH functional status
drug DRUGBANK L-Valine
drug DRUGBANK Flunarizine
drug DRUGBANK Isoxaflutole
drug DRUGBANK Saquinavir
drug DRUGBANK Coenzyme M
disease MESH marital status
drug DRUGBANK Cysteamine
drug DRUGBANK Fibrinogen Human
drug DRUGBANK Trestolone
disease MESH psychiatric diagnosis
disease IDO symptom
disease MESH inflammation
disease MESH chronic fatigue syndrome
pathway REACTOME Reproduction
drug DRUGBANK Etoperidone
disease MESH Cancer
pathway REACTOME Immune System
drug DRUGBANK Cholesterol
disease MESH neurological manifestations
disease MESH anxiety
disease MESH loneliness
disease MESH cognitive dysfunction
drug DRUGBANK L-Leucine
disease MESH Acute Respiratory Distress Syndrome
disease MESH critical illness
disease MESH Death
disease MESH tic
disease MESH rheumatoid arthritis
pathway KEGG Rheumatoid arthritis
drug DRUGBANK Serine
disease MESH Infectious disease
pathway REACTOME Infectious disease

Original Article

(Visited 2 times, 1 visits today)

Leave a Comment

Your email address will not be published. Required fields are marked *