Abstract
Background
Hip fractures are considered as a major cause of mortality worldwide. Even after being the second most populous country in world and facing huge burden of hip fractures, there is scarcity of data from India. For the first time in Indian context, we analysed the predictors of mortality after hip fracture surgery in patients with age 50 years and above.
Materials and Methods
In this prospective cohort study, patients with age ≥ 50 years and having hip fractures presented to our institute from January 2018 through October 2018 were enrolled after meeting including and excluding criteria. Patients were followed-up for minimum 1 year after surgery. Association between 1-year mortality and different affecting variables were analysed. Significant variables were further analysed using logistic regression to find independent predictors.
Results
Out of 87 patients followed-up for 1 year, 25 patients died within 1 year of surgery. Age > 75 years, road traffic accident as mode of injury, delay in surgery > 48 h, > 2 co-morbidities, haemoglobin level ≤ 10 at the time of admission and osteoporosis are significantly associated with high mortality. When these significant variables were further analysed using logistic regression, age > 75 years and > 2 co-morbidities were only factors associated independently with high mortality.
Conclusion
In patients with age 50 years and above, following hip fracture surgery, age > 75 years and > 2 co-morbidities are the predictors of 1-year mortality when adjusted for other variable. A better designed multi-centric study can be more helpful in understanding the things in Indian context.
Keywords: Hip, Fracture, Elderly, Mortality
Introduction
Elderly patients undergoing hip fracture surgery have high mortality rates when compared with age and sex matched younger population. This higher mortality ranges from 14 to 36% in different studies [1–3]. International guidelines for hip fracture care suggest that delay in surgery leads to significantly higher mortality and other complication rates and a patient with hip fracture should undergo surgery within 24–48 h of hospital admission [4, 5]. In contrast, many studies have found that timing of surgery has no effect on mortality when adjusted for other variables [6–9]. Other studies have shown that higher mortality rate was associated with age, male sex and co-morbidities [10]. Low vitamin D levels and poor bone quality, though associated with higher risk of hip fractures, have not been studied for risk of morbidity or mortality in these patients.
It is estimated that by year 2025, in India, the incidence of hip fracture in elderly adults will be more than 400,000 annually [11]. Despite of this huge disease burden, there is scarcity of data from India regarding hip fractures. Unlike in developed countries where a multidisciplinary protocol-based approach is there for management of these fractures, in India, such guidelines and protocols are missing [12]. Lack of osteoporotic management, delayed presentation and unmanaged co-morbidities are common and further complicate the situation [12].
The purpose of our study was to analyse prospectively, the predictors of 1-year mortality after hip fracture surgery in patients with age 50 years or above presented to our institute from January 2018 through October 2018. To the best of our knowledge, our study is the first from India analysing these predictors. Our study will be helpful in better understanding the problem and improving the management in Indian context.
Materials and Methods
Our study was a prospective cohort study. After getting ethical clearance from institutional ethical board, the patients were enrolled over the period January 2018 through October 2018. Our inclusion criteria were—all the patients admitted to our institute with hip fractures having age 50 years or above. Exclusion criteria were—other associated traumatic injury, open fractures, fracture due to malignancy and patient not willing to participate in study.
In all the patients, after getting X-rays done and diagnosis was made, surgery was planned accordingly. For patients having intra-capsular hip fracture and age 60 years or above, modular cemented hemiarthroplasty was planned. For patients with age less than 60 years having intra-capsular hip fracture, screw fixation was planned. For all the patients having extra-capsular fracture, proximal femur nailing (two proximal screws) was planned. In all the patients with age less than 60 years, fixation of fracture was planned to preserve the joint. All the relevant investigations were done and consultations were taken from different specialities as per the co-morbid conditions. Surgery was planned as early as possible on routine list. After surgery patients were encouraged to mobilise as early as possible. Patients who underwent replacement surgery were mobilised full weight bearing from second day of surgery. Patients who underwent fracture fixation were allowed partial weight bearing (40% body weight) till 3 weeks followed by full weight bearing. On bed, physiotherapy was encouraged all the time after surgery. After discharge from hospital, patients were followed-up in out-patient department at 3, 6 and 12 months. All the patients were followed-up for minimum of 1 year.
We defined hip fracture as femur trochanteric region fracture (31A) or femur neck fracture (31B) according to AO/OTA classification. Continuous variables were defined as mean ± S.D. (Table 1). Diabetes, hypertension, cardiovascular disease, cerebrovascular disease and chronic respiratory disease were evaluated as co-morbidities during our study. Discrete variables were defined as frequency and percentage (Table 2). Our outcome variable was mortality within 1 year. Statistical analysis was done to determine the association between 1-year mortality and independent variables. All independent variables were first analysed for their association with mortality using odd ratio. Chi-square or Fisher’s exact test was done to calculate p value. Variables found to be significant were further analysed using logistic regression analysis. Analysis was done using enter method whereby all independent variables were inserted into the model simultaneously. For all the calculations, significant difference was defined at p < 0.05. Written consent was taken from all the patients before enrolling them for study.
Table 1.
Descriptive data (Continuous variables)
| Mean ± S.D | Range | |
|---|---|---|
| Age (years) | ||
| Total (n = 87) | 71.86 ± 10.65 | 50–92 |
| Lived > 1 year (n = 62) | 68.77 ± 9.73 | 50–89 |
| Died within 1 year (n = 25) | 79.52 ± 8.94 | 55–92 |
| Delay in surgery (days) | ||
| Total (n = 87) | 8.56 ± 7.00 | 1–36 |
| Lived > 1 year (n = 62) | 7.43 ± 5.80 | 1–36 |
| Died within 1 year (n = 25) | 11.36 ± 8.87 | 2–32 |
| Pre-operative haemoglobin (grams per decilitre) | ||
| Total (n = 87) | 11.48 ± 1.60 | 7.20–16.70 |
| Lived > 1 year (n = 62) | 11.71 ± 1.43 | 8.90–15.10 |
| Died within 1 year (n = 25) | 10.90 ± 1.87 | 7.20–16.70 |
| Body mass index | ||
| Total (n = 87) | 24.24 ± 3.35 | 18.00–33.70 |
| Lived > 1 year (n = 62) | 24.17 ± 3.22 | 18.60–33.70 |
| Died within 1 year (n = 25) | 24.43 ± 3.71 | 18.00–32.00 |
Table 2.
Descriptive data (Discrete variables)
| N (%) | |
|---|---|
| Sex | |
| Male | 44 (51%) |
| Female | 43 (49%) |
| Fixation method | |
| Proximal femur nail | 68 (78%) |
| Hemiarthroplasty | 15 (17%) |
| Screw fixation | 04 (05%) |
| T-score | |
| ≤ (− 2.5) (osteoporosis) | 32 (37%) |
| (− 2.4) to (− 1.5) (osteopenia) | 32 (37%) |
| > 1.5 (normal) | 23 (26%) |
| Co-morbidities | |
| Hypertension | 29 |
| Diabetes mellitus | 17 |
| Cerebrovascular disease | 03 |
| Cardiovascular disease | 06 |
| Chronic respiratory disease | 07 |
Results
Total 90 patients were enrolled in our study meeting our inclusion and exclusion criteria. 3 patients were lost to follow-up before completing 1 year so excluded from analysis. Of 87 patients, 44 were male and 43 were female with mean age 71.85 ± 10.48 years. Descriptive data for 87 patients are shown in Tables 1 and 2. Of 87 patients, 25 patients died within 1 year of surgery. When analysed for association with mortality, age > 75 years, mode of injury as RTA (road traffic accident), delay in surgery for > 48 h, more than 2 co-morbidities, Hb (haemoglobin) level ≤ 10 g per decilitre (at the time of admission) and T-score < (-2.5) were found to be significantly associated (Table 3). When these significantly associated variables were further analysed using logistic regression, age > 75 years and > 2 co-morbidities were found to be independent predictors of mortality within 1 year (Table 4).
Table 3.
Predictors of mortality
| Mortality | Lived | Odd ratio (C.I.) | p-value | |
|---|---|---|---|---|
| Age (years) | ||||
| > 75 | 17 | 16 | 6.10 (2.21–16.85) | 0.00 |
| ≤ 75 | 08 | 46 | ||
| Sex | ||||
| Male | 12 | 32 | 0.86 0.34–2.19 | 0.76 |
| Female | 13 | 30 | ||
| Mode of injury | ||||
| Road traffic accident | 23 | 41 | 5.89 1.26–27.41 | 0.01 |
| Low energy fall | 02 | 21 | ||
| Fracture type | ||||
| Extra-capsular | 20 | 49 | 1.061 (0.33–3.36) | 0.92 |
| Intra-capsular | 05 | 13 | ||
| Surgery done | ||||
| Fixation | 20 | 51 | 0.86 (0.26–2.79) | 0.80 |
| Hemiarthroplasty | 05 | 11 | ||
| Delay in surgery | ||||
| ≤ 48 h | 01 | 17 | 0.11 (0.01–0.88) | 0.01 |
| > 48 h | 24 | 45 | ||
| Delay in surgery | ||||
| ≤ 5 days | 08 | 30 | 0.50 (0.18–1.33) | 0.16 |
| > 5 days | 17 | 32 | ||
| Delay in surgery | ||||
| ≤ 7 days | 13 | 38 | 0.68 (0.26–1.74) | 0.42 |
| > 7 days | 12 | 24 | ||
| Co-morbidity | ||||
| ≤ 2 | 08 | 49 | 0.12 (0.04–0.35) | 0.00 |
| > 2 | 17 | 13 | ||
| Pre-operative haemoglobin (grams per decilitre) | ||||
| ≤ 10 | 12 | 09 | 5.43 (1.89–15.62) | 0.00 |
| > 10 | 13 | 53 | ||
| T-score | ||||
| ≤ (− 2.5) (osteoporosis) | 15 | 17 | 3.97 (1.49–10.53) | 0.04 |
| > (− 2.5) (osteopenia/normal) | 10 | 45 | ||
| Body mass index | ||||
| ≥ 25 (overweight/obese) | 11 | 23 | 1.33 (0.51–3.42) | 0.55 |
| < 25 (normal) | 14 | 39 | ||
Table 4.
Logistic regression analysis of significant predictors
| B | S.E | p value | Odd ratio (C.I.) | |
|---|---|---|---|---|
| Age | 1.625 | 0.684 | 0.017 | 5.077 (1.329–19.389) |
| Mode of injury | − 1.959 | 1.039 | 0.059 | 0.141 (0.018–1.081) |
| Delay in surgery (≤ 48 h or > 48 h) | − 2.065 | 1.415 | 0.144 | 0.127 (0.008–2.030) |
| Co-morbidities | − 1.899 | 0.671 | 0.005 | 0.150 (0.040–0.558) |
| Pre-operative haemoglobin | 1.256 | 0.734 | 0.087 | 3.511 (0.833–14.809) |
| T-score | 0.637 | 0.699 | 0.362 | 1.890 (0.481–7.433) |
Discussion
Hip fracture in elderly is a major public health problem in terms of morbidity and mortality and costs a huge financial burden [13]. After hip fracture surgery in elderly patients 1-year mortality rate of up to 36% has been reported [2]. Various factors have been reported to be associated with this high mortality rate. Timing of surgery is widely accepted to be the most important and current guidelines from developed world suggest surgery within 48 h of injury [4, 5].
However, in India, it is not mostly possible to operate these patients within 48 h mainly due to lack of protocol based multidisciplinary approach and deficiency of resources [12]. Protocol-based approach if present anywhere is only on experimental basis [12, 14–16]. In our study, only 18 of 87 patients were operated within 48 h. 6 patients had delay more than 21 days. All these six patients were managed with massages by local quacks before presenting to us. This faith in alternate medicine is another major reason for late presentation and delayed surgery in India. Late presentation to hospital is described by other Indian authors also [12, 15].
Though it is believed widely that timing of surgery effects mortality, many studies concluded that early surgery is not associated with lesser mortality [17–20]. Smektala et al. analysed patients with age more than 65 years with isolated femoral neck or pertrochnteric femoral fractures [17]. According to time period from fracture to surgery, authors divided the patients in three groups—short (≤ 12 h), medium (12 to ≤ 36 h) and long (> 36 h). The authors concluded that there was no association between 1-year mortality and time to surgery. Moran et al. in their prospective study of elderly patients who underwent surgical treatment of hip fractures concluded that surgical delay up to 4 days was not associated with increased 30 days mortality when patients did not have associated co-morbidities [18]. When surgery was delayed, patients having co-morbidites had mortality rate 2.5 times as compared to patients without co-morbidities. Orosz et al. also in a prospective cohort study of 1206 hip fracture patients having age > 50 years compared the mortality rates when surgery was done within or after 24 h. The authors concluded that early surgery was not associated with improved mortality [19]. Similarly, Al-ani et al. in their prospective study of 850 consecutive patients concluded that mortality rate was not affected by timing of surgery when patients were divided according to surgery done with 24 h, 36 h and 48 h of admission [20].
Moreover, other authors concluded that factors other than timing of surgery were associated with mortality. Siegmeth et al. in their prospective review found that mortality rate was not affected by timing of surgery when adjusted for ASA (American Society of Anaesthesiologist) score, mental score and pre-fracture mobility score [9]. Khan et al. in their systematic review of 52 studies found that mortality was more associated with surgery delay in studies where confounding variables were not adjusted [7]. The authors concluded that studies with more careful methodology were less likely to have a beneficial effect of early surgery on mortality. Vidan et al. concluded in a prospective cohort study of elderly hip fracture patients that high mortality due to delay in surgery was explained by the medical reasons of delay rather than by delay itself [8]. The authors argued that young and fit patients undergo early surgery and so the effect of time on mortality, as described by other authors, was actually a selection bias. Similarly, Franzo et al. in their study found that co-morbidity, male sex, advancing age and multiple surgeries were predictors of mortality. Furthermore, the authors concluded that mortality in elderly patients who underwent hip fracture surgery was not associated with delay in surgery after adjusting for patient risk factors and volume of hospital surgical activity [6]. The authors defined surgical delay as '2 or more days' after hospital admission.
In our study, we divided patients in three groups according to delay in surgery— ≤ 48 h vs > 48 h, ≤ 5 days vs > 5 days and ≤ 7 days vs > 7 days. We in our study found that age > 75 years, RTA as mode of injury, delay in surgery > 48 h, > 2 co-morbidities, ≤ 10 Hb and osteoporosis are significantly associated with high mortality rate. However, when these significant variables were analysed using logistic regression we found that age > 75 years and > 2 co-morbidities were only factors associated independently with high mortality.
Our finding regarding co-morbidity as predictor of mortality was in consistence with previous studies [21–23]. Roche et al. concluded that 3 or more co-morbidities increased mortality in elderly patients with hip fractures [21]. Cher et al. compared Charlson Comorbiditi Index (CCI) and delay in surgery as a predictor of mortality at 30 days, 90 days and 2 years after hip fracture [22]. The authors found CCI as a dominant predictor of both short- and long-term mortality as compared to delay in surgery. Similarly, Kenzora et al. found pre-operative medical conditions highly significant factor effecting mortality after hip fracture surgery [23]. Systematic reviews and meta-analysis also by different authors concluded co-morbidities as predictors of mortality. [24–26]. Xu et al. in their systematic review found that multiple co-morbidities were predictor of mortality after hip fractures in 14 of 15 studies [26]. Chand et al. also in their meta-analysis found that co-morbidities were associated with mortality after hip fracture surgery [25]. Similarly, Hu et al. in their meta-analysis found that multiple co-morbidities were predictor of mortality after hip fracture surgery in elderly patients.
As in our study, age was found by other authors also in their systematic reviews to be significantly associated with mortality after hip fracture surgery in elderly patients. [24, 26, 27]. While Smith et al. described age > 85 year, Xu et al. and Hu et al. simply described advanced age being associated with high mortality. We found age > 75 years to be associated with high mortality in our study. Xu et al. in their systematic review reported that males had high mortality as compared to females [24]. Similarly, Hu et al. and Smith et al. in their meta-analysis found male gender as a mortality predictor [26, 27]. In our study, we did not find any significant association between mortality and gender.
Regarding type of fracture there are conflicting results. Xu et al. in their systematic review found that extra-capsular fractures were associated with high mortality rate, while Smith et al. found that intra-capsular fractures had 77% higher mortality rate compared with extra-capsular fractures [24, 27]. Hu et al. in their meta-analysis found moderate evidence that intertrochanteric femur fractures had high mortality rates than neck femur fractures in elderly patients [26]. Our study did not find any significant association between mortality and type of fracture.
Hb level is considered to be a potentially modifiable predictor and its measurement is easy to do with relatively little expenses. In recent studies, low level of Hb at the time of admission was found to be significantly associated with high mortality rates in elderly patients with hip fracture [28, 29]. Similarly, Hu et al. in their meta-analysis found moderate evidence in favour of association between low Hb and excess mortality in elderly hip fracture patients [26]. In our study, though Hb level ≤ 10 was found to be associated with high mortality on univariate analysis, after adjusting for other factors on multivariate analysis, there was no significant association between Hb level and mortality.
Vitamin D level and bone quality, though, have been extensively studied as factors for hip fracture occurrence, we are not aware of any study evaluating Vitamin D level and bone quality as a predictor of mortality in elderly patients after having hip fracture surgery. In our study, though we did not find any significant association between vitamin D level and mortality, osteoporosis was found to be associated with high mortality rates. However, after multivariate analysis, osteoporosis also was found not to be associated significantly with high mortality rates. Similarly, RTA as mode on injury was found to be a predictor of mortality as compared to low-energy fall but when analysed on multivariate analysis model, there was no association between mortality and mode of injury.
Even though we have a lot of literature available, it is difficult to make any consensus on predictors of mortality after hip fracture surgery as previous studies found variable results. Moreover most of the available literature is from developed countries. Lack of protocol-based multidisciplinary approach, limited resources, delayed presentation and unmanaged co-morbidities make our Indian patients different than those analysed in studies from developed world. Our study is the first study from India analysing the predictors of mortality after hip fracture surgery, though we acknowledge the limitations of our study. First, our study had a small sample size. Too many variables analysed from a relatively small sample may cause overfitting of regression model. Second, there may be other variables affecting mortality which were not analysed in current study like intra-operative hypotension/hypoxia due to cementation [30], electrolyte imbalance, blood transfusion requirement, post-operative activity level, fracture stability and others [26].
In conclusion, our study shows that in patients with age 50 years and above, following hip fracture surgery, age > 75 years and > 2 co-morbidities are the predictors of 1-year mortality when adjusted for other variable. A better designed multi-centric study can be more helpful in understanding the things in Indian context.
Funding
None.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical standard
This article does not contain any studies with human or animal subjects performed by the any of the authors.
Informed consent
For this type of study informed consent is not required.
Footnotes
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Contributor Information
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