ArticleOccupational and environmental medicine2020
Predicting the duration of sickness absence spells due to back pain: a population-based study from Sweden.
Article in Occupational and environmental medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Predicting prolonged work absence due to musculoskeletal disorders: development, validation, and clinical usefulness of prognostic prediction models.International archives of occupational and environmental health · 2025Article
- Work Interventions Within Interdisciplinary Pain Rehabilitation Programs (IPRP) - Frequency, Patient Characteristics, and Association with Self-Rated Work Ability.Journal of pain research · 2023Article
- Role of social benefits for future long-term sickness absence, disability pension and unemployment among individuals on sickness absence due to mental diagnoses: a competing risk approach.International archives of occupational and environmental health · 2022Article
- Use of Health Services and Rehabilitation before and after the Beginning of Long-Term Sickness Absence-Comparing the Use by Employment and Disability Pension Transition after the Sickness Absence in Finland.International journal of environmental research and public health · 2022Article
- Article
- The role of sickness absence diagnosis for the risk of future inpatient- or specialized outpatient care in a Swedish population-based twin sample.BMC public health · 2021Article
- The predictive role of sickness absence spell durations in associations with inpatient- and specialized outpatient care among a population-based Swedish twin sample.BMC health services research · 2021Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesWe aimed to develop and validate a prediction model for the duration of sickness absence (SA) spells due to back pain (International Statistical Classification of Diseases and Related Health Problems 10th Revision: M54), using Swedish nationwide register microdata.
methodsInformation on all new SA spells >14 days from 1 January 2010 to 30 June 2012 and on possible predictors were obtained. The duration of SA was predicted by using piecewise constant hazard models. Nine predictors were selected for the final model based on a priori decision and log-likelihood loss. The final model was estimated in a random sample of 70% of the SA spells and later validated in the remaining 30%.
resultsOverall, 64 048 SA spells due to back pain were identified during the 2.5 years; 74% lasted ≤90 days, and 9% >365 days. The predictors included in the final model were age, sex, geographical region, employment status, multimorbidity, SA extent at the start of the spell, initiation of SA spell in primary healthcare and number of SA days and specialised outpatient healthcare visits from the preceding year. The overall c-statistic (0.547, 95% CI 0.542 to 0.552) suggested a low discriminatory capacity at the individual level. The c-statistic was 0.643 (95% CI 0.634 to 0.652) to predict >90 days spells, 0.686 (95% CI 0.676 to 0.697) to predict >180 spells and 0.753 (95% CI 0.740 to 0.766) to predict >365 days spells.
conclusionsThe model discriminates SA spells >365 days from shorter SA spells with good discriminatory accuracy.
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