Background: Complications after surgery can be predicted using ASA classification or comorbidity count. No study has assessed the measure self-rated health (SRH) yet. Our objective was to assess the association between SRH, ASA and comorbidity count and medical complications during hospitalization, and death and all-cause revision within 5years.

Methods: A prospective cohort study of primary elective total hip arthroplasties (THA) was conducted 2002-2019 including information on preoperative general health measured with SRH, comorbidity count and ASA grade. For medical complications, proportions of events per category of health measure were calculated. Risk of all-cause revision and mortality was assessed in the first five years after surgery using reverse Kaplan-Meier and Cox regression analyses.

Results: Overall, 3906 patients were included (mean age 69years). The risks of experiencing at least one medical complication and a severe medical complication during hospitalization were 27.2% and 1%, increasing with decreasing health status. Cumulative 5-year risk of dying was 9.5% (95%CI 8.5-10.6), increasing with decreasing health status. ASA grade 3-4 was most strongly associated with death (hazard ratio (HR) 5.0, 95%CI 2.3-10-8) compared to ASA grade 1. Patients with poor SRH or ≥ 4 comorbidities had a 3 times higher risk of dying. Cumulative 5-year risk of revision overall was 3.1% (95%CI 2.6-3.7), increasing with decreasing health status. The association was only significant in the first 3 months postoperative. For comorbidity count the adjusted HR was 3.6 (95%CI 1.9-6.8), and for ASA 3-4 h was 3.3 (95%CI 1.8-6.1).

Conclusion: SRH, ASA classification and comorbidity count showed increasing risks of medical complications and death with decreasing health status. ASA was most strongly associated with death. Regarding revision both comorbidity count and ASA performed well. SRH was associated with medical complications and death independent of the effect of ASA score or number of comorbidities indicating differences between health status measurements with respect to the underlying mechanisms.