Abstract
Aims
This work aimed at answering the following research questions: 1) What is the rate of mechanical complications, nonunion and infection for head/neck femoral fractures, intertrochanteric fractures, and subtrochanteric fractures in the elderly USA population? and 2) Which factors influence adverse outcomes?
Methods
Proximal femoral fractures occurred between 1 January 2009 and 31 December 2019 were identified from the Medicare Physician Service Records Data Base. The Kaplan-Meier method with Fine and Gray sub-distribution adaptation was used to determine rates for nonunion, infection, and mechanical complications. Semiparametric Cox regression model was applied incorporating 23 measures as covariates to identify risk factors.
Results
Union failure occured in 0.89% (95% confidence interval (CI) 0.83 to 0.95) after head/neck fracturs, in 0.92% (95% CI 0.84 to 1.01) after intertrochanteric fracture and in 1.99% (95% CI 1.69 to 2.33) after subtrochanteric fractures within 24 months. A fracture-related infection was more likely to occur after subtrochanteric fractures than after head/neck fractures (1.64% vs 1.59%, hazard ratio (HR) 1.01 (95% CI 0.87 to 1.17); p < 0.001) as well as after intertrochanteric fractures (1.64% vs 1.13%, HR 1.31 (95% CI 1.12 to 1.52); p < 0.001). Anticoagulant use, cerebrovascular disease, a concomitant fracture, diabetes mellitus, hypertension, obesity, open fracture, and rheumatoid disease was identified as risk factors. Mechanical complications after 24 months were most common after head/neck fractures with 3.52% (95% CI 3.41 to 3.64; currently at risk: 48,282).
Conclusion
The determination of complication rates for each fracture type can be useful for informed patient-clinician communication. Risk factors for complications could be identified for distinct proximal femur fractures in elderly patients, which are accessible for therapeutical treatment in the management.
Cite this article: Bone Jt Open 2023;4(10):801–807.
Take home message
The determination of complication rates for each fracture type can be useful for informed patient-clinician communication.
Risk factors for complications could be identified for distinct proximal femur fractures in elderly patients, which are accessible for therapeutical treatment in the management of these complications.
Introduction
Proximal femur fractures (PFFs) are among the most common type of fractures. These can be caused by a variety of factors such as falls, osteoporosis, and trauma. PFFs primarily affect elderly individuals, and comorbitant injuries are common.1 The incidence is expected to rise as the ageing population increases.2 Projections have estimated that the annual prevalence would heighten from 1.26 million in 1990 to 4.5 million by 2050.3
PFFs can have significant consequences including increased morbidity, decreased quality of life, and one-year mortality rates up to 23%.4-6 Additionally, PFFs are associated with high healthcare costs including long hospitalization periods, surgery, and rehabilitation and thus, it was ranked as the 13th most expensive diagnosis.7 A meta-analysis revealed one-year healthcare costs of USD $43,000 per patient.8 Treatment for PFF typically involves surgical intervention such as hip arthroplasty or internal fixation. For femoral neck fractures, a high number of arthroplasties is reported,9 while intertrochanteric and subtrochanteric fractures are mainly treated with nailing. 10,11
Despite advances in surgical techniques as well as interdisciplinary treatment approaches, complications such as failure of bony union, or the occurrence of a fracture-related infection, are still unavoidable. As optimal management including the considerations of risk factors for adverse events is critical for reducing the burden of this condition on both patients, and the healthcare systems, this work aimed at answering the following questions: 1) What is the rate of complications in terms of mechanical complications, nonunion and infection after surgical fixation of head/neck femoral fractures, intertrochanteric fractures, and subtrochanteric fractures in the elderly USA population? and 2) Which factors influence adverse outcomes?
Methods
Proximal femoral fractures occurring between 1 January 2009 and 31 December 2019 were identified from the Medicare Physician Service Records Data Base. These records encompassed services rendered in medical offices, clinics, hospitals, emergency departments, skilled nursing facilities, and other healthcare institutions. They were compiled by the Centres for Medicare and Medicaid Services (CMS) and, after deidentification, were made available for research, known as the Limited Data Set (LDS). CMS replaced the beneficiary’s identity with a synthetic and unique ID in the LDS data sets, which allowed patients to be followed longitudinally for survivorship and outcomes analyses. The population of interest included elderly Medicare patients (aged 65 years and above). Since the CMS data are deidentified, it was exempt from review by the Institutional Review Board.
The International Classification of Diseases (ICD), Ninth and Tenth Revisions,12,13 were used to identify femoral fractures from these physician records. Diagnoses in claims submitted before 1 October 2015 were recorded in ICD-9-CM and thereafter in ICD-10-CM. Several steps were implemented to ensure that the identified fracture was true, and was a new fracture. First, only records with fracture diagnosis listed as the primary diagnosis were retained. Second, there must be no fracture record of the same type in the previous year. Concurrent fracture of different parts of the femur (e.g. a head/neck fracture) was not uncommon, and was included. Some patients did experience the same type of fracture more than once during the ten-year study period, but from one fracture to the next, a minimal interval of one year was required to ensure that the next fracture was not associated with continued care for the previous fracture. Third, for fractures coded using ICD-10, the seventh digit must be “A”, “B”, or “C”, indicating a new encounter with that condition. Fractures with diagnoses indicating postoperative care for healing of fracture, or codes that indicated malunion or nonunion, would not be counted because these conditions were consistent only with pre-existing fractures.
Three types of outcome analysis were investigated. They were: a) the likelihood of malunion or nonunion following the fracture, b) the risk of post-fracture infection, and c) mechanical complication following fracture repairs.
Statistical analysis
We used survival analysis techniques to analyze these outcomes. The Kaplan-Meier (KM) method, with the Fine and Gray sub-distribution adaptation, was used to calculate the cumulative incidence rate of the malunion/nonunion, infection, and mechanical complications.14 We also used the semiparametric Cox regression with competing risk correction to investigate these outcomes and to compare the risk between different types of femoral fracture, after adjusting for a number of potential confounding factors. The Cox models incorporated demographic, clinical, and several community-level socioeconomic measures as covariates. The demographic factors included: age, sex, race, resident region, and Medicare buy-in (as a surrogate for patient’s economic status). Clinical factors included were osteoporosis, obesity, diabetes mellitus, rheumatoid disease, chronic kidney disease, tobacco dependence, regular use of anticoagulant, regular insulin use, regular non-steroidal anti-inflammatory drugs (NSAID) use, hypertension, ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease (COPD), and congestive heart failure. These conditions were identified from physician records in a one-year period prior to the fracture. Supplementary Table i provides the codes used to identify these conditions. These conditions could appear as either primary or secondary diagnosis, but at least two mentions of such condition in the prior year was required. All data processing and statistical analyses were performed using the SAS statistical software (Version 9.4; SAS Institute, USA) and significance was determined at α = 0.05.
Results
Study population
A total of 163,091 proximal femoral fractures were identified. Out of these, 97,957 (60.0%) were head/neck fractures, 56,896 (34.9%) intertrochanteric fractures, and 8,238 (5.1%) subtrochanteric fractures. The majority of patients was in the age group 80 years or older (112,841, 69.2%). Patients were predominantly female (117,724, 72.2%) (Table I).
Table I.
Demographic data and comorbidities of the study population.
| Variable | Fracture | |||||||
|---|---|---|---|---|---|---|---|---|
| All proximal femur Fx | Head/neck | Pertrochanteric | Subtrochanteric | |||||
| Demographic | Fx, n | Fx, % | Fx, n | Fx, % | Fx, n | Fx, % | Fx, n | Fx, % |
| Total | 163,091 | 100.0 | 97,957 | 100.0 | 56,896 | 100.0 | 8,238 | 100.0 |
| Age at Fx, yrs | ||||||||
| 65 to 69 | 10,150 | 6.2 | 6,303 | 6.4 | 3,270 | 5.7 | 577 | 7.0 |
| 70 to 74 | 16,926 | 10.4 | 10,385 | 10.6 | 5,567 | 9.8 | 974 | 11.8 |
| 75 to 79 | 23,174 | 14.2 | 14,357 | 14.7 | 7,603 | 13.4 | 1,214 | 14.7 |
| 80+ | 112,841 | 69.2 | 66,912 | 68.3 | 40,456 | 71.1 | 5,473 | 66.4 |
| Medicare buy-in | ||||||||
| No buy-in | 131,557 | 80.7 | 79,257 | 80.9 | 45,627 | 80.2 | 6,673 | 81.0 |
| State buy-in | 31,467 | 19.3 | 18,661 | 19.1 | 11,245 | 19.8 | 1,561 | 18.9 |
| Unknown | 67 | 0.0 | 39 | 0.0 | 24 | 0.0 | 4 | 0.0 |
| Race | ||||||||
| Black | 5,717 | 3.5 | 3,589 | 3.7 | 1,805 | 3.2 | 323 | 3.9 |
| Other | 6,455 | 4.0 | 3,806 | 3.9 | 2,301 | 4.0 | 348 | 4.2 |
| White | 150,919 | 92.5 | 90,562 | 92.5 | 52,790 | 92.8 | 7,567 | 91.9 |
| Sex | ||||||||
| Female | 117,724 | 72.2 | 70,618 | 72.1 | 41,023 | 72.1 | 6,083 | 73.8 |
| Male | 45,367 | 27.8 | 27,339 | 27.9 | 15,873 | 27.9 | 2,155 | 26.2 |
| USA regions | ||||||||
| Midwest | 37,638 | 23.1 | 22,501 | 23.0 | 13,184 | 23.2 | 1,953 | 23.7 |
| Northeast | 30,454 | 18.7 | 18,100 | 18.5 | 10,783 | 19.0 | 1,571 | 19.1 |
| South | 67,592 | 41.4 | 40,778 | 41.6 | 23,449 | 41.2 | 3,365 | 40.8 |
| West | 27,407 | 16.8 | 16,578 | 16.9 | 9,480 | 16.7 | 1,349 | 16.4 |
| Urban-rural | ||||||||
| Metro large | 73,698 | 45.2 | 44,266 | 45.2 | 25,871 | 45.5 | 3,561 | 43.2 |
| Metro medium | 36,051 | 22.1 | 21,652 | 22.1 | 12,537 | 22.0 | 1,862 | 22.6 |
| Metro small | 18,352 | 11.3 | 11,118 | 11.3 | 6,291 | 11.1 | 943 | 11.4 |
| Non-metro large urban | 13,080 | 8.0 | 7,807 | 8.0 | 4,588 | 8.1 | 685 | 8.3 |
| Non-metro small urban | 17,688 | 10.8 | 10,598 | 10.8 | 6,139 | 10.8 | 951 | 11.5 |
| Total rural | 4,165 | 2.6 | 2,480 | 2.5 | 1,452 | 2.6 | 233 | 2.8 |
| Clinical | ||||||||
| Anticoagulant use | ||||||||
| No | 151,796 | 93.1 | 91,161 | 93.1 | 53,062 | 93.3 | 7,573 | 91.9 |
| Yes | 11,295 | 6.9 | 6,796 | 6.9 | 3,834 | 6.7 | 665 | 8.1 |
| COPD | ||||||||
| No | 135,290 | 83.0 | 81,389 | 83.1 | 46,996 | 82.6 | 6,905 | 83.8 |
| Yes | 27,801 | 17.0 | 16,568 | 16.9 | 9,900 | 17.4 | 1,333 | 16.2 |
| Cerebrovascular disease | ||||||||
| No | 140,977 | 86.4 | 84,614 | 86.4 | 49,127 | 86.3 | 7,236 | 87.8 |
| Yes | 22,114 | 13.6 | 13,343 | 13.6 | 7,769 | 13.7 | 1,002 | 12.2 |
| Chronic kidney disease | ||||||||
| No | 141,984 | 87.1 | 85,311 | 87.1 | 49,480 | 87.0 | 7,193 | 87.3 |
| Yes | 21,107 | 12.9 | 12,646 | 12.9 | 7,416 | 13.0 | 1,045 | 12.7 |
| Congestive heart failure | ||||||||
| No | 137,542 | 84.3 | 82,919 | 84.6 | 47,745 | 83.9 | 6,878 | 83.5 |
| Yes | 25,549 | 15.7 | 15,038 | 15.4 | 9,151 | 16.1 | 1,360 | 16.5 |
| Concomitant Fx | ||||||||
| No | 146,471 | 89.8 | 87,746 | 89.6 | 51,223 | 90.0 | 7,502 | 91.1 |
| Yes | 16,620 | 10.2 | 10,211 | 10.4 | 5,673 | 10.0 | 736 | 8.9 |
| Diabetic Dx | ||||||||
| No | 124,818 | 76.5 | 75,401 | 77.0 | 43,292 | 76.1 | 6,125 | 74.4 |
| Yes | 38,273 | 23.5 | 22,556 | 23.0 | 13,604 | 23.9 | 2,113 | 25.6 |
| Fall-related Fx | ||||||||
| No | 134,387 | 82.4 | 80,945 | 82.6 | 46,501 | 81.7 | 6,941 | 84.3 |
| Yes | 28,704 | 17.6 | 17,012 | 17.4 | 10,395 | 18.3 | 1,297 | 15.7 |
| Hypertensive disease | ||||||||
| No | 53,065 | 32.5 | 31,964 | 32.6 | 18,522 | 32.6 | 2,579 | 31.3 |
| Yes | 110,026 | 67.5 | 65,993 | 67.4 | 38,374 | 67.4 | 5,659 | 68.7 |
| Insulin use | ||||||||
| No | 161,317 | 98.9 | 96,952 | 99.0 | 56,239 | 98.8 | 8,126 | 98.6 |
| Yes | 1,774 | 1.1 | 1,005 | 1.0 | 657 | 1.2 | 112 | 1.4 |
| Ischaemic heart disease | ||||||||
| No | 124,648 | 76.4 | 74,975 | 76.5 | 43,326 | 76.1 | 6,347 | 77.0 |
| Yes | 38,443 | 23.6 | 22,982 | 23.5 | 13,570 | 23.9 | 1,891 | 23.0 |
| Morbid obesity | ||||||||
| No | 162,180 | 99.4 | 97,432 | 99.5 | 56,597 | 99.5 | 8,151 | 98.9 |
| Yes | 911 | 0.6 | 525 | 0.5 | 299 | 0.5 | 87 | 1.1 |
| NSAID use | ||||||||
| No | 162,990 | 99.9 | 97,893 | 99.9 | 56,864 | 99.9 | 8,233 | 99.9 |
| Yes | 101 | 0.1 | 64 | 0.1 | 32 | 0.1 | 5 | 0.1 |
| Open Fx | ||||||||
| No | 161,440 | 99.0 | 96,902 | 98.9 | 56,425 | 99.2 | 8,113 | 98.5 |
| Yes | 1,651 | 1.0 | 1,055 | 1.1 | 471 | 0.8 | 125 | 1.5 |
| Opioid use | ||||||||
| No | 162,525 | 99.7 | 97,615 | 99.7 | 56,694 | 99.6 | 8,216 | 99.7 |
| Yes | 566 | 0.3 | 342 | 0.3 | 202 | 0.4 | 22 | 0.3 |
| Osteoporosis Dx | ||||||||
| No | 144,726 | 88.7 | 87,377 | 89.2 | 50,277 | 88.4 | 7,072 | 85.8 |
| Yes | 18,365 | 11.3 | 10,580 | 10.8 | 6,619 | 11.6 | 1,166 | 14.2 |
| Prior osteoporotic Fx | ||||||||
| No | 159,367 | 97.7 | 95,813 | 97.8 | 55,547 | 97.6 | 8,007 | 97.2 |
| Yes | 3,724 | 2.3 | 2,144 | 2.2 | 1,349 | 2.4 | 231 | 2.8 |
| Rheumatoid arthritis | ||||||||
| No | 159,082 | 97.5 | 95,501 | 97.5 | 55,570 | 97.7 | 8,011 | 97.2 |
| Yes | 4,009 | 2.5 | 2,456 | 2.5 | 1,326 | 2.3 | 227 | 2.8 |
| Tobacco dependence | ||||||||
| No | 159,809 | 98.0 | 96,047 | 98.1 | 55,661 | 97.8 | 8,101 | 98.3 |
| Yes | 3,282 | 2.0 | 1,910 | 1.9 | 1,235 | 2.2 | 137 | 1.7 |
| Vehicle-related Fx | ||||||||
| No | 162,842 | 99.8 | 97,827 | 99.9 | 56,799 | 99.8 | 8,216 | 99.7 |
| Yes | 249 | 0.2 | 130 | 0.1 | 97 | 0.2 | 22 | 0.3 |
-
COPD, chronic obstructive pulmonary disease; Dx, diagnosis; Fx, fracture; NSAID, non-steroidal anti-inflammatory drugs.
Union failure
The union failure rate rose from 0.44% (95% confidence interval (CI) 0.40 to 0.49; currently at risk: 65,263) after 12 months to 0.89% (95% CI 0.83 to 0.95; currently at risk: 49,618) after 24 months for head/neck fractures, from 0.45% (95% CI 0.39 to 0.51; currently at risk: 36,967) after 12 months to 0.92% (95% CI 0.84 to 1.01, currently at risk: 27,691) after 24 months for intertrochanteric fractures and from 1.23% (95% CI 1.00 to 1.40, currently at risk: 5,625) after 12 months to 1.99% (95% CI 1.69 to 2.33, currently at risk: 4,380) after 24 months for subtrochanteric fractures (Figure 1). Union failure was significantly less common in patients aged 75 to 79 years (hazard ratio (HR) 0.73 (95% CI 0.63 to 0.84); p < 0.001) and in patients older than 80 years (HR 0.42 (95% CI 0.37 to 0.47); p < 0.001) compared to patients aged 65 to 69 years. Further, in comparison to femoral neck fractures, failure of union was more likely to occur after subtrochanteric fractures (HR 1.54 (95% CI 1.39 to 1.71); p < 0.001). Significant risk factors included cerebrovascular disease, concomitant fracture, congestive heart failure, fall-related fracture, hypertension, osteoporosis, and rheumatoid disease (Table II).
Fig. 1
Risk of proximal femur fracture consolidation failure (malunion or nonunion) as a function of time.
Table II.
Multivariate analysis of risk factors for union failure, fracture-related infection, and mechanical complications after proximal femur fractures.
| Factor | Union failure | Fracture-related infection | Mechanical complications | ||||||
|---|---|---|---|---|---|---|---|---|---|
| HR (95% CI) | χ2 | p-value | HR (95% CI) | χ2 | p-value | HR (95% CI) | χ2 | p-value | |
| Age 70 to 74 yrs | 0.90 (0.78 to 1.04) | 2.06 | 0.151 | 0.83 (0.70 to 0.99) | 4.39 | 0.036 | 0.90 (0.79 to 1.03) | 2.36 | |
| Age 75 to 79 yrs | 0.73 (0.63 to 0.84) | 19.65 | < 0.001 | 0.62 (0.52 to 0.74) | 27.62 | < 0.001 | 0.73 (0.65 to 0.83) | 22.96 | < 0.001 |
| Age 80+ yrs | 0.42 (0.37 to 0.47) | 180.28 | < 0.001 | 0.33 (0.28 to 0.39) | 184.26 | < 0.001 | 0.45 (0.40 to 0.50) | 189.24 | < 0.001 |
| Female sex | 0.98 (0.90 to 1.08) | 0.11 | 0.736 | 1.11 (0.99 to 1.25) | 3.08 | 0.079 | 1.04 (0.96 to 1.13) | 1.06 | 0.302 |
| Anticoagulant use | 1.04 (0.89 to 1.21) | 0.24 | 0.621 | 1.36 (1.15 to 1.61) | 12.60 | < 0.001 | 1.02 (0.89 to 1.17) | 0.11 | 0.735 |
| COPD | 0.95 (0.86 to 1.05) | 1.00 | 0.317 | 0.99 (0.87 to 1.12) | 0.04 | 0.842 | 0.90 (0.82 to 0.98) | 5.25 | 0.022 |
| Cerebrovascular disease | 0.88 (0.79 to 0.99) | 4.57 | 0.033 | 0.81 (0.69 to 0.94) | 7.82 | 0.005 | 0.87 (0.79 to 0.97) | 6.96 | 0.008 |
| Chronic kidney disease | 1.03 (0.91 to 1.16) | 0.21 | 0.643 | 1.08 (0.93 to 1.25) | 0.93 | 0.335 | 0.94 (0.84 to 1.05) | 1.11 | 0.291 |
| Concomitant fracture | 1.20 (1.07 to 1.34) | 9.92 | 0.002 | 1.16 (1.00 to 1.35) | 3.90 | 0.048 | 0.96 (0.86 to 1.07) | 0.49 | 0.483 |
| Congestive heart failure | 0.88 (0.79 to 0.99) | 4.45 | 0.035 | 0.92 (0.80 to 1.06) | 1.35 | 0.245 | 0.83 (0.75 to 0.93) | 11.17 | < 0.001 |
| Diabetes mellitus | 1.01 (0.92 to 1.11) | 0.02 | 0.881 | 1.19 (1.06 to 1.34) | 8.27 | 0.004 | 0.94 (0.86 to 1.02) | 2.06 | 0.151 |
| Fall-related fracture | 0.90 (0.83 to 0.97) | 6.89 | 0.009 | 0.95 (0.85 to 1.06) | 0.93 | 0.335 | 0.90 (0.84 to 0.97) | 8.27 | 0.004 |
| Hypertensive disease | 1.22 (1.11 to 1.33) | 19.17 | < 0.001 | 1.27 (1.13 to 1.43) | 15.88 | < 0.001 | 1.23 (1.14 to 1.33) | 28.21 | < 0.001 |
| Insulin use | 1.17 (0.86 to 1.61) | 0.99 | 0.319 | 1.20 (0.82 to 1.75) | 0.91 | 0.340 | 0.79 (0.55 to 1.14) | 1.57 | 0.211 |
| Ischemic heart disease | 1.04 (0.94 to 1.14) | 0.56 | 0.455 | 1.01 (0.89 to 1.14) | 0.01 | 0.915 | 1.05 (0.96 to 1.15) | 1.15 | 0.283 |
| Morbid obesity | 1.39 (0.96 to 2.01) | 3.00 | 0.083 | 2.84 (2.10 to 3.84) | 46.38 | < 0.001 | 1.28 (0.92 to 1.80) | 2.10 | 0.147 |
| Open fracture | 0.79 (0.58 to 1.07) | 2.39 | 0.122 | 1.41 (1.05 to 1.89) | 5.22 | 0.022 | 1.13 (0.90 to 1.42) | 1.09 | 0.296 |
| Osteoporosis | 1.26 (1.13 to 1.42) | 16.11 | < 0.001 | 0.99 (0.85 to 1.16) | 0.01 | 0.928 | 1.10 (0.99 to 1.23) | 3.41 | 0.065 |
| Rheumatoid disease | 1.34 (1.10 to 1.63) | 8.63 | 0.003 | 1.84 (1.45 to 2.33) | 25.22 | < 0.001 | 1.53 (1.29 to 1.81) | 23.68 | < 0.001 |
| Tobacco dependence | 1.07 (0.85 to 1.35) | 0.32 | 0.573 | 1.02 (0.76 to 1.38) | 0.02 | 0.892 | 1.03 (0.82 to 1.29) | 0.06 | 0.807 |
-
CI, confidence interval; HR, hazard ratio.
Fracture-related infection
For all three fracture types, the occurrence of a fracture-related infection increased with time (Figure 2). The infection rate rose from 0.51% (95% CI 0.46 to 0.55; currently at risk: 90,101) after one month, to 1.59% (95% CI 1.51 to 1.67; currently at risk: 49,449) after 24 months for head/neck fractures, from 0.32% (95% CI 0.28 to 0.37; currently at risk: 52,057) after one month to 1.13% (95% CI 1.05 to 1.23; currently at risk: 27,708) after 24 months for intertrochanteric fractures and from 0.56% (95% CI 0.42 to 0.74; currently at risk: 7,575) after one month to 1.64% (95% CI 1.38 to 1.94; currently at risk: 4,431)) after 24 months for subtrochanteric fractures. A fracture-related infection was more likely to occur after subtrochanteric fractures than after head/neck fractures (HR 1.01 (95% CI 0.87 to 1.17); p < 0.001) as well as after intertrochanteric fractures (HR 1.31 (95% CI 1.12 to 1.52); p < 0.001).
Fig. 2
Risk of fracture-related infections after proximal femur fracture as a function of time.
The occurrence of a fracture-related infection was significantly less common in patients aged 70 to 74 years (HR 0.83 (95% CI 0.70 to 0.99); p = 0.036), in patients aged 75 to 79 years (HR 0.62 (95% CI 0.52 to 0.74); p < .001) and in patients older than 80 years (HR 0.33 (95% CI 0.28 to 0.39); p < 0.001) compared to patients aged 65 to 69 years. Further significant risk factors included anticoagulant use, cerebrovascular disease, a concomitant fracture, diabetes mellitus, hypertension, obesity, open fracture, and rheumatoid disease (Table I).
Mechanical complications
Mechanical complications were also found to increase with time in proximal femoral fractures (Figure 3). The complication rate rose from 1.28% (95% CI 1.21 to 1.3; currently at risk: 89,410) after one month to 3.52% (95% CI 3.41 to 3.64; currently at risk: 48,282) after 24 months for head/neck fractures, from 0.69% (95% CI 0.63 to 0.76; currently at risk: 51,863) after one month to 2.54% (95% CI 2.41 to 2.68; currently at risk: 27,207) after 24 months for intertrochanteric fractures and from 0.72% (95% CI 0.55 to 0.92; currently at risk: 7,562) after one month to 2.98% (95% CI 2.62 to 3.37; currently at risk: 4,351) after 24 months for subtrochanteric fractures. A mechanical complication was more likely to occur after head/neck fractures compared to intertrochanteric fractures (HR 1.35 (95% CI 1.29 to 1.40); p < 0.001) and subtrochanteric fractures (HR 1.20 (95% CI: 1.07 to 1.35); p < 0.001).
Fig. 3
Risk of mechanical complications after proximal femur fracture as a function of time.
The occurrence of a mechanical complication was significantly less common in patients aged 75 to 79 years (HR 0.73 (95% CI 0.65 to 0.83); p < 0.001) and in patients older than 80 years (HR 0.45 (95% CI 0.40 to 0.50); p < 0.001) compared to patients aged 65 to 69 years. Further significant risk factors included COPD, cerebrovascular disease, congestive heart failure, fall-related fracture, hypertension, rheumatoid disease, and poverty (Table I).
Discussion
The present analysis provides an estimation of complication rates after PFF, with its associated risk factors, based on Medicare registry data of elderly patients. Impaired fracture consolidation was reported in 0.89% of head/neck fractures and 0.92% of intertrochanteric fractures after 24 months. Subtrochanteric fractures were associated with a higher risk of union failure (1.99% (95% CI 1.69 to 2.33)). The rates were lower compared to findings in the literature. For instance, a multicentre, randomized trial showed a 21% revision rate after low-energy femoral neck fractures in patients aged over 50 years treated with sliding hip screw or cannulated screws. Further, only 67% of all fractures consolidated fully by 24 months.15 Whereas here, cerebrovascular disease, concomitant fractures, congestive heart failure, fall-related fracture, hypertension, osteoporosis, and rheumatoid disease were determined as risk factors. Other studies have also found female sex, high BMI, and displaced fractures to be a prerequisite for necessary revision surgeries.16,17
The occurrence of a fracture-related infection was reported in 1.59% of head/neck fractures and 1.13% of intertrochanteric fractures after 24 months. Subtrochanteric fractures were associated with a higher risk of infection (1.64% (95% CI 1.38 to 1.94)). A recent meta-analysis of pooled data from 20 studies reporting on 88,615 patients estimating a incidence of 2.1% (95% CI 1.54 to 2.62), whereby infection incidences were higher after hemiarthroplasty (2.87% (95% CI 1.99 to 3.75)) compared to sliding hip screws (1.35% (95% CI 0.78 to 1.93)).18 Comparable infection rates of 1.05% after proximal femoral fractures were also reported.19 Determined risk factors included anticoagulant use, cerebrovascular disease, a concomitant fracture, diabetes mellitus, hypertension, obesity, open fracture, and rheumatoid disease. Other authors also found BMI (p = 0.031), corticosteroid therapy (p = 0.003), and anaemia (p = 0.041), length of hospital stay (15 vs 8 days, p < 0.001), and operating time (117 vs 77 minutes, p < 0.001) as associative factors in the development of an infection.20,21
This study revealed a maximum mechanical complication rate of 3.52% after head/neck fractures. The numbers were considerably lower compared to patients younger than 60 years, for which up to 10% out of 1,600 fractures have been reported.22 Other investigations found 7% mechanical failure rates. 23,24
A limitation of the study is that the data, based on the Medicare 5% sample equivalent to the records from approximately 1.6 million enrollees, are not truly a clinical data set, but administrative claims data. In particular, the coding of surgical therapies is often inaccurate from a surgical perspective and can only describe the exact surgical procedure to a limited extent. Therefore, detailed analysis of treatment concepts was not a focus of the present study. However, it was possible to ensure that all included patients underwent a surgical procedure for fracture fixation. In contrast, it can be assumed that the extensive information on patient characteristics and complications has a high level of quality due to its relevance for reimbursement of costs. In terms of the range of available parameters, the Medicare dataset is characterized by a richness of relevant parameters that is incomparable to other registry data.
In conclusion, despite a prevalence lower than 5%, complications after surgical management of PFFs can be challenging. The determination of complication rates for each fracture type can be useful for informed patient-clinician communication. Risk factors for complications could be identified for distinct PFFs in elderly patients, which are accessible for therapeutical treatment in the management of these complications.
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Author contributions
N. Walter: Conceptualization, Methodology, Validation, Investigation, Writing – Original draft.
D. Szymski: Investigation, Validation, Writing – review & editing.
S. M. Kurtz: Investigation, Validation, Writing – review & editing.
D. W. Lowenberg: Investigation, Validation, Writing – review & editing.
V. Alt: Investigation, Validation, Supervision, Writing – review & editing.
E. C. Lau: Conceptualization, Methodology, Formal analysis, Writing – original draft.
M. Rupp: Conceptualization, Methodology, Validation, Project administration, Supervision, Writing – review & editing.
Funding statement
The authors received no financial or material support for the research, authorship, and/or publication of this article.The authors have no conflict of interest to disclose.
ICMJE COI statement
E. Lau is an employee of Exponent Inc, and S. M. Kurtz holds shares in Exponent Inc, which has been paid fees by companies and suppliers for their consulting services, including Stryker Orthopedics, Ferring Pharmaceutical, Boston Scientific, Medtronic Inc., Sanofi Incs, Ceramtec Inc., Relievant Medsystem Inc., and Alcon Inc.
Data sharing
The data that support the findings for this study are available to other researchers from the corresponding author upon reasonable request.
Ethical review statement
Since the CMS data is deidentified, IRB approval was waived by the ethic committee of the University Hospital Regensburg, Germany. This work was performed in accordance with the Declaration of Helsinki.
Open access funding
Open access funding was provided by the University Regensburg, Germany.
Supplementary material
A table of the ICD-9 and ICD-10 codes of the clinical indicator used.
© 2023 Author(s) et al. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND 4.0) licence, which permits the copying and redistribution of the work only, and provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc-nd/4.0/
