Prevention and management of perioperative complications is a consistent subject in practice and research in elderly hip fracture, especially for those prevalent and further catastrophic complications. In this study, we used the sample from a tertiary referral trauma center and found preoperative DVT had prevalence of 12.3% in elderly patients with a hip fracture, and identified 6 independent factors associated with DVT, including history of a VTE event, time from injury to DVT screening, BMI, peripheral vascular disease, lower albumin level and elevated D-Dimer. The combination risk prediction model, developed based on these findings, showed a favorable performance in distinguishing between DVTs and non-DVTs, with an AUC of 0.780.

We reported a relatively lower prevalence rate of preoperative DVT following elderly intertrochanteric fractures, compared to those in literature. Zuo et al. [18] reported a 20.1% rate of admission DVT diagnosed by DUS in their retrospective analysis of 578 intertrochanteric fractures in patients aged 60 years or older. Fei et al. [20], in their retrospective study of 218 patients aged 16 years or older with intertrochanteric fractures, found the preoperative DVT diagnosed by DUS was 37.6%, about 3 times as ours. Bengoa et al. [26] investigated the relationship between DVT prevalence and the delay to admission, and found 17.6% of prevalence in patients admitted ≥ 48 h after a hip fracture, which was consistent with ours (14.5%, 95/654). In the other studies with different settings related to patients or fracture types (including or limited to femoral neck fracture), investigators reported the variable prevalence rates, from 11.% to 35.0% [1,2,3]. The great variation in DVT prevalence reflected the differences in race, patient characteristics, study design, DVT screening methods and the policies on DVT prophylaxis and hip fracture care, although it was almost impossible in a perfectly homogeneous population. In our study we used the more stringent criteria that only patients without DVT chemoprophylaxis before DVT examination could be included. In addition, for purpose of continuous exploration of potentially new factors, we excluded those with a well-established factor, e.g. recent incident thrombotic events (i.e., within 1 month before index fracture) or pre-fracture mobility dependence, because as per institutional policy, patients with these conditions would be classified as high-risk group and be given targeted therapeutic intervention (double-dose LMWH, compared to single-dose for prophylactic intervention) as a matter of priority. These are likely contributing to our examined low prevalence rate of DVT.

Among the 6 independent factors identified, most were repeatedly investigated in literature, such as delay to admission or DVT screening [10, 17,18,19], higher BMI or obesity [18, 19], peripheral vascular disease [19], reduced albumin [18] and elevated D-Dimer level [1, 10, 17,18,19]. The relatively prolonged time from injury to DVT examination (mean, 4.1 days) must be explain. In fact, in most tertiary referral hospitals in China, including ours, it is not easy to follow the early-surgery-within-48-h recommendation, and the prolonged “wait” is primarily involves the time from injury to admission. This institution is an 800-beds-setting orthopaedics-specialized hospital, covering over 10 million inhabitants in Shijiazhuang City. Despite that, a substantial proportion of patients will wait for some days before admitting, due to the relatively inadequate beds; and during COVID-19, this situation is even more deteriorating due to the strict hospitalization policy regarding compulsory and within-48 h nucleic acid testing negative result. In almost all previous studies, history of a VTE was excluded due to its potential strong effect on the secondary VTE, which subjected to be provoked by an acute trauma (e.g. fracture or bleeding event) or a medically unstable status (e.g. cerebral or cardiac ischemia). In our study, we found the strongest magnitude of association of history of VTE (OR, 4.43) with the DVT, underscoring the importance of classifying patients with a history of VTE as high-risk population in elderly intertrochanteric fracture practice, regardless of presence of other risk factors.

Plasma D-dimer level is a typical laboratory biomarker for diagnosis of DVT or PE, but its diagnostic value in some specific groups of patients remains in controversy. Substantial evidences have demonstrated the age-dependence of D-dimer concentration, and the conventional cut-off value (0.5 mg/L) is scarcely able to provide a discrimination between VTEs and non-VTEs in the elderly patients. According to a systematic review, the specificity of D-dimer test with a traditional cut-off value was 49% to 67% in patients aged < 50 years, but between 0 and 18% in those ≥ 80 years [27]. Given that most intertrochanteric fracture occurred at an advanced age, mean of 77 years in this study, we re-defined cut-off value of D-dimer as 1.0 mg/L and demonstrated its acceptable power (sensitivity, 0.781; specificity, 0.380). Future studies on investigation of age-adjusted D-dimer value on DVT at a specific group, e.g. hip fracture patients, are warranted to refine its value.

Improvement of the specificity in diagnosis of VTE have been an increasingly important subject via various methods, such as adjusting the age-related D-dimer coefficient, combination diagnostic test, or development of risk models based on the identified factors, to reduce the unnecessary diagnostic imaging investigation [27,28,29]. However, specific at hip fractures generally requiring emergent surgeries, there were few effective and practical methods and related studies were inadequate. In this study, we developed this risk prediction model based on the 6 risk factors identified, which exhibited a moderate sensitivity of 0.667, but importantly the relatively high specificity of 0.777. This may compensate for the low specificity of D-dimer in traditional (0.5 mg/L, about 10%-30%) [30, 31] or current cut-off (1.0 mg/L, 38%) in the elderly patients, contributing to safely ruling out DVT in a substantial proportion of hip fracture patients. Despite this, given the potential serious consequence of the DVT and that surgeons do not always get the chance to reconsider a missed diagnosis in such major trauma requiring emergence surgeries, the subsequent prospective studies with large sample are needed to verify the effectiveness and safety of this risk prediction model.

The strengths of this study were the strict and exclusion criteria, the large sample of participants, redefining the optimal cut-offs for some DVT-closely-related biomarkers and development of a risk prediction model with high specificity for a specific population of elderly intertrochanteric fracture patients. However, the limitations should be noted. First, the retrospective design introduced the bias in accuracy in data collection, especially on comorbidities that were self-reported by patients or relatives. It is possible that some already existing comorbidities are not identified or diagnosed, and therefore underreported. Second, this was a single-center study in a tertiary referral trauma center, which biased the patient selection because patients admitted had a severer fracture or more complex medical conditions. The generalizability of the findings is limited; especially, the results including the presented DVT rate are more applicable to Chinese healthcare system. Third, for outpatients or inpatients, Wells or Caprini score are most important tool for risk-classifying patients for the risk of DVT. However, due to absence of many variables, such as inflammatory bowel disease, positive for lupus anticoagulant Heparin-induced thrombocytopenia, central venous access or serum homocysteine et al., and exclusion of some well-known factors like pre-fracture not independent mobility, VTE history, and recent use of corticosteroids or anticoagulants, we could not obtain the corresponding score, which might have lowered its practicability. Fourth, we collected laboratory data at admission for analysis, most of which, however, were variable in time. In our study, the wide span of admission would have affected the results, despite we have adjusted for this variable. Fitth, as every multivariate analysis, there remains residual confounding effects from unknown or unmeasured factors. Fifth, this is first attempt to develop a DVT risk prediction model in such a population, and so its validity necessitates further well-designed studies to verify.

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