![]()
![]()
![]()
1 Tomislav Matejić
2 Anica Džajić
3 Snježana Kaštelan
4,5 Nikola Gotovac
1 University Hospital Sveti Duh, Zagreb, Croatia
2 Children’s Hospital Srebrnjak, Zagreb, Croatia
3 University Hospital Dubrava, Zagreb, Croatia
4 County General Hospital Požega, Požega, Croatia
5 Faculty of Dental Medicine and Health Osijek,
Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
https://doi.org/10.24141/2/9/2/10
Author for correspondence:
Nikola Gotovac
County General Hospital Požega, Požega, Croatia E-mail: nikolagotovac@net.hr
![]()
Keywords: hip fracture, comorbidities, preoperative preparation, ASA classification, preoperative risk
![]()
![]()
![]()
Results. Urological, neurological, and endocrine comorbidities significantly prolonged preoperative preparation (p<0.05). The number of additional diag- nostic tests was the strongest predictor of prepara- tion duration (p<0.001) and mediated the relation- ship between comorbidity burden and preoperative delay. Higher ASA classification scores were linked to longer preoperative preparation times and more required tests.
cific conditions leading to prolonged hospital stays and increased diagnostic demands. Optimising chron- ic disease management before trauma occurrence may help reduce preoperative delays and improve surgical outcomes.
![]()
![]()
Elderly individuals accounted for 39.6% of all hospi- talised patients in Croatia in 2022, reflecting a slight increase from 38.8% the year before. The average hospital stay decreased slightly from 9.49 to 9.36 days. In geriatric patients, hip fractures were among the most common diagnoses, and in those over 85, they were the leading cause of hospitalisation, high- lighting the significant impact of falls and musculo- skeletal injuries in this age group (1, 2).
Hip fractures account for approximately 30% of all bone fractures in individuals over 50 years of age, with a prevalence three times higher in women. The fracture risk in this population is notably elevated, 5.6% in men and 20% in women, primarily due to os- teoporosis (3-5). Over the next decade, hip fracture incidence is projected to increase by 12% in women and 6.4% in men (4-6). By 2050, this trauma is ex- pected to reach epidemic proportions, with an esti- mated 6 million hip fractures occurring annually in geriatric patients (4, 6).
Hip fractures pose a major public health concern due to their high incidence, associated morbidity and mortality (7). The global rise in hip fractures is largely driven by population aging and increased life expec- tancy (8). Projections indicate a continuing increase in fracture numbers, placing substantial strain on healthcare systems worldwide (9-11). Osteoporotic fractures, including hip fractures, contribute to over 10 million cases annually, imposing significant bur- dens on patients, families, and healthcare infrastruc- tures (7, 9).
Similar to other traumatic injuries, femoral fractures in the hip region are unpredictable and place a signif- icant burden on the bed capacity of healthcare facili- ties due to the need for hospitalisation and intensive treatment. Cost-benefit analyses indicate that these
fractures involve substantial financial expenditure (12, 13). Nearly two-thirds of hip-region femoral fractures are both functionally and biomechanically unstable, necessitating hospital admission, surgical intervention, and a prolonged period of rehabilitation
(14). These injuries are among the most frequently surgically treated traumatic conditions (15). Full re- covery is achieved in only about 25% of cases, while nearly 50% of patients require long-term systemic support. Additionally, around 40% continue to need physical therapy, and approximately 25% remain at risk of sustaining a fracture in the contralateral hip (6, 13).
A crucial aspect of effective management is the patient’s preoperative preparation, which involves comprehensive diagnostic assessments, preventive strategies, and the thorough preparation of both the patient and the surgical field to ensure optimal surgi- cal conditions.
The timing of surgical intervention in hip fractures remains a subject of ongoing debate. In elderly pa- tients with multiple comorbidities, a multidisciplinary evaluation is essential to identify potential contrain- dications related to cardiovascular, respiratory, or neurological function. Nonetheless, early surgical intervention is key to reducing the duration of bed rest and minimizing the risk of complications. Balanc- ing these considerations makes the interval between hospital admission and surgery a critical factor, with important implications for clinical outcomes and healthcare system efficiency (14, 16).
Given the high prevalence of comorbidities in geri- atric patients, surgical treatment must be precise to optimize recovery and maintain the quality of life (15, 17, 18). Following trauma, initial hip fracture diagnosis is performed using primary radiological assessments, followed by preoperative evalua- tion. Standardized laboratory tests and diagnostic procedures are required before anesthesiological clearance for surgery. However, most patients have one or more chronic or acute conditions, which fre- quently delay surgical approval. Additional specialist evaluations and diagnostic tests further extend the time to treatment (13, 19). Prolonged preoperative preparation has negative consequences, including an increased risk of complications related to extended bed rest, such as respiratory infections, urinary tract infections, pain management difficulties leading to distress syndrome, psychomotor disorders, and noso- comial infections. The surge in preoperative examina-
tions also places a considerable burden on diagnostic resources and healthcare personnel, prolonging hos- pital stays, increasing bed occupancy, and leading to substantial financial costs (16, 20).
The healthcare implications of hip fractures are pro- found, involving extended hospitalization, increased rehabilitation needs, and higher healthcare costs
(21). Beyond the economic impact, hip fractures sig- nificantly affect patients’ quality of life, often result- ing in reduced mobility, loss of independence, and psychological distress (20, 22, 23). Understanding the influence of comorbidities on preoperative prepa- ration duration and treatment outcomes remains es- sential for improving patient care (23).
![]()
![]()
This study aimed to examine the number of co- morbidities, the initial anaesthesiological risk as- sessment, and the need for additional diagnostic procedures with the duration of preoperative hospi- talisation in patients undergoing surgical treatment for femoral fractures in the hip region. Furthermore, it investigated how these factors are related to de- lays in surgical interventions and overall length of hospital stay, to identify opportunities to optimise preoperative management and enhance patient outcomes.
![]()
![]()
This retrospective observational research study in- cluded all patients admitted to the Traumatology De- partment through the emergency surgical outpatient clinic of the Emergency Department of the University Hospital Sveti Duh over one year (from January 1st, 2015 to January 1st, 2016), in whom surgical treat-
ment of a radiologically verified femoral fracture in the hip area was indicated. The study was approved by the Ethics Committee of the University Hospital Sveti Duh (approval number 01-3225). Data were collected from the hospital information system data- base, and all participant identities remained anony- mous and protected.
Data were analysed regarding participants’ sex and age, the type and number of comorbidities, Ameri- can Society of Anesthesiologists (ASA) classification
(24) at the initial anaesthesiological assessment, the number of prescribed and performed additional examinations and tests, and the number of days re- quired for preoperative preparation for the planned surgical procedure. The collected data on comorbidi- ties were categorised into seven groups. The cardiac comorbidities group included: hypertension, arrhyth- mias and conduction disorders, history of myocardial infarction, and conditions following coronary artery bypass grafting and stent placement. The neuro- logical comorbidities group comprised Parkinson’s disease, post-stroke with consequent paresis, and various peripheral neuropathies. In the group of uro- logical comorbidities, the following were observed: acute and chronic urinary tract infections, inconti- nence, and prostate hypertrophy.
Pulmonary comorbidities included acute and chronic respiratory infections, asthma, chronic bronchitis, and COPD. In the group of psychiatric comorbidities, the following were found: Alzheimer’s disease, vari- ous degrees of dementia, and psycho-organic syn- dromes. The group of “other” comorbidities included malignant diseases, metastatic fractures, circulatory insufficiency, venous ulcer disease, and autoimmune disorders. A total of 71 patients participated in our one-year study, including 57 women (80.3%) and 14 men (19.7%), which is consistent with epidemiologi- cal findings from other studies (25). The average age of the patients was 82, with the youngest being 59 and the oldest 93.
Of the patients included in the study, only 4.2% had no comorbidities, while the remaining exhibited be- tween one and five comorbid conditions. The most frequently observed was two comorbidities, present in 35.3% of patients, followed by three in 31.0%, one in 22.5%, four in 4.2%, and five comorbidities in 2.8% of cases.
Table 1. Patient demographic and clinical data | ||
Sex | n | (%) |
men | 14 | (19.7) |
women | 57 | (80.3) |
Total | 71 | (100.0) |
Age (years), median (IQR) | 82 | (79-85) |
Comorbidities | ||
cardiac | 51 | (71.8) |
urological | 29 | (40.8) |
endocrinological | 23 | (32.4) |
neurological | 20 | (28.2) |
psychiatric | 13 | (18.3) |
respiratory | 6 | (8.5) |
Other | 9 | (12.7) |
Number of comorbidities, median (IQR) | 2 | (1-3) |
Number of comorbidities, n (%) | ||
0 | 3 | (4,2) |
1 | 16 | (22.5) |
2 | 25 | (35.3) |
3 | 22 | (31.0) |
4 | 3 | (4.2) |
5 | 2 | (2.8) |
ASA classification at initial exam | ||
2 | 19 | (26.8) |
3 | 48 | (67.6) |
3-4 | 4 | (5.6) |
Number of additional tests, median (IQR) | 2 | (1-4) |
Preoperative duration (days), median (IQR) | 4 | (3-6) |
IQR = interquartile range, ASA = American Society of Anesthesiologists | ||
The statistical significance level was set at 5% (p < 0.05), and two-tailed statistical tests were applied to all analyses. The normality of the distribution of con- tinuous variables was tested using the Kolmogorov- Smirnov test for the entire patient set and subsamples larger than 30 patients, and the Shapiro-Wilks test for even smaller samples. Due to deviations from a normal distribution, the median and interquartile range were used to measure central tendency and dispersion. The Mann-Whitney test was employed to compare pa- tients with and without a particular type of comorbid- ity. In the case of statistically significant differences, the AUC (area under the curve) was calculated as a standardised measure of effect size. The point-biserial coefficient was used for dichotomous variables, such as gender, and continuous variables. The simultane- ous contribution of demographic and clinical charac- teristics to predicting the duration of preoperative preparation was examined using multiple linear re- gression analysis. All analyses were performed using the IBM SPSS statistical package. The hypothesis that the number of additional examinations is a mediator of the relationship between the number of comorbidi- ties and the duration of preoperative preparation was tested using the Sobel test implemented in the PRO- CESS macro, version 2.16.3 (26).
![]()
![]()
The study included 71 patients hospitalised at the Traumatology Department through the emergency surgical outpatient clinic of the Center for Emergen- cy Medicine – Central Emergency Department of the University Hospital Sveti Duh over one year, who re- quired surgical treatment of a radiologically verified femoral fracture in the hip area.
The most common comorbidities were cardiac (71.8%), followed by urological (40.8%), endocrino-
logical (32.4%), neurological (28.2%), psychiatric
(18.3%), and “other” conditions (12.7%). Respiratory comorbidities were the least frequent, occurring in 8.5% of patients. The number of prescribed and ad- ditional examinations and tests ranged from none to 16, while the duration of preoperative preparation varied from two to 11 days (Table 1).
The data concerning each type of comorbidity and the total length of preoperative preparation were al- so analysed. The length of preoperative preparation was compared in patients with and without the four most common comorbidities (Table 2).
There was no statistically significant difference in the length of preoperative preparation between pa- tients with and without cardiac comorbidities. On the other hand, the length of preoperative preparation was longer in patients with urological comorbidities (Mann-Whitney U = 406.0; p = 0.016; AUC = 0.33).
In the presence of endocrinological comorbidities, the length of preoperative preparation was longer than in their absence (Mann-Whitney U = 169.0; p < 0.001; AUC = 0.15. Neurological comorbidities also prolonged the preoperative preparation (Mann-Whit- ney U = 253.5; p = 0.001; AUC = 0.25).
Furthermore, the level of ASA classification at the initial anaesthesiology examination was divided into two categories. The first group consisted of patients whose ASA-sum was 2, while the second group con- sisted of patients whose ASA-sum was 3 or 3-4. At the univariate level, it was determined that the number of days spent on preoperative preparation has a statisti- cally highly significant correlation with the number of prescribed and additionally performed examinations and tests, whereby the number of days of prepara- tion increased with the number of additional tests. A greater number of days of preoperative preparation was associated with a greater number of comorbidi- ties and a higher level of ASA classification at the ini-
tial anaesthesiology examination. A greater number of comorbidities was also associated with advanced patient age and a higher level of ASA classification at the initial anaesthesiology examination (Table 3).
Multiple linear regression analysis showed that the demographic and clinical predictor variables exam- ined explained a proportion of the variation in the length of preoperative preparation, which amounted to 82.2% (R² = 0.822; F (5.65) = 60.11; p<0.001).
The analysis showed that the number of prescribed and additionally performed examinations and tests was the only statistically significant predictor of the length of preoperative preparation.
Table 2. Median duration of preoperative care and significance of the presence of specific comorbidities | |||||
Not-present | Comorbidity present | ||||
Comorbidity type | Median | (IQR) | Median | (IQR) | p |
Cardiac | 4.0 | (2.3-6.8) | 4,0 | (3.0-6.0) | 0.871 |
Urological | 4.0 | (2.0-6.0) | 5,0 | (4.0-7.5) | 0.016 |
Endocrinological | 4.0 | (2.0-5.0) | 7,0 | (6.0-10.0) | < 0.001 |
Neurological | 4.0 | (2.0-6.0) | 5,5 | (4.3-9.0) | 0.001 |
IQR = interquartile range; p = statistical significance level; Mann-Whitney U test results | |||||
Table 3. Relation of the duration of preoperative preparation and demographic and clinical predictor variables | ||||||
1 | 2 | 3 | 4 | 5 | 6 | |
1 Preoperative preparation (days) | - | -0.13 | 0.16 | 0.68*** | 0.53*** | 0.90*** |
2 Sex (female) | - | 0.09 | -0.08 | -0.14 | -0.03 | |
3 Age | - | 0.25* | 0.11 | 0.13 | ||
4 Number of comorbidities | - | 0.65*** | 0.75*** | |||
5 ASA classification at initial anesthesiological exam 3 or 3-4 | - | 0.51*** | ||||
6 Number of additional tests | - | |||||
* p < 0.05 ** p < 0.01 *** p < 0.001 | ||||||
Table 4. Regression Analysis of the duration of Preoperative Preparation Based on Demographic and Clinical Characteristics | |||||
B | SE B | β | t | p | |
Age | 0.03 | 0.02 | 0.06 | 1.12 | 0.266 |
Number of comorbidities | -0.20 | 0.23 | -0.08 | -0.88 | 0.383 |
ASA classification at initial anesthesiological exam 3 or 3-4 | 0.63 | 0.41 | 0.11 | 1.53 | 0.130 |
Number of additional tests | 0.780 | 0.07 | 0.89 | 11.28 | < 0.001 |
B = non standardised (raw) regression coefficient; SE B = standard error of regression coefficient; β = standardised regression coefficient | |||||
Furthermore, even after adjusting for other predic- tors in the regression model, more prescribed and performed examinations and tests remained sig- nificantly associated with a prolonged preoperative preparation period (Table 4).
Although the number of comorbidities was statisti- cally significantly associated with the length of pre- operative preparation at the univariate level (Table 3), this relationship was not statistically significant when other variables were considered in the multi- variate prediction. At the univariate level, the num- ber of comorbidities was highly correlated with the number of additional examinations (r = 0.75), so the possibility that the number of comorbidities affects the length of preoperative preparation due to the number of additional examinations was considered. In other words, the mediation hypothesis was tested where the number of comorbidities influences the length of preoperative preparation through the num- ber of additional examinations.
In the first step, the relationship between the num- ber of additional examinations and the number of comorbidities was examined using multiple linear regression, controlling for gender, age, and level of anaesthesia risk, and it was found that the number of comorbidities statistically significantly contribut- ed to the prediction of the number of additional ex- aminations (B=2.04; SE B=0.31; t=6.65; p<0.001). In
the second step, the indirect effect of the number of comorbidities on the length of preoperative prepara- tion was analysed using the Sobel test, while con- trolling for other variables included in the analysis. The analysis revealed that this indirect effect is sta- tistically significant (z=5.71; SE z=0.28; p<0.001), thus confirming the mediation hypothesis.
In other words, it was determined that the number of additional examinations is a mediator, or an interven- ing variable, in the relationship between the number of comorbidities and the duration of preoperative preparation. A higher number of comorbidities leads to additional examinations, which in turn prolong the duration of preoperative preparation.
![]()
![]()
Hip fractures in elderly patients represent a signifi- cant global health concern, particularly due to the high prevalence of comorbidities that complicate pre- operative preparation, surgical procedures, and post- operative recovery (19, 27). The presence of multiple chronic conditions prolongs the time required for pre- operative optimisation and increases the risk of com- plications, leading to worse treatment outcomes and higher healthcare costs (10, 28-31). Optimising the management of comorbidities before the occurrence of trauma could help reduce the duration of preop- erative preparation and potentially improve the sur- gical outcomes for hip fracture treatment in elderly patients (32, 33).
Analysis of the collected data showed that cardiac co- morbidities were the most common, affecting 71.8% of patients, a finding consistent with other studies (34, 35). Urological comorbidities were also common, present in 40.8% of patients, followed by endocrin- ological (32.4%), neurological (28.2%), psychiatric
(18.3%), and “other” comorbidities (12.7%). Respira- tory comorbidities were the least frequent, affecting 8.5% of patients. These findings align with those ob- served in similar studies (36). The high percentage of cardiac comorbidities was to be expected, most likely due to the advanced age of the participants.
Data analysis was focused on the relationship be- tween the occurrence of each type of comorbidity and the total length of preoperative preparation. The preoperative preparation duration was compared between patients with and without the four most common comorbidities. The analysis revealed no statistically significant difference in the length of preoperative preparation for patients with cardiac comorbidities compared to those without such con- ditions. However, urological comorbidities (p=0.016) and neurological comorbidities (p=0.001) were sig- nificantly connected to the length of preoperative preparation. Endocrinological comorbidities had the most pronounced statistically significant relation to the length of preoperative preparation (p<0.001).
The number of prescribed and additional examina- tions and tests ranged from none (0) to 16. The dura- tion of preoperative preparation varied from two to 11 days, with a typical range of three to six days. In
our study, the duration of preoperative preparation is similar to the average duration of preoperative prep- aration in published studies (37-41).
Through multiple linear regression analysis, it was determined that a statistically significant proportion of the variation in the length of preoperative prepa- ration could be explained based on the investigated clinical predictor variables (p<0.001) and that the number of prescribed and additionally performed ex- aminations and tests is the only statistically signifi- cant predictor of the length of preoperative prepara- tion. After controlling for other predictor variables in the regression model, more prescribed and addition- ally performed examinations and tests were associ- ated with a longer preoperative preparation time.
This study has several limitations. The retrospective, single-center observational design and the moderate sample size may introduce potential biases. These biases could be mitigated by extending the study pe- riod to account for seasonal variations, which may in- fluence the incidence of hip fractures. Furthermore, changing the design and adding more locations could improve results of the study.
![]()
![]()
This study demonstrates that comorbidities in patients with hip fractures pose a significant challenge in the implementation of preoperative preparation, thereby affecting the overall surgical treatment process. The length of preoperative preparation was found to in- crease statistically significantly in patients with a higher ASA classification at the initial anaesthesiol- ogy examination, in those with endocrinological, uro- logical, and neurological comorbidities, and in patients prescribed additional tests due to uncontrolled comor- bidities and a high ASA classification.
Conceptualization and methodology (TM, SK, ADŽ); Data curation and formal analysis (TM, NG); investi- gation and project administration (TM, ADŽ, NG); and Writing – original draft and review & editing (TM, SK, NG). All authors have approved the final manuscript.
The authors declare no conflicts of interest.
Not applicable.
This research did not receive any specific grant from funding agencies in the public, commercial, or not- for-profit sectors.
![]()
![]()
Croatian Institute of Public Health. Croatian Health Statistical Yearbook for 2022 [Internet]. Morbidity and causes of death in the elderly. Available at: http// www.hzjz.hr/periodicne-publikacije/hrvatski-zdrav- stveno-statisticki-ljetopis-za-2022. Accessed: 29. 1.
2025.
Abelleyra Lastoria DA, Benny CK, Smith T, Hing CB. Outcomes of hip fracture in centenarians: a syste- matic review and meta-analysis. Eur Geriatr Med. 2023 Dec;14(6):1223-39. https://doi.org/10.1007/ s41999-023-00866-y
Piirtola M, Vahlberg T, Isoaho R, Aarnio P, Kivela SL. In- cidence of fractures and changes over time among the aged in a Finnish municipality: a population-based 12-ye- ar follow-up. Aging Clin Exp Res. 2007;19(4):26976. https://doi.org/10.1007/BF03324701
Cooper C, Campion G, Melton LJ. Hip fractures in the elderly; a world-wide projection. Osteoporos Int. 1992;2(6):285-
9. https://doi.org/10.1007/BF01623184
Fraser LA, Langsetmo L, Berger C, Ioannidis G, Goltz- man D, Adachi JD, et al. Fracture prediction and calibra- tion of a Canadian FRAX® tool: a population-based re- port from CaMos. Osteoporos Int. 2011;22(3):82937. https://doi.org/ 10.1007/s00198-010-1465-1
Branco JC, Felicissimo P, Monteiro J. Epidemiology of hip fractures and its social and economic impact. A re- vision of severe osteoporosis current standard of care. Acta Reumatol Port. 2009;34(3):475-85.
Zeng Z, Li H, Luo C, Huang MD, Li HP, Peng X, et al. Risk factors associated with mortality in elderly patients receiving hemiarthroplasty for femoral neck fractures. BMC Musculoskelet Disord. 2025 Apr 16;26(1):373. https://doi.org/10.1186/s12891-025-08620-0. PMID: 40241076
Cram P. CORR Insights®: 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):1221-3. https://doi. org/10.1097/CORR.0000000000002511
GBD 2019 Fracture Collaborators. Global, regional, and national burden of bone fractures in 204 countri- es and territories, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019. Lan- cet Healthy Longev. 2021;2(9):e580-e592. https:// doi.org/10.1016/S2666-7568(21)00172-0
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 Addi- tional Analysis of the Global Burden of Disease Study 2019. Clin Orthop Relat Res. 2023;481(6):1209-20. https://doi.org/10.1097/CORR.0000000000002465
Borgström F, Karlsson L, Ortsäter G, Norton N, Halbout P, Cooper C, et al. Fragility fractures in Europe: bur- den, management and opportunities. Arch Osteopo- ros. 2020 Apr 19;15(1):59. https://doi.org/10.1007/ s11657-020-0706-y
Sing CW, Lin TC, Bartholomew S, Bell JS, Bennett C, Beyene K, et al. Global Epidemiology of Hip Fractu- res: Secular Trends in Incidence Rate, Post-Fractu- re Treatment, and All-Cause Mortality. J Bone Miner Res. 2023;38(8):1064-75. https://doi.org/10.1002/ jbmr.4821
Alolabi B, Bajammal S, Shirali J, Karanicolas P, Gaf- ni A, Bahandari M. Treatment of displaced femoral neck fractures in the elderly: a cost-benefit analysis. J Orthop Trauma 2009;23(6):442-6. https://doi. org/10.1097/BOT.0b013e31817614dd
Liu F, Chang WJ, Wang X, Gong R, Yuan DT, Zhang YK, et al. Risk factors for prolonged preoperative waiting time of intertrochanteric fracture patients undergoing operative treatment. BMC Musculoskelet Disord. 2022 Oct 13;23(1):912. https://doi.org/10.1186/s12891- 022-05865-x.
Court-Brown CM, Heckman JD, McQueen MM, Ricc WM, Torretta P. Rockwood and Green’s Fractures in Adults. 8th ed. Philadelphia: Wolters Kluwer; 2015.
Rozenfeld M, Bodas M, Shani M, Radomislensky I, Murad H, Comaneshter D, et al. National study: Most elderly patients benefit from earlier hip fracture sur- gery despite co-morbidity. Injury. 2021;52(4):905–9. https://doi.org/ 10.1016/j.injury.2020.10.060
Forte ML, Virnig BA, Eberly LE et al. Provider factors asso- ciated with intramedullary nail use for intertrochanteric hip fractures. J Bone Joint Surg Am 2010;92(5):1105-
14. https://doi.org/10.2106/JBJS.I.00295
Borgström F, Karlsson L, Ortsäter G, Norton N, Halbout P, Cooper C, et al. Fragility fractures in Europe: bur- den, management and opportunities. Arch Osteopo- ros. 2020 Apr 19;15(1):59. https://doi.org/10.1007/ s11657-020-0706-y
Đozić H, Bišćević M, Muharemović T, Žujo S, Kukuljac A, Skopljak E. The Predictive Values of the Functional Status, Comorbidities, and the Types of Treatment on the Treatment Outcomes in Elderly Patients Follow- ing the Hip Fracture. Acta Chir Orthop Traumatol Cech. 2022;89(3):199-203.
Schrøder CK, Hjelholt TJ, Møller H, Madsen M, Pedersen AB, Kristensen PK. Comorbidity and Quality of In-Hos- pital Care for Hip Fracture Patients. J Am Med Dir As- soc. 2022;23(4):671-7.e4. https://doi.org/10.1016/j. jamda.2022.01.078
Yoon SH, Kim BR, Lee SY, Beom J, Choi JH, Lim JY. Influence of comorbidities on functional outcomes in patients with surgically treated fragility hip fractures: a retro- spective cohort study. BMC Geriatr. 2021;21(1):283. https://doi.org/10.1186/s12877-021-02227-5
Loggers SAI, Willems HC, Van Balen R, Gosens T, Polin- der S, Ponsen KJ, et al. Evaluation of Quality of Life Af- ter Nonoperative or Operative Management of Proximal Femoral Fractures in Frail Institutionalized Patients: The FRAIL-HIP Study. JAMA Surg. 2022;157(5):424-34.
https://doi.org/10.1001/jamasurg.2022.0089
Kang MJ, Kim BR, Lee SY, Beom J, Choi JH, Lim JY. Factors predictive of functional outcomes and quality of life in patients with fragility hip fracture: A retrospective co- hort study. Medicine (Baltimore). 2023;102(7):e32909. https://doi.org/10.1097/MD.0000000000032909
Kivrak S, Haller G. Scores for preoperative risk eva- luation of postoperative mortality. Best Pract Res Clin Anaesthesiol. 2021;35(1):115-34. https://doi. org/10.1016/j.bpa.2020.12.005
Skala-Rosenbaum J, Bartoniček J, Riha D, Waldauf P, Džupa V. Single-centre study of hip fractures in Prague, Czech Republic, 1997-2007. Int orthop 2011;35:587-
93. https://doi.org/10.1007/s00264-010-0984-x
Hayes, AF. Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: The Guilford Press, 2013.
Selaković I, Mandić-Rajčević S, Milovanović A, Toma- nović-Vujadinović S, Dimitrijević S, Aleksić M, et al. Pre-Fracture Functional Status and Early Functional Recovery are Significant Predictors of Instrumental Activities of Daily Living After Hip Fracture: A Pros- pective Cohort Study. Geriatr Orthop Surg Rehabil. 2024 May 16;15:21514593241255627. https://doi. org/10.1177/21514593241255627
Sameer M, Muthu S, Vijayakumar PC. Enhanced Re- covery After Surgery (ERAS) Protocol in Geriatric Hip Fractures: An Observational Study. Cureus. 2023 Jul 18;15(7):e42073. https://doi.org/10.7759/cure- us.42073
Chandrupatla SR, Singh JA. Medical Comorbidity and Male Sex Are Associated With Higher In-hospital Mor- tality for 90-Day Readmissions and Higher Readmissi- on Rates After Nonelective Primary Total Hip Arthro- plasty for Hip Fracture. J Clin Rheumatol. 2025 Apr 17. https://doi.org/10.1097/RHU.0000000000002236
Han X, Han L, Chu F, Liu B, Song F, Jia D, et al. Pre- dictors for 1-year mortality in geriatric patients following fragile intertrochanteric fracture surgery. J Orthop Surg Res. 2024 Oct 30;19(1):701. https://doi. org/10.1186/s13018-024-05219-4
Bhatti UF, Shah AA, Williams AM, Biesterveld BE, Oka- for C, Ilahi ON, et al. Delay in Hip Fracture Repair in the Elderly: A Missed Opportunity Towards Achieving Better Outcomes. J Surg Res. 2021 Oct;266:142-7. https://doi.org/10.1016/j.jss.2021.03.027
Williams CT, Whyman J, Loewenthal J, Chahal K. Mana- ging Geriatric Patients with Falls and Fractures. Ort- hop Clin North Am. 2023 Jul;54(3S):e1-e12. https:// doi.org/10.1016/j.ocl.2023.04.001
González de Villaumbrosia C, Barba R, Ojeda-Thies C, Grifol-Clar E, Alvarez-Diaz N, Alvarez-Espejo T, et al. Pre- dictive factors of gait recovery after hip fracture: a sco- ping review. Age Ageing. 2025 Mar 3;54(3):afaf057. https://doi.org/10.1093/ageing/afaf057
Ali AM, Gibons CE. Predictors of 30-day hospital re- admission after hip fracture: a systematic review. Injury 2017;48(2):243-52. https://doi.org/10.1016/j. injury.2017.01.005
Kristensen PK, Hjelholt TJ, Madsen M, Pedersen AB. Current Trends in Comorbidity Prevalence and Asso- ciated Mortality in a Population-Based Cohort of Hip Fracture Patients in Denmark. Clin Epidemiol. 2023 Jul 18;15:839-53. https://doi.org/10.2147/CLEP.S410055
Nicholas JA. Preoperative optimization and risk asse- ssment. Clin Geriatr Med. 2014;30:207-18. https:// doi.org/10.1016/j.cger.2014.01.003
Herron J, Hutchinson R, Lecky F, Bouamra O, Edwar- ds A, Woodford M, et al. The impact of age on ma- jor orthopaedic trauma: an analysis of the United Kingdom Trauma Audit Research Network databa- se. Bone Joint J. 2017; 99B:167780. https://doi.org/ 10.1302/0301-620X.99B12.BJJ-2016-1140.R2
Haq ZA, Murthy P, Malik I, Lahori VU, Chaudhary S, Ahuja S. Detection of comorbid illnesses during pre- anaesthesia evaluation in a university teaching hos- pital: A prospective observational study. Natl Med J India. 2014; 27 :256-8.
Brown CA, Olson S, Zura R. Predictors of length of hospital stay in elderly hip fracture patients. J Surg Orthop Adv. 2013;22:160-3. https://doi.org/10.3113/ jsoa.2013.0160
Reguant F, Arnau A, Lorente JV, Maestro L, Bosch J. Ef- ficacy of a multidisciplinary approach on postopera- tive morbidity and mortality of elderly patients with hip fracture. J Clin Anesth. 2019;53:11–9. https://doi. org/10.1016/j.jclinane.2018.09.029
Tewari P, Sweeney BF Jr, Lemos JL, Shapiro L, Gard- ner MJ, Morris AM, et al. Evaluation of Systemwide Improvement Programs to Optimize Time to Surgery for Patients With Hip Fractures: A Systematic Review. JAMA Netw Open. 2022;5(9):e2231911. https://doi. org/10.1001/jamanetworkopen.2022.31911