What is the clinical evidence from this study?

Study design: Cohort. Population: Hip fracture (n=14932). Intervention: University hospital admission vs. Non-university hospital admission. Primary outcome: All-cause mortality at longest follow-up (aHR 0.83, 95% CI 0.76-0.91, p=<0.001).

What does this research mean for the field?

Admission to a university hospital for hip fracture surgery is associated with a significantly lower risk of all-cause mortality compared to non-university hospitals, while age, male gender, ASA-PS-class, and postoperative care unit length of stay are strong independent predictors of mortality. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

October 18, 2018Open Access

Determinants of mortality after hip fracture surgery in Sweden: a registry-based retrospective cohort study

Q: What are the key findings of this study?

Admission to a university hospital for hip fracture surgery was associated with a significantly lower risk of all-cause mortality (aHR 0.83) compared to non-university hospitals.

Q: What does this research mean for the field?

Admission to a university hospital for hip fracture surgery is associated with a significantly lower risk of all-cause mortality compared to non-university hospitals, while age, male gender, ASA-PS-class, and postoperative care unit length of stay are strong independent predictors of mortality. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Key Result

Admission to a university hospital for hip fracture surgery was associated with a significantly lower risk of all-cause mortality (aHR 0.83) compared to non-university hospitals.

Study Design

Type

Cohort (n=14,932)

Multicenter

Yes

Structured PICO

What are the independent predictors of mortality in patients undergoing hip fracture surgery?

Population

14,932 patients ≥18 years of age undergoing surgical hip fracture procedures in Sweden between January 1, 2014 and December 31, 2016. Median age 83, 66.8% female.

Intervention

12 interrelated 'exposures' including patient, surgical, anaesthetic, and structural factors (e.g., age, gender, ASA-PS-class, university hospital status, time of surgery, type of surgery, compliance to surgical urgency planning, surgical delay, time in theatre, type of anaesthesia, PACU-LOS, ICU-admission)

Outcome

All-cause mortality at longest follow-up (up to 3 years)hard clinical

Age, male gender, higher ASA-PS class, and longer PACU stay are independent predictors of mortality after hip fracture surgery, whereas treatment at a university hospital is protective.

Main Result

Effect estimate: aHR 0.83 (95% CI 0.76-0.91)

p-value: p=<0.001

Limitations

Possibility of unmeasured confounders such as socioeconomic factors, hospital staffing, and severity of comorbidities
Only examined mortality as an end-point, lacking data on functional status or complications
Did not examine specific causes of death
Lack of complete coverage in the registry during the study period
Did not distinguish between university and non-university teaching hospitals, or urban and rural hospitals

Abstract

Surgery for hip fractures is associated with high mortality and morbidity. The causes of poor outcome are not fully understood and may be related to other factors than the surgery itself. The relative contributions of patient, surgical, anaesthetic and structural factors have seldom been studied together. This study, a retrospective registry-based cohort study of 14 932 patients undergoing hip fracture surgery in Sweden from 1st of January 2014 to 31st of December 2016, aimed to identify important predictors of mortality post-surgery. The independent predictive power of our included variables was examined using Cox proportional hazards modeling with all-cause mortality at longest follow-up as the outcome. Twelve independent variables were considered as interrelated 'exposures' and their individual adjusted effect within a single model were evaluated. Kaplan-Meier curves were also generated. Crude mortality rates were 8.2% at 30 days (95% CI 7.7-8.6%) and 23.6% at 365 days (95% CI 22.9-24.2%). Of the 12 factors entered into the Cox regression analysis, age (aHR1.06, p < 0.001), male gender (aHR 1.45, p < 0.001), ASA-PS-class (ASA 1 ASA 3 aHR 2.12; ASA 4 aHR 4.79; ASA 5 aHR 12.57 respectively, p < 0.001) and PACU-LOS (aHR 1.01, p < 0.001) were significantly associated with mortality at longest follow-up (up to 3 years). University hospital status was protective (aHR 0.83, p < 0.001) in the same model. Age, gender and ASA-PS-class were strong predictors of mortality after surgery for hip fractures in Sweden. University hospital status and length of stay in the postoperative care unit were also identified as modifiable risk factors after multivariable adjustment and require confirmation in future studies.

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