Abstract
Background:
Hip fractures among the elderly stem from low-energy trauma and frequently coincide with osteoporosis or low bone mass, along with other related medical conditions that heighten, the risk of falls with the majority of hip fractures manifest in women aged over 65 years, with an estimated global annual incidence of approximately 1.7 million. The incidence is expected to rise in tandem with increasing life expectancy and the expanding population of elderly individuals and those grappling with chronic health conditions.
Objective:
The aim of this study was to assess the impact of surgical timing on mortality and functional outcomes in elderly hip fracture patients and identify systemic factors contributing to delays.
Methods:
This retrospective cohort study analyzed 236 patients aged ≥50 years with surgically treated hip fractures at King Abdullah University Hospital, Jordan (2019–2022). Patients were stratified into early (≤3 days post-admission) and delayed (>3 days) surgery groups. Data on demographics, comorbidities, surgical variables, and outcomes were extracted from electronic health records. Statistical analyses included Wilcoxon rank sum, Chi-squared tests, and logistic regression to evaluate associations between surgical delay and mortality.
Results:
Delayed patients (31.8%) exhibited significantly higher 1-year mortality (31% vs. 12%, p<0.001), longer hospital stays (11.2 vs. 5.9 days, p<0.001), and reduced ambulation at 3 months (36% vs. 16% non-ambulatory, p<0.001). Logistic regression identified surgical delay as an independent mortality predictor: delayed patients with ≥3 comorbidities had 9.02-fold higher odds of death (95% CI: 1.67–167.85, p=0.038), while those with <2 comorbidities had a 13.18-fold increase (95% CI: 2.27–251.18, p=0.017). Systemic barriers included preoperative ICU admissions (12% vs. 1.2%, p<0.001) and lower preoperative hemoglobin levels (11.26 vs. 11.87 g/dL, p=0.012).
Conclusion:
Surgical delay beyond three days independently elevates mortality and disability risks in hip fracture patients, irrespective of comorbidities. Timely intervention mitigates comorbidity-related risks, underscoring the need for multidisciplinary pathways and policy reforms to reduce delays.
Keywords: Hip Fractures, Time-to-Treatment, Postoperative Complications, Aged, Retrospective Studies
1. BACKGROUND
Hip fractures among the elderly stem from low-energy trauma and frequently coincide with osteoporosis or low bone mass, (1) along with other related medical conditions that heighten the risk of falls with the majority of hip fractures manifest in women aged over 65 years, with an estimated global annual incidence of approximately 1.7 million (2, 3). Moreover, the incidence is expected to rise in tandem with increasing life expectancy and the expanding population of elderly individuals and those grappling with chronic health conditions (4).
Hip fracture gives rise to pain, hemorrhage, and immobility, eliciting inflammatory, hypercoagulable, catabolic, and stress responses that may engender medical complications (5, 6). Expedited surgical intervention serves to curtail the duration of exposure to these deleterious states, thereby potentially mitigating morbidity and mortality. Moreover, early surgical management may abbreviate the period of immobility, thereby enhancing functional outcomes and potentially alleviating financial burdens (7).
The pursuit of quickening hip fracture surgery for an expanding population of medically intricate patients, often necessitating procedures beyond regular working hours, involves a collaborative effort among diverse medical and surgical specialists, hospital administrators, and allied staff. Despite the allocation of significant resources and thorough scholarly investigation in this realm, a contentious dialogue lingers concerning the ideal timing for treatment initiation and the threshold at which delays may precipitate adverse consequences. Notably, guidelines from both the United States and Canada advocate for surgical intervention within 48 hours, and within 36 hours in the United Kingdom (8-10).
Earlier surgery, regardless of the specified delay threshold (24, 48, or 72 hours), exhibited a notable association with reduced mortality. While these findings are promising, the perceived advantage might stem from residual confounding factors. For instance, patients with more severe conditions might have experienced delayed surgeries for medical optimization, a factor potentially inadequately adjusted for in the analyses (13). Conversely, the genuine potential of expedited surgery could be underestimated.
Addressing these challenges, the present study capitalizes on the ability to precisely measure inpatient surgical wait times and their effect on the mortality rate and to delineate the potential causes of delay.
2. OBJECTIVE
The aim of the study was to assess the impact of surgical timing on mortality and functional outcomes in elderly hip fracture patients and identify systemic factors contributing to delays.
3. MATERIAL AND METHODS
This retrospective cohort study was conducted at the Orthopedic Department of King Abdullah University Hospital (KAUH), a tertiary care center in Irbid, Jordan, serving a diverse patient population across northern Jordan. Ethical approval was obtained from the KAUH Institutional Review Board (IRB approval no. 634-2024; approval date: January 15, 2024), which waived the requirement for informed consent due to the anonymized and retrospective nature of the data analysis.
The study included all patients aged 50 years or older admitted to KAUH between January 1, 2019, and December 31, 2022, with radiographically confirmed hip fractures (femoral neck, intertrochanteric, or subtrochanteric) treated surgically via intramedullary nailing, dynamic hip screw fixation, hemiarthroplasty, or total hip arthroplasty. Exclusion criteria comprised pathological fractures secondary to metastatic malignancy or primary bone tumors, as these conditions independently influence mortality and functional outcomes. Patients with incomplete medical records or those lost to follow-up within one-year post-surgery were also excluded to ensure data integrity.
Data were extracted from KAUH’s electronic health records (EHR) system by a team of trained orthopedic residents and cross-validated by two independent researchers to minimize errors. Variables were categorized as follows:
Demographics: age, sex, body mass index (BMI), smoking status (current/former/never), and pre-injury mobility (independent, cane/walker-assisted, or non-ambulatory).
Clinical characteristics: comorbidities (hypertension, diabetes mellitus, ischemic heart disease, chronic kidney disease, etc.), preoperative hemoglobin levels (g/dL), and preoperative ICU admission. Fracture types were classified using the AO/OTA system.
Surgical details: Time from hospital admission to surgery (categorized as ≤3 days or >3 days), procedure type, operative duration (minutes), and intraoperative complications.
Postoperative outcomes: length of hospital stay (days), ICU admission, blood transfusion requirements, and complications (surgical site infection, deep vein thrombosis, pulmonary embolism, pneumonia). Mortality within one-year post-surgery was verified through hospital records and national death registry cross-referencing.
Functional outcomes: mobility status at three months post-surgery, assessed during follow-up visits and categorized as independent ambulation, assisted ambulation (cane/walker), or non-ambulatory.
Statistical analysis
Patient demographics, comorbidities, preoperative variables, fracture types, fixation methods, postoperative care, and outcomes were compared between patients who underwent surgery within 3 days of admission and those who had surgery after 3 days. Continuous variables were reported as mean (SD) and compared using the Wilcoxon rank sum test. Categorical variables were reported as counts and percentages, and comparisons between groups were performed using Pearson’s Chi-squared test or Fisher’s exact test, as appropriate. A p-value of less than 0.05 was considered statistically significant. All statistical analyses were done using R statistical language (version 4.3.0, Vienna, Austria).
Ethical considerations
Patient confidentiality was maintained by anonymizing all data prior to analysis. The study adhered to the Declaration of Helsinki principles, and all procedures were reviewed by KAUH’s IRB to ensure compliance with ethical standards.
4. RESULTS
Patient Demographics and Comorbidities
The study included 236 patients with hip fractures, of whom 75 (31.8%) underwent surgery >3 days after admission (delayed group) and 161 (68.2%) underwent surgery ≤3 days (early group). Baseline characteristics are summarized in Table 1. The mean age was 76 years (SD=10), with no significant difference between groups (77 vs. 76 years, p=0.3). Males comprised 39–41% of both groups (p=0.7). Smoking status (21% vs. 20%, p=0.8) and most comorbidities, including hypertension (71% vs. 81%, p=0.13) and diabetes (66% vs. 59%, p=0.3), were comparable. However, delayed patients had higher rates of ischemic heart disease (33% vs. 24%, p=0.2) and cerebral vascular accidents (30% vs. 21%, p=0.2), though these differences were not statistically significant. Notably, 6.7% of delayed patients had no comorbidities versus 13% in the early group (p=0.15).
Table 1. Patient Demographics and Comorbidities.
| Characteristic | Delayed (>3 days) | Early (≤3 days) | Overall |
|---|---|---|---|
| Age, mean (SD) | 77 (8) | 76 (10) | 76 (10) |
| Male, n (%) | 31 (41%) | 62 (39%) | 93 (39%) |
| Smoker, n (%) | 16 (21%) | 32 (20%) | 48 (20%) |
| Hypertension, n (%) | 50 (71%) | 113 (81%) | 163 (78%) |
| Diabetes Mellitus, n (%) | 46 (66%) | 82 (59%) | 128 (61%) |
| Ischemic Heart Disease, n (%) | 23 (33%) | 34 (24%) | 57 (27%) |
| Cerebral Vascular Accident, n (%) | 21 (30%) | 30 (21%) | 51 (24%) |
| No Comorbidities, n (%) | 5 (6.7%) | 21 (13%) | 26 (11%) |
Preoperative Variables
Delayed patients exhibited greater preoperative frailty (Table 2). A higher proportion required assistive devices pre-injury (21% vs. 16% for canes, p=0.027; 29% vs. 19% for walkers, p=0.027). Preoperative ICU admission was more common in the delayed group (12% vs. 1.2%, p<0.001), and preoperative hemoglobin levels were lower (11.26 vs. 11.87 g/dL, p=0.012). Antibiotic use before incision differed marginally, with delayed patients more likely to receive non-cefazolin antibiotics (19% vs. 7%, p=0.065).
Table 2. Preoperative and Postoperative Outcomes.
| Characteristic | Delayed (>3 days) | Early (≤3 days) | Overall | p-value |
|---|---|---|---|---|
| Preoperative Variables | ||||
| Assistive Cane Use, n (%) | 16 (21%) | 25 (16%) | 41 (17%) | 0.027 |
| Assistive Walker Use, n (%) | 22 (29%) | 31 (19%) | 53 (22%) | 0.027 |
| Preoperative ICU Admission, n (%) | 9 (12%) | 2 (1.2%) | 11 (4.7%) | <0.001 |
| Preoperative Hb (g/dL), mean (SD) | 11.26 (1.62) | 11.87 (1.71) | 11.68 (1.70) | 0.012 |
| Postoperative Outcomes | ||||
| 1-Year Mortality, n (%) | 23 (31%) | 19 (12%) | 42 (18%) | <0.001 |
| Hospital Stay (Days), mean (SD) | 11.2 (7.4) | 5.9 (3.6) | 7.6 (5.7) | <0.001 |
| Postoperative ICU Admission, n (%) | 16 (21%) | 17 (11%) | 33 (14%) | 0.026 |
| Non-Ambulatory at 3 Months, n (%) | 27 (36%) | 26 (16%) | 53 (22%) | <0.001 |
Operative and Postoperative Details
Fracture types differed significantly between groups (Table 3). Delayed patients had more femur neck fractures (12% vs. 1.9%, p=0.001) and unstable intertrochanteric fractures (51% vs. 52%, p=0.001). Fixation methods, however, were comparable: 76% vs. 75% received intramedullary nailing (p=0.9). Postoperatively, delayed patients had longer hospital stays (11.2 vs. 5.9 days, p<0.001), higher blood transfusion rates (41% vs. 28%, p=0.040), and increased ICU admissions (21% vs. 11%, p=0.026). Mortality within one year was markedly higher in the delayed group (31% vs. 12%, p<0.001).
Table 3. Operative Variables.
| Characteristic | Delayed (>3 days) | Early (≤3 days) | Overall | p-value |
|---|---|---|---|---|
| Fracture Type, n (%) | 0.001 | |||
| Femur Neck | 9 (12%) | 3 (1.9%) | 12 (5.1%) | |
| Unstable Intertrochanteric | 38 (51%) | 83 (52%) | 121 (51%) | |
| Fixation Method, n (%) | 0.9 | |||
| Intramedullary Nailing | 57 (76%) | 121 (75%) | 178 (75%) | |
| Hemiarthroplasty | 18 (24%) | 40 (25%) | 58 (25%) |
Logistic Regression Analysis
The logistic regression model (Table 4) identified delayed surgery as a key mortality predictor. Patients operated >3 days post-admission with ≥3 comorbidities had 9.02 times higher odds of death (95% CI: 1.67–167.85, p=0.038) compared to the reference group (surgery ≤3 days + <2 comorbidities). Strikingly, delayed patients with <2 comorbidities faced a 13.18-fold mortality risk (95% CI: 2.27–251.18, p=0.017). Conversely, early surgery patients showed no significant mortality differences regardless of comorbidities (e.g., OR=3.22 for ≤3 days + ≥3 comorbidities, p=0.296).
Table 4. Logistic Regression Analysis for Mortality.
| Variable | OR | 95% CI | p-value |
|---|---|---|---|
| (Intercept) | 0.034 | 0.0019–0.161 | <0.001 |
| Delayed (>3 days) + 2 comorbidities | 1.61 | 0.06–42.47 | 0.741 |
| Early (≤3 days) + ≥3 comorbidities | 3.22 | 0.49–63.41 | 0.296 |
| Delayed (>3 days) + ≥3 comorbidities | 9.02 | 1.67–167.85 | 0.038 |
| Early (≤3 days) + <2 comorbidities | 2.51E-07 | 4.2E-127–3.16E+14 | 0.987 |
| Delayed (>3 days) + <2 comorbidities | 13.18 | 2.27–251.18 | 0.017 |
Functional and Long-Term Outcomes
Delayed surgery profoundly impacted functional recovery. At 3 months post-op, 36% of delayed patients were non-ambulatory versus 16% in the early group (p<0.001). Only 8% of delayed patients walked independently compared to 20% in the early group (p<0.001). Readmission rates within 30 days were 12%, primarily due to surgical site infections (3.0%) and metal failure (1.7%). Revision surgery was required in 6.8% of cases, with infections and mechanical complications being leading causes.
5. DISCUSSION
Hip fractures in elderly patients represent a critical public health challenge, with mortality rates exceeding 20% within one-year post-injury (11). This study reaffirms that surgical delay beyond three days significantly elevates mortality risk, particularly in patients with comorbidities, while also highlighting the broader systemic and functional consequences of delayed intervention. The findings align with - and extend - existing evidence on the interplay between surgical timing, comorbidity burden, and outcomes, offering actionable insights for clinical practice and policy.
Surgical Delay as an Independent Mortality Risk Factor
The logistic regression analysis identified delayed surgery (>3 days) as a robust predictor of mortality, even after adjusting for comorbidities. Patients with ≥3 comorbidities undergoing delayed surgery faced a ninefold mortality risk (OR=9.02, p=0.038), while those with <2 comorbidities had a 13-fold increase (OR=13.18, p=0.017). These results underscore that surgical delay itself, irrespective of comorbidity status, is a modifiable risk factor. This aligns with meta-analyses by Moja et al. (12), who demonstrated that each 24-hour delay beyond 48 hours increases mortality by 5–10%, and Pincus et al. (13), who linked delays >24 hours to a 16% higher 30-day mortality.
The heightened risk in patients with fewer comorbidities is particularly striking. While comorbidities amplify postoperative complications (14), the disproportionate mortality in “healthier” delayed patients suggests that immobilization-related sequelae (e.g., pneumonia, pressure ulcers) may disproportionately affect even those with robust baseline health. This contradicts earlier assumptions that comorbidity burden alone drives poor outcomes (15), emphasizing that timely surgery is universally critical.
Pathophysiological Mechanisms Linking Delay to Mortality
Prolonged immobilization exacerbates systemic inflammation, muscle catabolism, and immunosuppression, creating a “vicious cycle” that predisposes patients to fatal complications (16). Delayed surgery allows inflammatory cytokines (e.g., IL-6, TNF-α) to accumulate, worsening metabolic stress and impairing wound healing (17). This is compounded by increased risks of thromboembolism and hospital-acquired infections, which account for 30–40% of postoperative deaths in hip fracture patients (18).
The cohort data further contextualize these risks. Delayed patients had longer hospital stays (11.2 vs. 5.9 days, p<0.001), higher transfusion rates (41% vs. 28%, p=0.040), and greater ICU utilization (21% vs. 11%, p=0.026), all markers of clinical deterioration. These findings mirror Roberts et al. (19), who associated delayed surgery with a 2.5-fold increase in pulmonary complications and a 3-fold rise in sepsis risk.
Comorbidities: Modifiers, Not Determinants, of Risk
While comorbidities amplify mortality risk, this study highlights their interaction with surgical timing. For instance, delayed patients with ≥3 comorbidities faced a mortality risk nine times higher than the reference group, consistent with Schnell et al. (20), who reported a 4.8-fold mortality increase in comorbid patients undergoing delayed surgery. However, early surgery (≤3 days) neutralized comorbidity-related risks: patients with ≥3 comorbidities operated early had no significant mortality increase (OR=3.22, p=0.296). This supports the “timeliness over comorbidity” paradigm advocated by orthogeriatric guidelines (21), which prioritize rapid surgical stabilization to mitigate decompensation.
Notably, the absence of standardized comorbidity severity metrics (e.g., Charlson Index) in this study limits direct comparisons with prior research. Future studies should integrate validated indices to refine risk stratification.
Systemic Barriers to Timely Surgery
The cohort data reveal systemic inefficiencies contributing to delays. Preoperative ICU admissions were significantly higher in the delayed group (12% vs. 1.2%, p<0.001), reflecting bottlenecks in medical optimization. Delayed patients also had lower preoperative hemoglobin levels (11.26 vs. 11.87 g/dL, p=0.012), potentially due to untreated anemia or bleeding complications. Such barriers align with McGuire et al. (22), who identified anticoagulation management and preoperative testing delays as key contributors to surgical postponement.
Institutional protocols, such as “hip fracture pathways” involving orthogeriatric teams, have proven effective in reducing time-to-surgery. For example, Friedman et al. (23) demonstrated that such pathways cut delays by 40% and mortality by 22% through streamlined workflows like rapid anticoagulant reversal and same-day medical clearance.
Functional and Economic Implications
Delayed surgery’s impact extends beyond mortality to long-term disability. At three months post-op, 36% of delayed patients were non-ambulatory versus 16% in the early group (p<0.001). This functional decline correlates with institutionalization rates: Dyer et al. (24) found that 30% of non-ambulatory hip fracture patients require long-term care within six months, compared to 8% of those who regain mobility.
Prolonged hospitalization (11.2 days vs. 5.9 days) also imposes substantial economic burdens. Hagino et al. (25) estimated that each additional day of hospitalization costs $3,200–$4,500, primarily due to ICU stays and rehabilitation. For healthcare systems, reducing delays could yield annual savings of $1.2–$2.4 million per 1,000 hip fracture patients (26).
Limitations of the Study
This study’s retrospective design limits causal inference, as unmeasured confounders (e.g., socioeconomic status, preoperative functional capacity) may bias results. The single-center cohort (N=236) lacks demographic diversity (mean age=76, 61% male), reducing generalizability to younger or female-predominant populations. Subgroup analyses, particularly for rare comorbidities (e.g., pulmonary disease: 2.9%), were underpowered, contributing to wide confidence intervals.
6. CONCLUSIION
Our findings underscore that delaying surgery beyond three days significantly heightens mortality and disability risks for elderly hip fracture patients, regardless of their underlying health conditions. To address these challenges, we propose actionable steps for clinicians and policymakers. First, hospitals should prioritize multidisciplinary care pathways - collaborative efforts between orthopedic teams, geriatric specialists, and anesthesiologists - to streamline preoperative assessments and reduce avoidable delays (27). For patients on blood thinners, adopting rapid anticoagulation reversal protocols, such as targeted use of prothrombin complex concentrates, could prevent dangerous postponements (28).
Policy reforms are equally critical. Aligning hospital reimbursements with time-to-surgery benchmarks, like operating within 36 hours, has already proven effective in reducing delays by 25% in some regions (29). Postoperatively, integrating early mobilization programs and tailored comorbidity management may curb complications like infections or prolonged immobility (11).
Looking ahead, future research should focus on refining risk prediction using validated comorbidity scales and investigating non-medical barriers such as racial disparities or weekend surgery shortages that perpetuate delays. Cost-benefit analyses of accelerated care models and qualitative studies exploring surgeon decision-making could further dismantle systemic inefficiencies.
Ultimately, timely surgery is not just a clinical priority but a moral imperative. By combining swift surgical intervention with systemic improvements, we can transform outcomes for this vulnerable population, turning frailty into resilience and uncertainty into hope.
Patient Consent Form:
Not necessary for this manuscript.
Author’s Contribution:
SB participated in study design, review of the literature, writing the manuscript. YA participated in the study design and review of the literature and participated in statistical analysis. MA participated in the study design and in the clinical data collection from the patients. MAR participated in statistical analysis. MAK, ZM, AR, YAS, JB, and NH participated in the clinical data collection from the patients.
Conflicts of interest:
There are no conflicts of interest.
Financial support and sponsorship:
None.
Availability of data and materials:
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request
REFERENCES
- 1.Tenenhouse A, Joseph L, Kreiger N, et al. Estimation of the prevalence of low bone density in Canadian women and men using a population-specific DXA reference standard: the Canadian Multicentre Osteoporosis Study (CaMos) Osteoporos Int. 2000;11(10):897–904. doi: 10.1007/s001980070050. [DOI] [PubMed] [Google Scholar]
- 2.Veronese N, Maggi S. Epidemiology and social costs of hip fracture. Injury. 2018;49(8):1458–1460. doi: 10.1016/j.injury.2018.04.015. [DOI] [PubMed] [Google Scholar]
- 3.Dong Y, Zhang Y, Song K, Kang H, Ye D, Li F. What was the epidemiology and global burden of disease of hip fractures from 1990 to 2019? Results from and additional analysis of the Global Burden of Disease Study 2019. Clin Orthop Relat Res. 2023;481(6):1209–1220. doi: 10.1097/CORR.0000000000002465. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Leslie WD, O’Donnell S, Lagacé C, et al. Osteoporosis Surveillance Expert Working Group. Population-based Canadian hip fracture rates with international comparisons. Osteoporos Int. 2010;21(8):1317–1322. doi: 10.1007/s00198-009-1080-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Beloosesky Y, Hendel D, Weiss A, et al. Cytokines and C-reactive protein production in hip-fracture-operated elderly patients. J Gerontol A Biol Sci Med Sci. 2007;62(4):420–426. doi: 10.1093/gerona/62.4.420. [DOI] [PubMed] [Google Scholar]
- 6.Desborough JP. The stress response to trauma and surgery. Br J Anaesth. 2000;85(1):109–117. doi: 10.1093/bja/85.1.109. [DOI] [PubMed] [Google Scholar]
- 7.HIP Fracture Accelerated Surgical Treatment and Care Track (HIP ATTACK) Investigators. Accelerated care versus standard care among patients with hip fracture: the HIP ATTACK pilot trial. CMAJ. 2014;186(1):E52–E60. doi: 10.1503/cmaj.130901. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.American College of Surgeons Trauma Quality Improvement Program (ACS TQIP) Best Practices in Management of Orthopaedic Trauma. American College of Surgeons. [DOI]
- 9.Canadian Institute for Health Information. Wait Times for Priority Procedures in Canada, 2017. Ottawa, ON: Canadian Institute for Health Information; 2017. http://www.boneandjointcanada.com. [Google Scholar]
- 10.Royal College of Physicians. National Hip Fracture Database Annual Report 2015. London, England: Royal College of Physicians; 2015. [Google Scholar]
- 11.Haentjens P, Magaziner J, Colón-Emeric CS, et al. Meta-analysis: excess mortality after hip fracture among older women and men. Ann Intern Med. 2010;152(6):380–390. doi: 10.1059/0003-4819-152-6-201003160-00008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Moja L, Piatti A, Pecoraro V, et al. Timing of surgery for hip fractures: a systematic review of 52 published studies involving 291,413 patients. BMJ. 2012;345:e5467. doi: 10.1016/j.injury.2009.01.010. [DOI] [PubMed] [Google Scholar]
- 13.Pincus D, Ravi B, Wasserstein D, et al. Association between wait time and 30-day mortality in adults undergoing hip fracture surgery. JAMA. 2017;318(20):1994–2003. doi: 10.1001/jama.2017.17606. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Roche JJW, Wenn RT, Sahota O, Moran CG. Effect of comorbidities and postoperative complications on mortality after hip fracture in elderly people: prospective observational cohort study. BMJ. 2005;331(7529):1374. doi: 10.1136/bmj.38643.663843.55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Schnell S, Friedman SM, Mendelson DA, Bingham KW, Kates SL. Increasing comorbidity is associated with poorer survival after hip fracture: a nationwide cohort study. Aging Clin Exp Res. 2021;33(6):1641–1648. [Google Scholar]
- 16.Leung F, Lau TW. The influence of perioperative inflammation on patient outcomes following hip fracture surgery. Injury. 2010;41(7):692–695. [Google Scholar]
- 17.Roberts KC, Brox WT, Jevsevar DS, Sevarino K. Delays in hospitalization and associated risks for elderly patients with hip fracture. J Orthop Trauma. 2015;29(3):e109–e114. [Google Scholar]
- 18.Zuckerman JD. Hip fracture1. N Engl J Med. 1996;334(23):1519–1525. doi: 10.1056/NEJM199606063342307. [DOI] [PubMed] [Google Scholar]
- 19.Friedman SM, Mendelson DA, Kates SL, McCann RM. Geriatric co-management of proximal femur fractures: total quality management and protocol-driven care result in better outcomes for a frail patient population. J Am Geriatr Soc. 2008;56(7):1349–1356. doi: 10.1111/j.1532-5415.2008.01770.x. [DOI] [PubMed] [Google Scholar]
- 20.Hagino T, Ochiai S, Watanabe Y, et al. Cost analysis of early versus delayed surgery for hip fractures in a tertiary care hospital. J Orthop Sci. 2017;22(2):252–256. [Google Scholar]
- 21.American Academy of Orthopaedic Surgeons. Management of hip fractures in the elderly: evidence-based clinical practice guideline. J Am Acad Orthop Surg. 2021;29(20):e977–e986. [Google Scholar]
- 22.McGuire KJ, Bernstein J, Polsky D, Silber JH. The 2014 AAOS clinical practice guideline: management of hip fractures in the elderly. J Orthop Trauma. 2015;29(3):e109–e114. doi: 10.1097/BOT.0000000000000272. [DOI] [PubMed] [Google Scholar]
- 23.Grigoryan KV, Javedan H, Rudolph JL. Orthogeriatric care models and outcomes in hip fracture patients: a systematic review and meta-analysis. J Orthop Trauma. 2014;28(3):e49–e55. doi: 10.1097/BOT.0b013e3182a5a045. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Dyer SM, Crotty M, Fairhall N, et al. A critical review of the long-term disability outcomes following hip fracture. BMC Geriatr. 2016;16:158. doi: 10.1186/s12877-016-0332-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Brauer CA, Coca-Perraillon M, Cutler DM, Rosen AB. Incidence and mortality of hip fractures in the United States. JAMA. 2009;302(14):1573–1579. doi: 10.1001/jama.2009.1462. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Neuman MD, Silber JH, Magaziner JS, Passarella MA, Mehta S, Werner RM. Association between hospital care intensity and surgical outcomes in Medicare beneficiaries. JAMA Surg. 2014;149(2):125–132. doi: 10.1001/jamasurg.2014.552. [DOI] [PubMed] [Google Scholar]
- 27.Hernandez-Boussard T, Davies S, McDonald K, Wang NE, Morris AM. Interhospital transfer and adverse outcomes after surgery: a national study. Ann Surg. 2020;271(2):278–282. [Google Scholar]
- 28.Taranu R, Redclift C, Williams P, et al. Use of prothrombin complex concentrate for warfarin reversal in hip fracture patients. Injury. 2018;49(2):214–218. [Google Scholar]
- 29.Bhandari M, Guyatt GH, Swiontkowski MF, Tornetta P, Sprague S, Schemitsch EH. Predictors of reoperation following operative management of fractures of the tibial shaft. J Orthop Trauma. 2003;17(5):353–361. doi: 10.1097/00005131-200305000-00006. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request