A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Identifying classes with different disability profiles among patients undergoing lumbar discectomy: a latent class analysis
Tekijät: Saltychev, Mikhail; Koivunen, Konsta; Pernaa, Katri; Juhola, Juhani
Kustantaja: Ovid Technologies (Wolters Kluwer Health)
Julkaisuvuosi: 2026
Lehti: International Journal of Rehabilitation Research
ISSN: 0342-5282
eISSN: 1473-5660
DOI: https://doi.org/10.1097/MRR.0000000000000707
Julkaisun avoimuus kirjaamishetkellä: Ei avoimesti saatavilla
Julkaisukanavan avoimuus : Osittain avoin julkaisukanava
Verkko-osoite: https://doi.org/10.1097/mrr.0000000000000707
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/523653831
Rinnakkaistallennetun julkaisun versio: Final draft
The objective of this retrospective register-based study among 534 patients undergoing lumbar discectomy was to identify larger classes with different functional profiles. Main statistical method was latent class analysis. The mean age was 46.0 (17.8) years. Based on the distribution of 10 domains of functioning included in Oswestry Disability Index, four latent classes were identified: 'no or mild disability' (26% of the sample); 'moderate restrictions in sitting and traveling' (26%); 'moderate restrictions in standing and lifting and severe pain' (19%); and 'severe disability in most of the domains' (30%). Female sex (49 vs. 37%), obesity (48 vs. 28%), older age (63 vs.42%), greater pain severity (73-83 vs. 59-65%), and longer preoperative pain (27 vs. 20%) were associated with a higher likelihood of classification into a severe disability class. The results show that the functional difficulties of patients undergoing lumbar discectomy are not evenly distributed in the same way across individuals and are not simply a matter of variation at the individual level. It seems that there are larger classes whose disability domains are distributed in a different way than other classes. Belonging to a particular class can potentially be predicted by descriptive factors such as sex, age, pain intensity and pain history. This information can help identify risks that predict particularly severe disability and recognize the most common functional limitations that may be overlooked if all the patients are treated as a homogeneous group and the severity of disability is described by only one composite score.
