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The Bone & Joint Journal
Vol. 106-B, Issue 4 | Pages 394 - 400
1 Apr 2024
Kjærvik C Gjertsen J Stensland E Dybvik EH Soereide O

Aims. The aims of this study were to assess quality of life after hip fractures, to characterize respondents to patient-reported outcome measures (PROMs), and to describe the recovery trajectory of hip fracture patients. Methods. Data on 35,206 hip fractures (2014 to 2018; 67.2% female) in the Norwegian Hip Fracture Register were linked to data from the Norwegian Patient Registry and Statistics Norway. PROMs data were collected using the EuroQol five-dimension three-level questionnaire (EQ-5D-3L) scoring instrument and living patients were invited to respond at four, 12, and 36 months post fracture. Multiple imputation procedures were performed as a model to substitute missing PROM data. Differences in response rates between categories of covariates were analyzed using chi-squared test statistics. The association between patient and socioeconomic characteristics and the reported EQ-5D-3L scores was analyzed using linear regression. Results. The median age was 83 years (interquartile range 76 to 90), and 3,561 (10%) lived in a healthcare facility. Observed mean pre-fracture EQ-5D-3L index score was 0.81 (95% confidence interval 0.803 to 0.810), which decreased to 0.66 at four months, to 0.70 at 12 months, and to 0.73 at 36 months. In the imputed datasets, the reduction from pre-fracture was similar (0.15 points) but an improvement up to 36 months was modest (0.01 to 0.03 points). Patients with higher age, male sex, severe comorbidity, cognitive impairment, lower income, lower education, and those in residential care facilities had a lower proportion of respondents, and systematically reported a lower health-related quality of life (HRQoL). The response pattern of patients influenced scores significantly, and the highest scores are found in patients reporting scores at all observation times. Conclusion. Hip fracture leads to a persistent reduction in measured HRQoL, up to 36 months. The patients’ health and socioeconomic status were associated with the proportion of patients returning PROM data for analysis, and affected the results reported. Observed EQ-5D-3L scores are affected by attrition and selection bias mechanisms and motivate the use of statistical modelling for adjustment. Cite this article: Bone Joint J 2024;106-B(4):394–400


The Bone & Joint Journal
Vol. 104-B, Issue 7 | Pages 884 - 893
1 Jul 2022
Kjærvik C Gjertsen J Stensland E Saltyte-Benth J Soereide O

Aims. This study aimed to identify risk factors (patient, healthcare system, and socioeconomic) for mortality after hip fractures and estimate their relative importance. Further, we aimed to elucidate mortality and survival patterns following fractures and the duration of excess mortality. Methods. Data on 37,394 hip fractures in the Norwegian Hip Fracture Register from January 2014 to December 2018 were linked to data from the Norwegian Patient Registry, Statistics Norway, and characteristics of acute care hospitals. Cox regression analysis was performed to estimate risk factors associated with mortality. The Wald statistic was used to estimate and illustrate relative importance of risk factors, which were categorized in modifiable (healthcare-related) and non-modifiable (patient-related and socioeconomic). We calculated standardized mortality ratios (SMRs) comparing deaths among hip fracture patients to expected deaths in a standardized reference population. Results. Mean age was 80.2 years (SD 11.4) and 67.5% (n = 25,251) were female. Patient factors (male sex, increasing comorbidity (American Society of Anesthesiologists grade and Charlson Comorbidity Index)), socioeconomic factors (low income, low education level, living in a healthcare facility), and healthcare factors (hip fracture volume, availability of orthogeriatric services) were associated with increased mortality. Non-modifiable risk factors were more strongly associated with mortality than modifiable risk factors. The SMR analysis suggested that cumulative excess mortality among hip fracture patients was 16% in the first year and 41% at six years. SMR was 2.48 for the six-year observation period, most pronounced in the first year, and fell from 10.92 in the first month to 3.53 after 12 months and 2.48 after six years. Substantial differences in median survival time were found, particularly for patient-related factors. Conclusion. Socioeconomic, patient-, and healthcare-related factors all contributed to excess mortality, and non-modifiable factors had stronger association than modifiable ones. Hip fractures contributed to substantial excess mortality. Apparently small survival differences translate into substantial disparity in median survival time in this elderly population. Cite this article: Bone Joint J 2022;104-B(7):884–893


Bone & Joint Open
Vol. 1, Issue 10 | Pages 644 - 653
14 Oct 2020
Kjærvik C Stensland E Byhring HS Gjertsen J Dybvik E Søreide O

Aims. The aim of this study was to describe variation in hip fracture treatment in Norway expressed as adherence to international and national evidence-based treatment guidelines, to study factors influencing deviation from guidelines, and to analyze consequences of non-adherence. Methods. International and national guidelines were identified and treatment recommendations extracted. All 43 hospitals routinely treating hip fractures in Norway were characterized. From the Norwegian Hip Fracture Register (NHFR), hip fracture patients aged > 65 years and operated in the period January 2014 to December 2018 for fractures with conclusive treatment guidelines were included (n = 29,613: femoral neck fractures (n = 21,325), stable trochanteric fractures (n = 5,546), inter- and subtrochanteric fractures (n = 2,742)). Adherence to treatment recommendations and a composite indicator of best practice were analyzed. Patient survival and reoperations were evaluated for each recommendation. Results. Median age of the patients was 84 (IQR 77 to 89) years and 69% (20,427/29,613) were women. Overall, 79% (23,390/29,613) were treated within 48 hours, and 80% (23,635/29,613) by a surgeon with more than three years’ experience. Adherence to guidelines varied substantially but was markedly better in 2018 than in 2014. Having a dedicated hip fracture unit (OR 1.06, 95%CI 1.01 to 1.11) and a hospital hip fracture programme (OR 1.16, 95% CI 1.06 to 1.27) increased the probability of treatment according to best practice. Surgery after 48 hours increased one-year mortality significantly (OR 1.13, 95% CI 1.05 to 1.22; p = 0.001). Alternative treatment to arthroplasty for displaced femoral neck fractures (FNFs) increased mortality after 30 days (OR 1.29, 95% CI 1.03 to 1.62)) and one year (OR 1.45, 95% CI 1.22 to 1.72), and also increased the number of reoperations (OR 4.61, 95% CI 3.73 to 5.71). An uncemented stem increased the risk of reoperation significantly (OR 1.23, 95% CI 1.02 to 1.48; p = 0.030). Conclusion. Our study demonstrates a substantial variation between hospitals in adherence to evidence-based guidelines for treatment of hip fractures in Norway. Non-adherence can be ascribed to in-hospital factors. Poor adherence has significant negative consequences for patients in the form of increased mortality rates at 30 and 365 days post-treatment and in reoperation rates. Cite this article: Bone Joint Open 2020;1-10:644–653


Bone & Joint Open
Vol. 5, Issue 6 | Pages 524 - 531
24 Jun 2024
Woldeyesus TA Gjertsen J Dalen I Meling T Behzadi M Harboe K Djuv A

Aims

To investigate if preoperative CT improves detection of unstable trochanteric hip fractures.

Methods

A single-centre prospective study was conducted. Patients aged 65 years or older with trochanteric hip fractures admitted to Stavanger University Hospital (Stavanger, Norway) were consecutively included from September 2020 to January 2022. Radiographs and CT images of the fractures were obtained, and surgeons made individual assessments of the fractures based on these. The assessment was conducted according to a systematic protocol including three classification systems (AO/Orthopaedic Trauma Association (OTA), Evans Jensen (EVJ), and Nakano) and questions addressing specific fracture patterns. An expert group provided a gold-standard assessment based on the CT images. Sensitivities and specificities of surgeons’ assessments were estimated and compared in regression models with correlations for the same patients. Intra- and inter-rater reliability were presented as Cohen’s kappa and Gwet’s agreement coefficient (AC1).