Predicting the duration of sickness absence due to knee osteoarthritis: a prognostic model developed in a population-based cohort in Sweden.
Duration
Knee osteoarthritis
Prediction
Sick-leave
Sickness absence
Journal
BMC musculoskeletal disorders
ISSN: 1471-2474
Titre abrégé: BMC Musculoskelet Disord
Pays: England
ID NLM: 100968565
Informations de publication
Date de publication:
02 Jul 2021
02 Jul 2021
Historique:
received:
16
11
2020
accepted:
25
05
2021
entrez:
3
7
2021
pubmed:
4
7
2021
medline:
7
7
2021
Statut:
epublish
Résumé
Predicting the duration of sickness absence (SA) among sickness absent patients is a task many sickness certifying physicians as well as social insurance officers struggle with. Our aim was to develop a prediction model for prognosticating the duration of SA due to knee osteoarthritis. A population-based prospective study of SA spells was conducted using comprehensive microdata linked from five Swedish nationwide registers. All 12,098 new SA spells > 14 days due to knee osteoarthritis in 1/1 2010 through 30/6 2012 were included for individuals 18-64 years. The data was split into a development dataset (70 %, n Of all SA spells, 53 % were > 90 days and 3 % >365 days. Factors included in the final model were age, sex, geographical region, extent of sickness absence, previous sickness absence, history of specialized outpatient healthcare and/or inpatient healthcare, employment status, and educational level. The model was well calibrated. Overall, discrimination was poor (c = 0.53, 95 % confidence interval (CI) 0.52-0.54). For predicting SA > 90 days, discrimination as measured by AUC was 0.63 (95 % CI 0.61-0.65), for > 180 days, 0.69 (95 % CI 0.65-0.71), and for SA > 365 days, AUC was 0.75 (95 % CI 0.72-0.78). It was possible to predict patients at risk of long-term SA (> 180 days) with acceptable precision. However, the prediction of duration of SA spells due to knee osteoarthritis has room for improvement.
Sections du résumé
BACKGROUND
BACKGROUND
Predicting the duration of sickness absence (SA) among sickness absent patients is a task many sickness certifying physicians as well as social insurance officers struggle with. Our aim was to develop a prediction model for prognosticating the duration of SA due to knee osteoarthritis.
METHODS
METHODS
A population-based prospective study of SA spells was conducted using comprehensive microdata linked from five Swedish nationwide registers. All 12,098 new SA spells > 14 days due to knee osteoarthritis in 1/1 2010 through 30/6 2012 were included for individuals 18-64 years. The data was split into a development dataset (70 %, n
RESULTS
RESULTS
Of all SA spells, 53 % were > 90 days and 3 % >365 days. Factors included in the final model were age, sex, geographical region, extent of sickness absence, previous sickness absence, history of specialized outpatient healthcare and/or inpatient healthcare, employment status, and educational level. The model was well calibrated. Overall, discrimination was poor (c = 0.53, 95 % confidence interval (CI) 0.52-0.54). For predicting SA > 90 days, discrimination as measured by AUC was 0.63 (95 % CI 0.61-0.65), for > 180 days, 0.69 (95 % CI 0.65-0.71), and for SA > 365 days, AUC was 0.75 (95 % CI 0.72-0.78).
CONCLUSION
CONCLUSIONS
It was possible to predict patients at risk of long-term SA (> 180 days) with acceptable precision. However, the prediction of duration of SA spells due to knee osteoarthritis has room for improvement.
Identifiants
pubmed: 34215239
doi: 10.1186/s12891-021-04400-8
pii: 10.1186/s12891-021-04400-8
pmc: PMC8254363
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
603Subventions
Organisme : Forskningsrådet om Hälsa, Arbetsliv och Välfärd
ID : 2007-1762
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