header advert
The Bone & Joint Journal Logo

Receive monthly Table of Contents alerts from The Bone & Joint Journal

Comprehensive article alerts can be set up and managed through your account settings

View my account settings

Full Access

Trauma

The determinants of mortality and morbidity during the year following fracture of the hip

a prospective study



Download PDF

Abstract

Several studies have reported the rate of post-operative mortality after the surgical treatment of a fracture of the hip, but few data are available regarding the delayed morbidity. In this prospective study, we identified 568 patients who underwent surgery for a fracture of the hip and who were followed for one year. Multivariate analysis was carried out to identify possible predictors of mortality and morbidity. The 30-day, four-month and one-year rates of mortality were 4.3%, 11.4%, and 18.8%, respectively. General complications and pre-operative comorbidities represented the basic predictors of mortality at any time interval (p < 0.01). In-hospital, four-month and one-year general complications occurred in 29.4%, 18.6% and 6.7% of patients, respectively. After adjusting for confounding variables, comorbidities and poor cognitive status determined the likelihood of early and delayed general complications, respectively (p < 0.001). Operative delay was the main predictor of the length of hospital stay (p < 0.001) and was directly related to in-hospital (p = 0.017) and four-month complications (p = 0.008).

Cite this article: Bone Joint J 2015;97-B:383–90

Fractures of the hip fractures are a worldwide health problem. There have been several studies reporting the rates and risk factors that result in mortality following this injury.1-7 Fractures of the hip might not result in immediate death, but can induce a progressive deterioration in the patient’s health, leading to an increased risk of mortality over a period of time.8 The complications have generally been reported as short-term adverse events.6,9-13 The few studies that have investigated the outcome with a follow-up of one year have focused on functional outcome and mobility,2,14-17 but not on the delayed complications or associated medical conditions. Identifying the causes of the longer-term adverse events might help reduce preventable deaths.18 The aims of this study were to evaluate the complications and rates of mortality in elderly patients at four and twelve months after the surgical treatment of a fracture of the hip, and to ascertain which factors may predict outcome.

Patients and Methods

This prospective multicentre observational study involved all consecutive patients with a fracture of the hip who were admitted to our institutions between January 2011 and April 2012. There were initially 606 patients. Inclusion criteria were age ≥ 50 years and a history of low-energy trauma. Patients with a pathological fracture (14) and those treated conservatively (24) were excluded. This left 568 patients available for review one-year post-operatively. The study had ethical approval and all patients gave informed consent. Sociodemographic data including level of education and living situation, height and weight, medical history and whether they were smokers, were collected. In those patients who were cognitively impaired, information was obtained from either the partner or a close relative. Pre-fracture mobility was recorded using a five-item scale that ranged from grade 1 (unable to walk) to grade 5 (no need for walking aids).19 The activities of daily living (ADL) index20 was used to assess function. A score of 6 indicates full function and 1 indicates the most severe functional impairment. Cognitive status was assessed using the mini-mental state examination (MMSE)21 and comorbidities using the cumulative illness rating scale (CIRS).22 The MMSE consists of questions grouped into seven categories, each representing a different cognitive domain. The maximum score is 30 and any score ≥ 27 indicates normal cognition. The CIRS contains 13 items for different organ systems, and each system is rated in five levels of increasing impairment. Interviews were carried out by three authors (PR, EA, MG) who were unaware of the pattern of the fracture. The baseline characteristics of the patients are shown in Table I. All fractures were classified on anteroposterior (AP) and lateral radiographs by two orthopaedic surgeons (GGC, SC), who were unaware of the clinical characteristics of the patients, into femoral neck, trochanteric and subtrochanteric fractures. The pattern was further defined using the AO classification23 for trochanteric fractures, and both the AO and the Garden24 classifications for fractures of the femoral neck. The intra- and interobserver reliability of the classification of the fractures was tested using Cohen’s κ coefficient (Table II).

Table I

Baseline characteristics of patients

Patient data Mean (range) or No. (%)
Age 78.3 (50 to 105)
Gender
Females 439 (77.3)
Males 129 (22.7)
BMI 25.3 (15.2 to 44.4)
Educational level
Illiteracy 41 (7.2)
Primary School 278 (48.9)
Secondary School 106 (18.7)
High School 102 (18.0)
Graduation 41 (7.2)
Smoking habit 88 (15.5)
ASA grade
1 16 (2.8)
2 108 (19.0)
3 335 (59.0)
4 104 (18.3)
5 5 (0.9)
Pre-fracture treatment for osteoporosis 143 (25.2)
CIRS score 7.8 (0 to 18)
Dementia 118 (20.8)
Diabetes mellitus 135 (23.8)
MMSE score 21.7 (0 to 30)
Pre-fracture living situation
Needs nursing care 43 (7.6)
Needs full-time home help 101 (17.8)
Lives with spouse or relatives 314 (55.3)
Lives alone 110 (19.4)
Pre-fracture ADL Index
  1 35 (6.2)
  2 25 (4.4)
  3 43 (7.6)
  4 42 (7.4)
  5 73 (12.9)
  6 350 (61.6)
Pre-fracture mobility
Unable to walk 1 (0.2)
Requires accompaniment 38 (6.7)
Two aids/frame unaccompanied 35 (6.2)
One aid, unaccompanied 96 (16.9)
No aids, unaccompanied 398 (70.1)
  1. BMI, body mass index; ASA, American Society of Anesthesiologists; CIRS, cumulative illness rating scale; MMSE, mini mental state examination; ADL, activities of daily living

Table II

Κ coefficients for intra- and inter-observer reliability

Intra-observer reliability Inter-observer reliability
Neck fractures AO classification23 0.61 0.48
Garden classification24 0.55 0.45
Trochanteric fractures AO classification23 0.77 0.68

Pre-operative levels of haemoglobin (Hb), the American Society of Anaesthesiologists (ASA)25 grade, the time to surgery, the type of surgery (arthroplasty or osteosynthesis), in-hospital general or hip-related complications and length of hospital stay were recorded at discharge. In-hospital complications were further divided into major and minor, based on the perceived impact on outcome and survival. Follow-up information was available for 552 patients (97.2%). A telephone interview at four and 12 months post-operatively was used to collect data from the patients or, where necessary, from their relatives or carers. Information was collected regarding possible implant and medical complications, as well as re-operations that took place in the previous time interval. When a complication or re-operation was reported, the family physician was contacted for further information. For each deceased patient, the precise date of death was obtained. A total of 16 patients were lost to follow-up and were excluded from the analysis.

Statistical analysis

The Kaplan–Meier method was used to estimate the probability of survival one year after surgery in patients of two age groups (< 80 years, 264 patients vs ≥ 80 years, 288 patients). The intergroup comparison was performed using the log-rank test. Age-adjusted univariate and multivariate Cox’s regression analysis was performed to evaluate the effect of any explanatory variables on 30-day and one-year mortality. An age-adjusted univariate and forward stepwise multiple logistic regression analysis was used to determine whether these variables were significantly associated with complications and re-operations. An age-adjusted univariate and forward stepwise linear regression analysis was used to assess the association of independent variables with the length of hospital stay. Coefficients from the length of hospital stay model represented the changes in number of days of hospital stay attributable to the effect of each explanatory variable inserted in the model. For all the outcomes, and before constructing the models of multivariate analysis, an age-adjusted univariate analysis was performed. All explanatory variables that showed either an association or a trend towards an association (i.e. p < 0.10) with the outcome of interest in the univariate analysis were included in multiple regression models. The chi-squared difference was used to evaluate the improvement in the model fit after the single predictors were introduced into the multiple Cox’s and logistic regression analyses. In the multiple stepwise linear regression analysis, the total R2 for the model and changes in R2 for the independent contribution of single explanatory variables were calculated to assess the percentage of total variance in the outcome variable, which were accounted for by the whole model and by single explanatory variables, respectively. A p ≤ 0.05 was considered significant. Data were analysed using SPSS version 17.0 (SPSS, Chicago, Illinois).

Results

The classification of the fractures and surgical features of the patients are summarised in Table III. The 30-day, four-month and one-year rates of mortality were 4.3% (24/552), 11.4% (63/552) and 18.8% (104/552), respectively. The rate of mortality at 30 days included in-hospital deaths (11 patients) and deaths that occurred between discharge from hospital and 30 days after surgery (13 patients). The Kaplan–Meier survival curves for the two age groups showed an increased mortality in patients aged ≥ 80 years compared with the younger age group (Fig. 1). There was no significant difference in the 30-day rate of mortality between these two groups (< 80; 10/264, 3.8% vs > 80; 14/288, 4.9%; p = 0.537). However, there was a significantly increased rate of mortality one year post-operatively in the older age group (< 80; 33/264, 12.5% vs > 80; 71/288, 24.7%; p < 0.001). Table IV shows age-adjusted hazard ratios for single variables associated with mortality. There was a positive association between male gender and the 30-day and one-year rate of mortality. The determinants of mortality revealed by the multivariate Cox’s regression analysis are shown in Table V. Complications that had occurred within the previous time interval and the ASA grade represented the two most important predictors. In the model including patients aged < 80, the strongest predictors of 30-day and one-year mortality were ASA grade and the mobility four months post-operatively, respectively. In the model in which only patients aged ≥ 80 years were selected, complications that had occurred within the previous time interval represented by far the most important predictor of mortality at both time intervals. Complications and medical conditions following the fracture are shown in Table VI. In-hospital, four-month and one-year general complications occurred in 167 (29.4%), 91 (18.6%) and 30 (6.7%) patients, respectively. During their hospital stay, many developed several complications. Factors significantly influencing the development of complications and medical conditions are shown in Table VII. Using multivariate analysis, the occurrence of pressure sores was inversely related to the MMSE score (odds ratio (OR) 0.90; 95% confidence interval (CI) 0.87 to 0.94; p < 0.001) and to surgery performed within 72 hours (OR 0.53; 95% CI 0.30 to 0.93; p = 0.028), whereas it was directly associated with ASA grade (OR 2.41; 95% CI 1.40 to 4.14; p = 0.001). The MMSE score was the single most important predictor in this model. With the numbers available, no predictors of hip-related complications at any time were identified by multivariate analysis, even when patients treated with osteosynthesis or prosthesis were examined separately. Using multiple linear regression analysis, the length of stay was directly associated with in-hospital general complications (coefficient (c) = 1.47; p < 0.001), the use of a prosthesis vs osteosynthesis (c = 1.70; p < 0.001) and male gender (c = 1.97; p < 0.001), whereas surgery carried out within 72 hours (c= -4.17; p < 0.001) and the mean pre-operative Hb level (c = -0.43; p < 0.001) represented inverse predictors. The model accounted for 36% of the total variance in the length of hospital stay, with a short operative delay contributing 26%. A reoperation was reported by 15 patients (3.0%) at four months and by 13 (2.9%) one-year post-operatively. The BMI (OR 1.12; 95% CI 1.03 to 1.22; p = 0.009) was a weak direct predictor of the likelihood of re-operation, whereas the type of fracture and the type of surgery were not predictive. The pre-fracture treatment for osteoporosis was not associated with reported re-operations at follow-up.

Fig. 1 
          Graph showing survival curves after
hip fracture in two age groups (<
 80 years and ≥ 80).

Fig. 1

Graph showing survival curves after hip fracture in two age groups (< 80 years and ≥ 80).

Table III

Fracture classification and surgical features of patients

Variable n (%)
Femoral neck fractures 241 (42.4)
AO type 31B1 34 (14.1)
31B2 99 (41.1)
31B3 108 (44.8)
Garden type I 20 (8.3)
II 17 (7.1)
III 117 (48.5)
IV 87 (36.1)
Trochanteric fractures 311 (54.8)
AO type 31A1 102 (32.8)
31A2 178 (57.2)
31A3 31 (10.0)
Subtrochanteric fractures 16 (2.8)
Time to surgery < 72 hrs (%) 324 (57.0)
Time to surgery ≥ 72 hrs (%) 244 (43.0)
Osteosynthesis 342 (60.2)
Cannulated hip screws 26 (7.6)
Trochanteric nail 316 (92.4)
Arthroplasty 226 (39.8)
Hemiarthroplasty 157 (69.5)
Total hip arthroplasty 69 (30.5)
Median length of hospital stay (days) (IQR) 9.0 (7.0 to 12.0)
Mean pre-operative Hb level (g/dl) (range) 11.5 (6.2 to 17.3)
Mean post-operative Hb level (g/dl) (range) 9.3 (5.4 to 15.6)
  1. Hb, haemoglobin; IQR, interquartile range

Table IV

Univariate age-adjusted Cox’s regression analysis of variables associated with mortality. Figures are hazard ratios (95% confidence intervals)

30-day mortality p-value 1-year mortality p-value
Male 2.55 (1.12 to 5.81) 0.026 1.83 (1.14 to 2.95) 0.012
ASA grade 5.83 (3.13 to 10.82) < 0.001 4.12 (2.91 to 5.84) < 0.001
Pre-fracture ADL Index 0.73 (0.60 to 0.89) 0.002 0.73 (0.66 to 0.82) < 0.001
4-month ADL index 0.57 (0.48 to 0.68) < 0.001
Pre-fracture mobility 0.58 (0.48 to 0.71) < 0.001
4-month mobility 0.42 (0.33 to 0.55) < 0.001
MMSE 0.92 (0.88 to 0.96) < 0.001 0.94 (0.92 to 0.97) < 0.001
CIRS score 1.32 (1.19 to 1.47) < 0.001 1.22 (1.15 to 1.29) < 0.001
Dementia 3.65 (1.55 to 8.58) 0.003 2.49 (1.55 to 3.99) < 0.001
AO pattern of fracture 1.13 (1.03 to 1.23) 0.008
In-hospital general complications 8.81 (3.83 to 20.25) < 0.001 2.84 (1.82 to 4.42) < 0.001
4-month general complications 9.19 (4.80 to 17.58) < 0.001
4-month hip-related complications 2.61 (1.10 to 6.18) 0.030
  1. BMI, Body mass index; ASA, American Society of Anesthesiologists; ADL, activities of daily living; MMSE, mini-mental state examination; CIRS, cumulative illness rating scale; Hb, haemoglobin

Table V

Determinants of mortality: multivariate Cox’s regression analysis

All patients n = 552 Patients aged < 80 years n = 264 Patients aged ≥ 80 years n = 288
HR (95% CI) Chi-squared difference p-value HR (95% CI) Chi-squared difference p-value HR (95% CI) Chi-squared difference p-value
30 days
IHGC 11.59 (3.40 to 39.51) 37.26 < 0.001 6.03 (1.16 to 31.30) 5.51 0.019 19.68 (2.56 to 151.48) 21.55 0.004
ASA grade 3.27 (1.72 to 6.25) 13.21 < 0.001 3.12 (1.37 to 7.08) 12.70 0.007 3.04 (1.22 to 7.56) 5.66 0.017
Dementia 4.81 (1.30 to 17.83) 11.47 0.001
1 year
4-month GC 3.27 (1.54 to 6.97) 48.26 0.002 4.33 (1.81 to 10.31) 34.31 0.001
4-month mobility 0.55 (0.40 to 0.75) 23.89 < 0.001 0.46 (0.28 to 0.77) 16.75 0.003
ASA grade 2.11 (1.23 to 3.60) 6.58 0.006
AO pattern of fracture 1.14 (1.00 to 1.29) 3.79 0.049 1.30 (1.01 to 1.68) 3.96 0.045
CIRS 1.28 (1.09 to 1.51) 8.83 0.003
4-month ADL Index 0.64 (0.49 to 0.84) 13.21 0.001
  1. IHGC, in-hospital general complications; GC, general complications HR, hazard ratio; CI, confidence interval; ASA, American Society of Anesthesiologists; CIRS, cumulative illness rating scale; ADL, activities of daily living

Table VI

Post-operative complications and medical conditions

Complication or medical condition n (%)
In-hospital patients, (568) Minor general Delirium 68 (12.0)
Pressure sores 44 (7.7)
Anaemia 22 (3.9)
Fluid and electrolyte imbalance 20 (3.5)
Urinary tract infection 4 (0.7)
Other 3 (0.5)
Overall minor general complications 161
Major general Deep vein thrombosis/pulmonary embolism 15 (2.6)
Acute renal failure 14 (2.5)
Severe arrhythmia 11 (1.9)
Pneumonia 6 (1.1)
Myocardial infarction 4 (0.7)
Intestinal obstruction 4 (0.7)
Stroke 3 (0.5)
Heart failure 2 (0.4)
Other 5 (0.9)
Overall major general complications 64
Hip related Superficial surgical site infection 11 (1.9)
Implant infection 7 (1.2)
Hip arthroplasty dislocation 5 (0.9)
Peri-implant fracture 2 (0.4)
Sciatic nerve palsy 2 (0.4)
Overall hip-related complications 27
Patients at four-months post-operatively (489) General Pressure sores 51 (10.4)
Urinary tract infection 13 (2.7)
Pneumonia 9 (1.8)
Deep vein thrombosis/pulmonary embolism 7 (1.4)
Stroke 5 (1.0)
Other 7 (1.4)
Overall general complications 92
Hip related Failure of osteosynthesis/prosthesis 12 (2.5)
Implant infection 4 (0.8)
Peri-implant fracture 2 (0.4)
Sciatic nerve palsy 2 (0.4)
Other 3 (0.6)
Overall hip-related complications 23
Patients at one-year post-operatively (448) General Pressure sores 13 (2.9)
Urinary tract infection 8 (1.8)
Cognitive impairment 4 (0.9)
Stroke 2 (0.4)
Other 3 (0.7)
Overall general complications 30
Hip related Failure of osteosynthesis/prosthesis 7 (1.6)
Fracture nonunion 3 (0.7)
Other 5 (1.1)
Overall hip-related complications 15

Table VII

Determinants of general complications: forward stepwise multiple logistic regression analysis

Explanatory variables OR 95% CI Chi-squared difference p-value
IHGC
CIRS score 1.22 1.14 to 1.31 63.93 < 0.001
Pre-operative Hb concentration (g/dl) 0.78 0.69 to 0.88 18.17 < 0.001
MMSE score 0.96 0.93 to 0.99 9.61 0.002
Osteoporosis treatment 0.51 0.31 to 0.85 7.40 0.007
Surgery within 72 h 0.59 0.38 to 0.91 5.67 0.017
4-month GC
MMSE score 0.92 0.89 to 0.95 47.32 < 0.001
ASA grade 1.98 1.28 to 3.06 10.39 0.001
Surgery within 72 hrs 0.51 0.31 to 0.85 6.97 0.008
1-year GC
Four-month GC 33.53 11.38 to 99.78 82.92 < 0.001
Four-month ADL Index 0.79 0.63 to 0.99 4.23 0.040
  1. IHGC, in-hospital general complications; GC, general complications OR, odds ratio; CI, confidence interval; CIRS, cumulative illness rating scale; Hb, haemoglobin; MMSE, mini-mental state examination; ASA, American Society of Anesthesiologists; ADL, activities of daily living

Discussion

The rate of mortality in our cohort at the various time intervals was similar to that which has been previously reported.4 It was also closely linked to post-operative complications as previously described.8,9,12,13,15As in the other studies,3,6,10 increasing ASA grade played an independent detrimental role. The effect of patients’ mobility and ADL on mortality appeared only one year after the fracture and was not significantly associated with in-hospital deaths. Limited function prior to fracture has been associated with complications26 and mortality.1,2,27 We found that the odds of being alive one year after a fracture of the hip were lower for patients aged > 80 years than for those aged < 80 years. We also found a direct association between male gender and mortality in univariate analysis, but this was not confirmed using multivariate analysis. Both advanced age and male gender have been recognised as strong predictors of mortality after a fracture of the hip.4 However, not all studies agree on the effect of age2,12,28 and male gender29,30 in independently predicting mortality using a multivariate analysis. For example, others have found that men are more likely to have more severe medical comorbidities than women at the time of surgery.15,31 Clearly, multivariate analysis investigating the predictors of mortality is dependent on the choice of risk factors that are included. Therefore, the selection of covariables not used in previous studies or the use of different cut-off values may help to explain the lack of an association between mortality and increasing age or male gender in the multivariate analysis. However, when we constructed separate models of Cox’s regression analysis to assess whether age influenced the effect estimates, the role of complications as predictors of mortality was enhanced in patients aged ≥ 80 years compared with the younger age group. Thus, even though increasing age was not directly related to increased mortality in our multivariate analysis, it may have set the stage for the direct effect of early or delayed complications on mortality in the first post-operative year following fracture, because of the alteration in the functional balance caused by the fracture in these patients.

Our cohort was comparable to others6,9,11-13 in their rate of post-operative complications. We detected a decrease in the frequency of life-threatening conditions related to the fracture at four months and one year post-operatively. This may reflect the previous higher mortality owing to severe complications in the early post-operative period. Our multivariate analysis identified comorbidity to be a determinant of the likelihood of complications while in hospital and at four months post-operatively. These elderly patients may not have the functional reserve to withstand multiple insults, and this may lead to more frequent delayed medical complications and increased mortality. In earlier studies, a higher grade of ASA or CIRS has also been associated with an increased risk of early6,12,15 and delayed32 complications. In our patients a lower MMSE score was positively associated with an increased risk of post-operative complications. Cognitive impairment has been associated with a poor functional outcome33 and mortality33,34 in patients after a fracture of the hip, perhaps because of interference with motivation and function.33 Poor cognitive status, longer time to surgery and a higher ASA grade were also independent determinants of pressure sores in our patients, confirming that complications often result from a combination of the these risk factors rather than from a single cause. Previous studies have found similar relationships.10,35-37

The cut-off of 72 hours for the delay to surgery was longer than in most other studies.3,10,36 In our study, the delay was mainly attributable to secondary evidence of fracture, delayed presentations, unavailability of operating rooms and/or surgical personnel, and the patient’s comorbidity at the time of admission. Although mortality was not influenced, we detected a reduction in the risk of complications among patients who underwent earlier surgery, which is consistent with the literature.10,36-38 These models using multivariate analysis were adjusted for the level of comorbidity. Therefore, independent of comorbidities leading to the surgical delay, the delay itself was a determinant of in-hospital and general complications four months post-operatively. Delayed surgery was also the most important independent factor prolonging the hospital stay. Earlier studies also indicated that the shorter the pre-operative waiting time, the shorter the post-operative stay.37,38

Surgical factors, such as the type of fracture or specific treatment, have been under-reported in observational studies of fractures of the hip.13 The mortality and morbidity of our patients were not influenced by type of fracture (femoral neck or trochanteric) or surgical implant, thereby confirming previous reports.2,5,6,13,27 Only the increasing AO grade of fracture represented a weak predictor of mortality one year post-operatively in our multivariate analysis.

This study has several limitations. First, the study population may not be typical of the elderly patients who sustain a fracture of the hip, as the hospitals were not selected for their case mix. Hence, conclusions based on these patients may not apply to all patients with a fracture of the hip in our geographical area. Nevertheless, the participating hospitals have large catchment areas that include urban and rural areas, with patients of diverse socioeconomic status. Second, the patients may have been unable to recall their pre-fracture status owing to diminished mental status. Third, no testing of reliability was performed on the accuracy of the replies from relatives and carers, which might alter the precision of assessments made during the interviews. In order to minimise this effect, validated instruments were administered during the interviews. Moreover, family physicians were contacted to collect data on any complications or re-operations that occurred during the study period.

The study has several strengths, however. We used a large cohort of consecutive patients with data collected prospectively. Patients lost to follow-up and those treated conservatively did not exceed 10% of the study population. Also, the use of validated tools permitted comparison with other studies. This makes ours one of the few prospective studies to report complications and medical conditions between admission and the situation one year post-operatively.


Correspondence should be sent to Prof Dr M. Mariconda; e-mail:

1 Elliott J , BeringerT, KeeF, et al.Predicting survival after treatment for fracture of the proximal femur and the effect of delays to surgery. J Clin Epidemiol2003;56:788795. Google Scholar

2 Alegre-López J , Cordero-GuevaraJ, Alonso-ValdivielsoJL, Fernández-MelónJ. Factors associated with mortality and functional disability after hip fracture: an inception cohort study. Osteoporos Int2005;16:729736. Google Scholar

3 Daugaard CL , JørgensenHL, RiisT, et al.Is mortality after hip fracture associated with surgical delay or admission during weekends and public holidays? a retrospective study of 38,020 patients. Acta Orthop2012;83:609613. Google Scholar

4 Hu F , JiangC, ShenJ, TangP, WangY. Preoperative predictors for mortality following hip fracture surgery: a systematic review and meta-analysis. Injury2012;43:676685. Google Scholar

5 Diamantopoulos AP , HoffM, HochbergM, HaugebergG. Predictors of short- and long-term mortality in males and females with hip fracture - a prospective observational cohort study. PLoS One2013;8:78169. Google Scholar

6 Pugely AJ , MartinCT, GaoY, et al.A risk calculator for short-term morbidity and mortality after hip fracture surgery. J Orthop Trauma2014;28:6369. Google Scholar

7 Thomas CJ , SmithRP, UzoigweCE, BraybrookeJR. The weekend effect: short-term mortality following admission with a hip fracture. Bone Joint J2014;96-B:373378. Google Scholar

8 Cameron ID , ChenJS, MarchLM, et al.Hip fracture causes excess mortality owing to cardiovascular and infectious disease in institutionalized older people: a prospective 5-year study. J Bone Miner Res2010;25:866872. Google Scholar

9 Roche JJ , WennRT, SahotaO, MoranCG. Effect of comorbidities and postoperative complications on mortality after hip fracture in elderly people: prospective observational cohort study. BMJ2005;331:1374. Google Scholar

10 Smektala R , EndresHG, DaschB, et al.The effect of time-to-surgery on outcome in elderly patients with proximal femoral fractures. BMC Musculoskelet Disord2008;9:171. Google Scholar

11 De Brauwer I , LepageS, YombiJC, CornetteP, BolandB. Prediction of risk of in-hospital geriatric complications in older patients with hip fracture. Aging Clin Exp Res2012;24:6267. Google Scholar

12 Buecking B , EschbachD, KoutrasC, et al.Re-admission to Level 2 unit after hip-fracture surgery - Risk factors, reasons and outcome. Injury2013;44:19191925. Google Scholar

13 Belmont PJ Jr , GarciaEJ, RomanoD, et al.Risk factors for complications and in-hospital mortality following hip fractures: a study using the National Trauma Data Bank. Arch Orthop Trauma Surg2014;134:597604. Google Scholar

14 Rosell PA , ParkerMJ. Functional outcome after hip fracture; a 1-year prospective outcome study of 275 patients. Injury2003;34:529532. Google Scholar

15 Endo Y , AharonoffGB, ZuckermanJD, EgolKA, KovalKJ. Gender differences in patients with hip fracture: a greater risk of morbidity and mortality in men. J Orthop Trauma2005;19:2935. Google Scholar

16 Beaupre LA , JonesCA, JohnstonDW, WilsonDM, MajumdarSR. Recovery of function following a hip fracture in geriatric ambulatory persons living in nursing homes: prospective cohort study. J Am Geriatr Soc2012;60:12681273. Google Scholar

17 Vochteloo AJ , MoermanS, TuinebreijerWE, et al.More than half of hip fracture patients do not regain mobility in the first postoperative year. Geriatr Gerontol Int2013;13:334341. Google Scholar

18 Tarrant SM , HardyBM, BythPL, et al.Preventable mortality in geriatric hip fracture inpatients. Bone Joint J2014;96-B:11781184. Google Scholar

19 Holt G , SmithR, DuncanK, HutchisonJD, GregoriA. Epidemiology and outcome after hip fracture in the under 65s-evidence from the Scottish Hip Fracture Audit. Injury2008;39:11751181. Google Scholar

20 Katz S , FordAB, MoskowitzRW, JacksonBA, JaffeMW. Studies of illness in the aged; the index of ADL: a standardized measure of biological and psychosocial function. :. JAMA1963;185:914919. Google Scholar

21 Folstein MF , FolsteinSE, McHughPR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res1975;12:189198. Google Scholar

22 Linn BS , LinnMW, GurelL. Cumulative illness rating scale. J Am Geriatr Soc1968;16:622626. Google Scholar

23 Müller M , NazarianS, KochP, SchatzkerJ The Comprehensive Classification of Fractures of Long Bones. Berlin: Springer-Verlag, 1990. Google Scholar

24 Garden RS . Low-angle fixation in fractures of the femoral neck. J Bone Joint Surg [Br]1961;43-B:647663. Google Scholar

25 Owens WD , FeltsJA, SpitznagelEL Jr. ASA physical status classifications: a study of consistency of ratings. Anesthesiology1978;49:239243. Google Scholar

26 Myers AH , PalmerMH, EngelBT, WarrenfeltzDJ, ParkerJA. Mobility in older patients with hip fractures: examining prefracture status, complications, and outcomes at discharge from the acute-care hospital. J Orthop Trauma1996;10:99107. Google Scholar

27 Pereira SR , PutsMT, PortelaMC, SayegMA. The impact of prefracture and hip fracture characteristics on mortality in older persons in Brazil. Clin Orthop Relat Res2010;468:18691883. Google Scholar

28 Mossey JM , MutranE, KnottK, CraikR. Determinants of recovery 12 months after hip fracture: the importance of psychosocial factors. Am J Public Health1989;79:279286. Google Scholar

29 Kenzora JE , McCarthyRE, LowellJD, SledgeCB. Hip fracture mortality. Relation to age, treatment, preoperative illness, time of surgery, and complications. Clin Orthop Relat Res1984;186:4556. Google Scholar

30 Valizadeh M , MazloomzadehS, GolmohammadiS, LarijaniB. Mortality after low trauma hip fracture: a prospective cohort study. BMC Musculoskelet Disord2012;13:143. Google Scholar

31 White BL , FisherWD, LaurinCA. Rate of mortality for elderly patients after fracture of the hip in the 1980's. J Bone Joint Surg [Am]1987;69-A:13351340. Google Scholar

32 Giusti A , BaroneA, RazzanoM, et al.Predictors of hospital readmission in a cohort of 236 elderly discharged after surgical repair of hip fracture: one-year follow-up. Aging Clin Exp Res2008;20:253259. Google Scholar

33 Givens JL , SanftTB, MarcantonioER. Functional recovery after hip fracture: the combined effects of depressive symptoms, cognitive impairment, and delirium. J Am Geriatr Soc2008;56:10751079. Google Scholar

34 Schaller F , SidelnikovE, TheilerR, et al.Mild to moderate cognitive impairment is a major risk factor for mortality and nursing home admission in the first year after hip fracture. Bone2012;51:347352. Google Scholar

35 Söderqvist A , PonzerS, TidermarkJ. Cognitive function and pressure ulcers in hip fracture patients. Scand J Caring Sci2007;21:7983. Google Scholar

36 Simunovic N , DevereauxPJ, SpragueS, et al.Effect of early surgery after hip fracture on mortality and complications: systematic review and meta-analysis. CMAJ2010;182:16091616. Google Scholar

37 Rodriguez-Fernandez P , Adarraga-CansinoD, CarpinteroP. Effects of delayed hip fracture surgery on mortality and morbidity in elderly patients. Clin Orthop Relat Res2011;469:32183221. Google Scholar

38 Lefaivre KA , MacadamSA, DavidsonDJ, et al.Length of stay, mortality, morbidity and delay to surgery in hip fractures. J Bone Joint Surg [Br]2009;91-B:922927. Google Scholar

Author contributions

M. Mariconda: Data Analysis, Writing the paper, Performed surgeries.

G.G. Costa: Data collection, Data analysis, Performed surgeries.

S. Cerbasi: Data collection, Data analysis, Performed surgeries.

P. Recano: Data collection, Performed surgeries.

E. Aitanti: Data collection, Performed surgeries.

M. Gambacorta: Data collection, Data analysis, Helped writing the paper.

M. Misasi: Data analysis, Critical revision of the paper, Performed surgeries.

No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article.

This article was primary edited by S. Hughes and first proof edited by J. Scott.

Supplementary material. Additional infomative text, explaining the confounding or explanatory variables tested as predictors of all outcomes, is available alongside the online version of this article at www.bjj.boneandjoint.org.uk