Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Loss of walking independence one year after primary total hip arthroplasty for osteonecrosis of the femoral head: incidence and risk prediction model

Journal of Orthopaedic Surgery and Research volume 19, Article number: 580 (2024) Cite this article

Abstract

Background

Assessment of postoperative ambulation in osteonecrosis of the femoral head (ONFH) patients treated with total hip arthroplasty (THA) is limited. This study aimed to define the incidence and risk factors for losing walking independence (LWI) at one-year postoperatively in patients with ONFH undergoing primary THA, and to establish and validate a predictive nomogram.

Methods

This was a retrospective analysis of prospective collected data from patients admitted to a tertiary referral hospital with ONFH who underwent primary unilateral THA from October 2014 to March 2018. The Functional Independence Measure-Locomotion scale was used to quantify walking independence and was documented at a one-year continuous postoperative follow-up, which classified patients with a final score below 6 as LWI. Multivariate logistic regression identified independent risk factors for LWI, and a predictive nomogram was constructed based on the analysis results. The stability of the model was assessed using patients from April 2018 to April 2019 as an external validation set.

Results

1152 patients were enrolled in the study, of which 810 were used in the training cohort and the other 342 for the validation cohort. The incidence of LWI was 5.93%. Multivariate analysis revealed that age 62 years or older (odd ratio (OR) = 2.37, 95% confidence interval (CI) 1.07–5.24), Charlson’s comorbidity index 3 or higher (OR = 3.64, 95% CI 1.09–12.14), Association Research Circulation Osseous stage IV (OR = 2.16, 95% CI 1.03–4.54), reduced femoral offset (OR = 2.41, 95% CI 1.16–5.03), and a higher controlling nutritional status score (OR = 1.14, 95% CI 1.01–1.30) were independent risk factors of LWI. The nomogram had a concordance index of 0.773 and a Brier score of 0.049 in the training set, with corrected values of 0.747 and 0.051 after internal validation. The receiver-operating characteristic curve, calibration curve, Hosmer-Lemeshow test, and decision curve analysis all performed well in both the training and validation cohorts.

Conclusions

This study reported a 5.93% incidence of LWI and established a risk prediction model in patients undergoing THA for ONFH, supporting targeted screening and intervention to assist surgeons in assessing ambulation capacity and managing rehabilitation.

Introduction

Osteonecrosis of the femoral head (ONFH) affects over 20 million people worldwide and often necessitates surgery due to an 85% femoral head collapse rate [1,2,3,4,5]. Total hip arthroplasty (THA) remains the most effective and widely performed surgery for advanced ONFH [6,7,8]; yet, 7.2% of patients fail to regain independent ambulation postoperatively [9]. Patients losing walking independence (LWI) face up to a 13% revision risk and a 77% increased disability risk, significantly burdening the medical care system [10, 11]. Therefore, improving walking outcomes for ONFH patients undergoing THA is imperative.

Several studies have reported walking outcomes after THA. Singh et al. evaluated 5,707 patients via questionnaire and found that 5.7% had severe walking limitation 2 years postoperatively [12]. Another study of 753 elderly hip fracture patients reported that 36.3% had LWI at 180 days postoperatively [13]. However, existing walking assessments have focused on hip fracture or osteoarthritis patients, with few reports on the ONFH population. Sporadically published ones have identified factors such as Association Research Circulation Osseous (ARCO) stage and leg length discrepancy (LLD) affecting postoperative function, but did not prioritize independent walking as an outcome [1, 14]. With guidelines emphasizing the importance of walking assessment [15, 16], high-quality evidence is needed to inform the restoration of ambulation in patients undergoing THA for ONFH.

Given the above, this study defined the incidence and clinical risk factors for LWI at one-year postoperatively in patients undergoing primary THA for ONFH using an expanded sample, while establishing and validating a predictive nomogram.

Method

This retrospective cohort study was approved by the Institution’s Clinical Research Ethics Board. The study followed the Strengthening the Reporting of Cohort Studies in Surgery (STROCSS) and complied with the principles of the Helsinki Declaration. All participants or their immediate family members had signed a written informed consent form during hospitalization.

Data source

All of our data were obtained through the secondary analysis of the Surgical Site Infection in Orthopedic Surgery database. This database is maintained prospectively and manually, encompassing all data from orthopedic inpatients in the institution. Data are collected manually by 230 trained medical students and residents led by experienced professionals (including orthopaedic surgeons, radiologists, laboratory, infection control specialists, and senior nurses) and updated annually. Data include 310 items related to demographics, comorbidities, lifestyle, medication use, perioperative characteristics and serum perioperative biomarkers, and follow-up data (functional recovery, survival, complications, et al.). Follow-up visits were routinely performed at 2 weeks, 1 month, 3 months, 6 months, 12 months, and every 6 months thereafter postoperatively, using a combination of telephone and outpatient follow-up. We described this in detail elsewhere [13, 17,18,19,20,21].

Study design and populations

This retrospective analysis of prospective collected data included patients 18 years or older who underwent primary unilateral THA for ONFH in a tertiary referral orthopedic center from October 2014 to April 2019. THA and ONFH were defined by International Classification of Diseases, Clinical Modification codes (ICD-9-CM and ICD-10-CM), respectively. Exclusion criteria included bilateral hip arthroplasty, revision hip arthroplasty, inflammatory arthritis (including suppurative arthritis and gouty arthritis), symptoms of other large joint lesions, serious systemic illness, reported other lower extremity surgery or any major lower extremity injury within one year after primary THA, missing relevant blood parameters, and loss of follow-up.

General information

All data for this study were obtained from medical records and follow-up visits. Preoperative baseline characteristics comprised demographic characteristics, physiological status and disease severity, including age, gender, body mass index (BMI), aetiology, current smoking, living place, labor intensity, Charlson’s comorbidity index (CCI), surgical history, side of arthroplasty, ARCO stage, contralateral ARCO stage, American Society of Anesthesiologists (ASA) class, preoperative Visual Analogue Scale (VAS) score and preoperative comorbidities, including hypertension, diabetes, cerebrovascular disease, heart disease, chronic obstructive pulmonary disease (COPD), pneumonia, tumor, liver disease, kidney disease, peripheral vascular disease, and rheumatoid disease. The BMI was calculated based on the self-reported height and weight of the patient or his family. The labor intensity was divided into four grades according to the National Labor Standards of the People’s Republic of China: civilians, retirees, and civil servants were classified as grade I; doctors, teachers, drivers, and engineers were included in grade II; electricians and cleaners were grade III; and peasants and workers were grade IV. Freelancers and the unemployed, etc., are classified into other categories [22]. The controlling nutritional status (COUNT); prognostic nutritional index (PNI), and Glasgow prognostic score (GPS) are well-established nutritional screening tools and were used to assess the patients’ admission nutritional status [13, 23, 24]. Relevant parameters (peripheral blood lymphocyte count, serum albumin concentration, total cholesterol concentration, and C-reactive protein concentration) were extracted from routine blood tests and biochemical tests performed on admission.

Perioperative data included total hospital stay, year of surgery, surgeon experience, the presence of simultaneous contralateral hip-preserving surgery, anesthesia type, surgical approach, and surgical time. Four different surgical approaches were used: posterolateral approach, direct anterior approach, posterior approach, and direct lateral approach. Seventy-six patients were evaluated and underwent simultaneous contralateral hip-preserving surgery. Postoperatively, these patients were instructed to perform functional nonweight-bearing exercises on the hip-preserving limb for at least 6 months. The limb undergoing THA was required to bear partial weight for 1 week and full weight after 2 weeks.

Follow-up information included femoral offset (FO), LLD, and postoperative VAS score. A standard anteroposterior radiograph of the pelvis was taken at the one-month postoperative outpatient visit to measure global FO and LLD. The FO and limb length were measured on the arthroplasty side as previously described and compared with the contralateral side [25]. The patients were divided into three groups according to the radiographic measurements of FO: Reduced FO group (reduced by more than 5 mm on the operated side compared to the contralateral side); restored FO group (within 5 mm of the contralateral side); increased FO group (increased by more than 5 mm on the operated side compared to the contralateral side) [26]. Similarly, patients were divided into three groups based on the LLD between the healthy and operated sides: Undercorrected LL group (reduced by more than 10 mm); restored LL group (within 10 mm); and overcorrected LL group (increased by more than 10 mm) [27]. Postoperative VAS scores were measured at one-year postoperative follow-up.

Ambulatory capacity

A one-year time window was selected to assess walking independence in this study, as it allows sufficient time for recovery of walking ability after hip arthroplasty. This includes adaptation to functional lower limb length discrepancy, recovery of intraoperatively injured muscles, and pain relief [28]. The Functional Independence Measure-Locomotion (FIM-L) scale was used to quantify walking independence at intervals of 2 weeks, 1 month, 3 months, 6 months, and 1 year after surgery. According to FIM-L standards, a 50-foot walk was used for scores 2–5 and a 150-foot walk for scores 6–7. The FIM-L scale is defined as follows: 1 = total physical assistance; 2 = maximum physical assistance (> 50%); 3 = moderate physical assistance (25-50%); 4 = minimum physical assistance (< 25%); 5 = supervision without physical assistance; 6 = walking independently with equipment; 7 = walking independently without equipment [13]. All participants received a paper-based FIM-L scale along with a corresponding QR code during hospitalization, allowing follow-up on the Web, telephone, or mail. FIM-L scores were also measured and recorded during outpatient visits. The score at 1 year postoperatively was considered the final result. For patients who died within the follow-up window, their last recorded score was used. Patients with a final score of 6 or higher were classified into the ‘Recovering Walking Independence’ (RWI) group, while others were placed in the ‘Lossing Walking Independence’ (LWI) group.

Statistical analysis

The normality of continuous variables was assessed following the results of the Kolmogorov–Smirnov test, and normally distributed data were expressed as mean ± standard deviation (SD) using the Student’s t-test. Otherwise, the Mann–Whitney test was used and expressed as the median and interquartile range (IQR). Categorical variables were assessed using the chi-square test or Fisher’s exact test. We used the Youden index to determine the optimal cut-off point for age. Missing values of continuous BMI (4.3%) were imputed using multiple imputations.

Multivariate logistic regression analysis was performed for variables with P < 0.05 in univariate analysis, and independent risk factors for LWI were determined using backward stepwise regression. The “rms” package in the R software (version 4.3.2, R Foundation for Statistical Computing, Vienna, Austria) was run to establish the nomogram. The C-index and Brier score were calculated, and the ROC curve, calibration curve, and decision curve analysis (DCA) were plotted to visualize the combined performance of the model. The closer the C-index and the area under the curve (AUC) to 1, the better the discriminatory power of the model. The calibration curve was used to measure the accuracy of the absolute risk prediction value of the model and was further evaluated using the Hosmer–Lemeshow goodness-of-fit test. The Brier score can be interpreted as an extension of the Hosmer–Lemeshow test, the closer to 0, the better the model calibration. The value of the clinical application of the model was evaluated by DCA. Then, the Bootstrap method was used for internal validation to obtain the corrected C-index and corrected Brier score after 1000 sampling repetitions. Finally, the model is evaluated externally [29]. Variables with P < 0.10 were retained in the final model, and a two-tailed P < 0.05 was considered the level of statistical significance.

Results

Characteristics of participants

As shown in Fig. 1, a total of 1414 patients were identified for potential inclusion, with 262 excluded according to the exclusion criteria. Finally, 1152 eligible patients were included in the study, of which 810 comprised the training set. In the training cohort, the average age was 53.5 ± 12.6 years, with a predominance of males (63.5%) and a level IV labor intensity (69.1%). The majority had ARCO stage IV (63.8%) and steroid-induced ONFH (58.0%). One year after THA, 762 patients (94.1%) had regained independent walking ability.

Fig. 1
figure 1

Patients selection flowchart. THA: total hip arthroplasty; ONFH: osteonecrosis of the femoral head; RWI: recovered walking independence; LWI: losing walking independence

Full size image

Univariate and multivariate analysis

By analyzing the Youden index, the optimal cutoff value for age to predict LWI was 62 years. After univariate analysis, 12 potential predictors were identified in all variables (Table 1). In multivariate analysis, these variables were selected using backward stepwise regression, and the results showed that age 62 years or older, CCI 3 or higher, ARCO stage IV, reduced FO, and higher COUNT score were the independent risk factors for the LWI at one-year after THA (Table 2).

Table 1 Baseline characteristics of the study population*
Full size table
Table 2 Multivariate analyses of the independent risk factors associated with LWI
Full size table

Establishment and validation of the risk prediction model

The predictive nomogram was constructed based on the results of multifactorial analysis for more intuitive and convenient clinical application (Fig. 2). The AUC was 0.773 (95% CI 0.690–0.856) (Fig. 3), with high sensitivity and specificity (66.7% and 84.8%), which demonstrated the excellent discriminative capacity of the model. The C-index and Brier score were 0.773 and 0.049, respectively. After internal Bootstrap validation (B = 1000 repetitions), the correction values were 0.747 and 0.051, respectively, indicating that the model performed overall satisfactorily. The P-values of Hosmer–Lemeshow χ2 statistics of the calibration curve (Fig. 4) in the training and testing data sets were 0.096 and 0.850 (> 0.05), which illustrated a favorable consistency between the probability of predicting LWI and the actual probability of occurrence in patients who underwent THA for ONFH. Furthermore, the discriminatory power of the model performs equally well in the external validation dataset, with an AUC of 0.814.

Fig. 2
figure 2

Nomogram for predicting LWI at one year postoperatively in patients undergoing THA for ONFH. Five factors were calculated into the LWI prediction nomogram, with each predictor assigned a given score on the top points axis, and the predicted probability of LWI corresponding to the total points was shown on the bottom probability axis. LWI: losing walking independence; COUNT: controlling nutritional status; ARCO: Association Research Circulation Osseous; FO: femoral offset; CCI: Charlson comorbidity index

Full size image
Fig. 3
figure 3

Receiver-operating characteristic (ROC) curves for the nomogram in the training (A) and validation sets (B). The predictive accuracy of the nomogram was positively correlated with the area under the curve (AUC). The AUC of the nomogram was 0.773 and 0.814 in the training and validation sets, respectively, indicating that the model had good discriminative ability

Full size image
Fig. 4
figure 4

Calibration curves of nomogram in the training set (A, P = 0.096) and validation set (B, P = 0.850). X-axis represents the predicted probability of the model and y-axis represents the actual prob ability. The closer the red and green curves fit the ideal dashed line, the better the predictive consistency of the nomogram

Full size image

When using the nomogram, the level of COUNT score was first placed on the appointed variable axis. A line was then drawn straight up along the axis of the point to determine the risk score. The process was repeated for each variable, and a total score was calculated. The final sum was found on the “total points” axis and a vertical line was drawn to intersect the probability axis to obtain the predicted probability of LWI.

Clinical application

To validate the net benefit for ONFH patients who underwent THA, a decision curve analysis (DCA) was performed on the prediction model. The results (Fig. 5) suggested that the model enhanced the net benefit of the “treat all” or “no treatment” scenario when the threshold probability was between 2 and 60%. Similarly, this range was 1–37% in the validation model. The performance of the DCA showed that the model is good at guiding clinical practice.

Fig. 5
figure 5

Decision curve analysis (DCA) of nomogram in the training set (A) and validation set (B). DCA illustrated that the net benefit of the training model is higher in the threshold probability interval of 2–60%, and the net benefit of the validation model is higher in the threshold probability interval of 1–37%

Full size image

Discussion

This retrospective analysis of prospective collected data, specialized in patients who underwent primary unilateral THA for ONFH, is the first to establish and validate a nomogram to predict the risk of LWI at one-year postoperatively. The incidence of LWI was 5.9%, and age 62 years or older, CCI 3 or higher, ARCO stage IV, reduced FO, and higher COUNT score were identified as independent risk factors for LWI. The nomogram showed good predictive performance after internal and external validation.

Recovery of mobility after THA is a critical concern for surgeons. An umbrella review for consensus guidelines and a high-quality meta-analysis indicated that 82% of patients could return to sports, and 69% could resume work after THA [30, 31]. Independent walking is fundamental to daily activities, yet walking assessments after THA, particularly in patients with ONFH, are rarely reported. This study found a 5.9% incidence of LWI, with only one retrospective study that investigated 5707 patients reporting a 5.5% incidence at 2 years [9]. However, that study included all those who underwent THA in their institution, which may not represent patients with ONFH. Thus, our findings may add to existing knowledge for this subgroup of patients, pending validation in larger prospective studies.

The identification of older age and higher CCI as significant predictors aligns with previous findings [9, 32, 33]. This study establishes a lower age cutoff (62 years) compared to previous research on general THA patients (70 years) [9], this will undoubtedly significantly improve the diagnostic sensitivity and facilitate the detection of early as well as minor risk of LWI. Surgeons could implement secondary and tertiary prevention measures, including rehabilitation training, post-discharge healthcare, and nursing home placement, for patients at high risk of LWI as identified by this study.

Previous reported reduced global FO was associated with lower functional improvement and increased use of walking aids [28, 34], consistent with our findings. Weak hip abductors may be the main cause. Chamnongkich et al. found that patients with low FO had up to 25% abductor isometric muscle weakness compared to the intact limb [35]. Decreased hip abduction limits the ability to generate sufficient hip abductor muscle torque for proper pelvic tilt and upright posture [25]. This results in trunk sway during walking, smaller stride lengths, and reduced knee range of motion, which may directly impact walking recovery [36]. On the other side, reduced FO may in conjunction with the severity of ONFH to affect muscle function used for walking. This study found that patients with ARCO stage IV ONFH were more likely to suffer from LWI, often having prolonged medical histories and seeking surgery only after conservative treatments failed, leading to severe disability and pain. This caused serious abductor contracture, decreased muscle flexibility, and difficulty fully releasing abductor contracture [14]. These patients require more rigorous preoperative planning and intraoperative manipulation to restore appropriate global FO. Furthermore, surgical expectation management and individualized rehabilitation strategies should be developed for patients with long medical histories.

An interesting finding is that the CONUT score, a well-established nutritional screening tool, was associated with LWI in patients undergoing THA for ONFH. Growing evidence indicates that malnutrition strongly predicts adverse outcomes after joint arthroplasty [37]. Malnutrition has been observed in 11.3–27.0% of patients undergoing primary joint arthroplasty [38,39,40]. Prompt nutritional interventions could reduce postoperative complications and improve daily activities [41]. However, few studies have quantified the association between preoperative malnutrition and RWI in patients undergoing THA, with existing research primarily focusing on hip fracture populations [13, 42]. Only one study, involving 72,304 ONFH patients from the US National Inpatient Sample Database, examined the link between malnutrition and poor hospitalization outcomes, but did not assess walking ability or quality of life [43]. Orthopedic surgeons rarely consider nutritional interventions for ONFH patients, likely due to the younger, more active demographics of this group. Therefore, our findings supplement existing knowledge, suggesting that future medical workers should provide routine nutritional status screening and individualized nutritional intervention for this subgroup of patients.

Strengths of our study include prospective data collection, a large sample size, control of potential confounders, and the establishment and validation of a nomogram. However, several limitations should be noted. First, the study aimed to explore risk factors for LWI as quantified by the FIM-L scale, without considering commonly used outcomes such as the Harris Hip Score and Oxford Hip Score due to lack of follow-up data [44]. However, using independent walking ability as an objective measure could reduce the bias inherent in subjective assessments. Future studies should incorporate both objective and subjective outcomes for a more comprehensive evaluation. Second, despite adjusting for potential confounders, some unrecognized confounders, such as preoperative LLD and perceived LLD [45], during the follow-up period may still affect the LWI. Third, being a single-center study from a tertiary orthopedic referral center, selection bias may be present, limiting the generalizability to all ONFH patients eligible for THA. Finally, the functional deterioration of the contralateral hip could be a significant contributor to the loss of independent walking ability post-THA. While we accounted for the contralateral ARCO stage to assess hip function, further studies are needed to incorporate more comprehensive contralateral hip function scores or muscle strength assessments.

Conclusion

The incidence of LWI in patients who underwent primary unilateral THA for ONFH was 5.9%, and age 62 years or older, CCI 3 or greater, ARCO stage IV, reduced FO, and higher COUNT score were identified as independent risk factors for LWI. Based on this, the study established a risk prediction model that demonstrated strong discrimination power and clinical applicability both in internal and external validation. These findings support targeted screening and intervention to assist surgeons in assessing ambulation ability and managing rehabilitation for patients undergoing THA for ONFH.

Data availability

Please contact author for data requests.

References

  1. Wang T, Wu D, Li C, Cheng X, Yang Z, Zhang Y, et al. Comparison of outcomes after total hip arthroplasty between patients with osteonecrosis of the femoral head in association research circulation osseous stage III and stage IV: a five-year follow-up study. J Orthop Surg Res. 2024;19(1):170.

  2. Larson E, Jones LC, Goodman SB, Koo K-H, Cui Q. Early-stage osteonecrosis of the femoral head: where are we and where are we going in year 2018? Int Orthop. 2018;42(7):1723–8.

    Article  PubMed  Google Scholar 

  3. Migliorini F, Maffulli N, Baroncini A, Eschweiler J, Tingart M, Betsch M. Prognostic factors in the management of osteonecrosis of the femoral head: a systematic review. Surgeon. 2023;21(2):85–98.

    Article  PubMed  Google Scholar 

  4. Migliorini F, Maffulli N, Eschweiler J, Tingart M, Baroncini A. Core decompression isolated or combined with bone marrow-derived cell therapies for femoral head osteonecrosis. Expert Opin Biol Ther. 2021;21(3):423–30.

    Article  CAS  PubMed  Google Scholar 

  5. Sadile F, Bernasconi A, Russo S, Maffulli N. Core decompression versus other joint preserving treatments for osteonecrosis of the femoral head: a meta-analysis. Br Med Bull. 2016;118(1):33–49.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Mont MA, Salem HS, Piuzzi NS, Goodman SB, Jones LC. Nontraumatic osteonecrosis of the femoral head: where do we stand today? J Bone Joint Surg. 2020;102(12):1084–99.

    Article  PubMed  Google Scholar 

  7. Quaranta M, Miranda L, Oliva F, Aletto C, Maffulli N. Osteotomies for avascular necrosis of the femoral head. Br Med Bull. 2021;137(1):98–111.

  8. Migliorini F, La Padula G, Oliva F, Torsiello E, Hildebrand F, Maffulli N. Operative management of avascular necrosis of the femoral head in skeletally immature patients: a systematic review. Life (Basel). 2022;12(2):179

  9. Singh JA, Lewallen DG. Predictors of activity limitation and dependence on walking aids after primary total hip arthroplasty. J Am Geriatr Soc. 2010;58(12):2387–93.

    Article  PubMed  Google Scholar 

  10. Abdel MP, Roth PV, Harmsen WS, Berry DJ. What is the lifetime risk of revision for patients undergoing total hip arthroplasty? A 40-year observational study of patients treated with the Charnley cemented total hip arthroplasty. Bone Joint J. 2016;98–B(11):1436–40.

    Article  PubMed  Google Scholar 

  11. Artaud F, Singh-Manoux A, Dugravot A, Tzourio C, Elbaz A. Decline in fast gait speed as a predictor of disability in older adults. J Am Geriatr Soc. 2015;63(6):1129–36.

    Article  PubMed  Google Scholar 

  12. Singh JA, Lewallen DG. Patient-level clinically meaningful improvements in activities of daily living and pain after total hip arthroplasty: data from a large US institutional registry. Rheumatology. 2013;52(6):1109–18.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Cheng X, Chen W, Yan J, Yang Z, Li C, Wu D, Wang T, Zhang Y, Zhu Y. Association of preoperative nutritional status evaluated by the controlling nutritional status score with walking independence at 180 days postoperatively: a prospective cohort study in Chinese older patients with hip fracture. Int J Surg. 2023;109(9):2660–71.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Dong N, Yang C, Li SQ, Gao YH, Liu JG, Qi X. Effect of preoperative leg length discrepancy on functional outcome and patient satisfaction after total hip arthroplasty in cases of osteonecrosis of the femoral head. J Arthroplasty. 2016;31(12):2789–94.

    Article  PubMed  Google Scholar 

  15. Zhao D, Zhang F, Wang B, Liu B, Li L, Kim SY, Goodman SB, Hernigou P, Cui Q, Lineaweaver WC, et al. Guidelines for clinical diagnosis and treatment of osteonecrosis of the femoral head in adults (2019 version). J Orthop Translat. 2020;21:100–10.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Chughtai M, Piuzzi NS, Khlopas A, Jones LC, Goodman SB, Mont MA. An evidence-based guide to the treatment of osteonecrosis of the femoral head. Bone Joint J. 2017;99–B(10):1267–79.

    Article  PubMed  Google Scholar 

  17. Cheng X, Liu Y, Wang W, Yan J, Lei X, Wu H, Zhang Y, Zhu Y. Preoperative risk factor analysis and dynamic online nomogram development for early infections following primary hip arthroplasty in geriatric patients with hip fracture. Clin Interv Aging. 2022;17:1873–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Wang Y, Deng X, Wang Z, Zhu Y, Chen W, Zhang Y. Total hip arthroplasty or hemiarthroplasty for femoral neck fractures in elderly patients with neuromuscular imbalance. Aging Clin Exp Res. 2022;34(11):2825–33.

    Article  PubMed  Google Scholar 

  19. Wang Z, Zheng Z, Ye P, Tian S, Zhu Y, Chen W, Hou Z, Zhang Q, Zhang Y. Treatment of tibial plateau fractures: a comparison of two different operation strategies with medium-term follow up. J Orthop Translat. 2022;36:1–7.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Zhao K, Zhang J, Wang Z, Wang Y, Li J, Hou Z, Zhang Y, Chen W, Zhang Q. Multiplanar fracture reducer versus manual traction in the treatment of tibial shaft fractures with intramedullary nails. Int Orthop. 2022;46(4):911–7.

    Article  PubMed  Google Scholar 

  21. Li C, Wang T, Wu D, Guo H, Yang Z, Cheng X, Zhu Y, Zhang Y. Total hip arthroplasty after core decompression: time-to-event analysis and risk factors. Chin Med J. 2024;137(16):1988–90.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Tan B, Li W, Zeng P, Guo H, Huang Z, Fu F, Gao H, Wang R, Chen W. Epidemiological study based on China osteonecrosis of the femoral head database. Orthop Surg. 2021;13(1):153–60.

    Article  PubMed  Google Scholar 

  23. Chang W-T, Sun C-K, Wu J-Y, Yu C-H, Chang Y-J, Lin M-C, Lan K-M, Chen IW, Hung K-C. Association of prognostic nutritional index with long-term mortality in patients receiving percutaneous coronary intervention for acute coronary syndrome: a meta-analysis. Sci Rep. 2023;13(1):13102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Yamamoto T, Kawada K, Obama K. Inflammation-related biomarkers for the prediction of prognosis in colorectal cancer patients. International Journal of Molecular Sciences. 2021;22(15).

  25. Sato H, Maezawa K, Gomi M, Kajihara H, Hayashi A, Maruyama Y, Nozawa M, Kaneko K. Effect of femoral offset and limb length discrepancy on hip joint muscle strength and gait trajectory after total hip arthroplasty. Gait Posture. 2020;77:276–82.

    Article  PubMed  Google Scholar 

  26. McGrory BJ, Morrey BF, Cahalan TD, An KN, Cabanela ME. Effect of femoral offset on range of motion and abductor muscle strength after total hip arthroplasty. J Bone Joint Surg Br Volume. 1995;77(6):865–9.

    Article  CAS  Google Scholar 

  27. Röder C, Vogel R, Burri L, Dietrich D, Staub LP. Total hip arthroplasty: leg length inequality impairs functional outcomes and patient satisfaction. BMC Musculoskelet Disord. 2012;13(1):95.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Flecher X, Ollivier M, Argenson JN. Lower limb length and offset in total hip arthroplasty. Orthop Traumatol Surg Res. 2016;102(1 Suppl):S9–20.

    Article  CAS  PubMed  Google Scholar 

  29. Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ (Clinical Res ed). 2015;350:g7594.

    Google Scholar 

  30. Sowers CB, Carrero AC, Cyrus JW, Ross JA, Golladay GJ, Patel NK. Return to sports after total hip arthroplasty: an umbrella review for consensus guidelines. Am J Sports Med. 2023;51(1):271–8.

    Article  PubMed  Google Scholar 

  31. Hoorntje A, Janssen KY, Bolder SBT, Koenraadt KLM, Daams JG, Blankevoort L, Kerkhoffs G, Kuijer P. The effect of total hip arthroplasty on sports and work participation: a systematic review and meta-analysis. Sports Med. 2018;48(7):1695–726.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Penfold CM, Judge A, Sayers A, Whitehouse MR, Wilkinson JM, Blom AW. Temporal trends in comorbidity in adult elective hip and knee arthroplasty patients in England: a national population-based cohort study from the national joint registry. Bone Joint J. 2022;104–B(9):1052–9.

    Article  PubMed  Google Scholar 

  33. Zak SG, Lygrisse K, Tang A, Meftah M, Long WJ, Schwarzkopf R. Primary total hip arthroplasty outcomes in octogenarians. Bone Jt Open. 2021;2(7):535–9.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Mahmood SS, Mukka SS, Crnalic S, Wretenberg P, Sayed-Noor AS. Association between changes in global femoral offset after total hip arthroplasty and function, quality of life, and abductor muscle strength. A prospective cohort study of 222 patients. Acta Orthop. 2016;87(1):36–41.

    Article  PubMed  Google Scholar 

  35. Chamnongkich S, Asayama I, Kinsey TL, Mahoney OM, Simpson KJ. Difference in hip prosthesis femoral offset affects hip abductor strength and gait characteristics during obstacle crossing. Orthop Clin North Am. 2012;43(5):e48–58.

    Article  CAS  PubMed  Google Scholar 

  36. Sariali E, Klouche S, Mouttet A, Pascal-Moussellard H. The effect of femoral offset modification on gait after total hip arthroplasty. Acta Orthop. 2014;85(2):123–7.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Nanri Y, Shibuya M, Fukushima K, Uchiyama K, Takahira N, Takaso M. Preoperative malnutrition is a risk factor for delayed recovery of mobilization after total hip arthroplasty. Pm&R. 2021;13(12):1331–9.

    Article  Google Scholar 

  38. Ihle C, Weiß C, Blumenstock G, Stöckle U, Ochs BG, Bahrs C, Nüssler A, Schreiner AJ. Interview based malnutrition assessment can predict adverse events within 6 months after primary and revision arthroplasty - a prospective observational study of 351 patients. BMC Musculoskelet Disord. 2018;19(1):83.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Golladay GJ, Satpathy J, Jiranek WA. Patient optimization-strategies that work: malnutrition. J Arthroplast. 2016;31(8):1631–4.

    Article  Google Scholar 

  40. Pruzansky JS, Bronson MJ, Grelsamer RP, Strauss E, Moucha CS. Prevalence of modifiable surgical site infection risk factors in hip and knee joint arthroplasty patients at an urban academic hospital. J Arthroplast. 2014;29(2):272–6.

    Article  Google Scholar 

  41. Takahashi K, Momosaki R, Yasufuku Y, Nakamura N, Maeda K. Nutritional therapy in older patients with hip fractures undergoing rehabilitation: a systematic review and meta-analysis. J Am Med Dir Assoc. 2020;21(9):1364–1364.e6.

  42. Oba T, Makita H, Inaba Y, Yamana H, Saito T. New scoring system at admission to predict walking ability at discharge for patients with hip fracture. Orthop Traumatol Surg Research: OTSR. 2018;104(8):1189–92.

    Article  Google Scholar 

  43. Chuang FK, Yeh TT, Hung CC, Hsu CL, Shih JT, Shen PH. Effects of malnutrition on outcomes of patients with femoral head osteonecrosis undergoing total hip arthroplasty: a population-based study. Nutr Clin Pract. 2023;38(5):1104–14.

    Article  CAS  PubMed  Google Scholar 

  44. Nilsdotter A, Bremander A. Measures of hip function and symptoms: Harris Hip score (HHS), hip disability and osteoarthritis outcome score (HOOS), Oxford Hip score (OHS), Lequesne Index of Severity for Osteoarthritis of the hip (LISOH), and American Academy of Orthopedic Surgeons (AAOS) hip and knee questionnaire. Arthritis Care Res (Hoboken). 2011;63(Suppl 11):S200–207.

    PubMed  Google Scholar 

  45. Kim HS, Lee HJ, Yoo JJ. Minimal pre-operative leg length discrepancy as a risk factor of post-operative leg length discrepancy after total hip arthroplasty: a retrospective study of patients with non-traumatic osteonecrosis of the femoral head. BMC Musculoskelet Disord. 2023;24(1):954.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We sincerely thank all the patients in this study.

Funding

This research was supported by the Centre Guiding Local Science and Technology Development Fund Project (Science and Technology Innovation Base Project)-Grand (No. 236Z7754G). The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Author information

Author notes

  1. Chengsi Li and Dongwei Wu contributed equally to this work.

Authors and Affiliations

  1. Department of Orthopedic Surgery, The 3rd Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050051, P.R. China

    Chengsi Li, Dongwei Wu, Wei He, Tianyu Wang, Haichuan Guo, Zhenbang Yang, Xinqun Cheng, Yingze Zhang & Yanbin Zhu

  2. Hebei Chest Hospital, Shijiazhuang, Hebei, 050041, P.R. China

    Wei He

  3. Key Laboratory of Biomechanics of Hebei Province, Orthopedic Research Institute of Hebei Province, Shijiazhuang, Hebei, 050051, P.R. China

    Yingze Zhang & Yanbin Zhu

Authors
  1. Chengsi Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dongwei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wei He
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tianyu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Haichuan Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Zhenbang Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xinqun Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yingze Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yanbin Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

YBZ designed the study; DWW, WH, TYW, HCG, XQC and ZBY searched for relevant studies and abstracted the data; CSL and WH analyzed and interpreted the data; CSL and DWW wrote the manuscript, and YBZ and YZZ approved the final version of the manuscript. All authors reviewed the manuscript before submitting it.

Corresponding authors

Correspondence to Yingze Zhang or Yanbin Zhu.

Ethics declarations

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the local ethical committee (The 3rd Hospital of Hebei Medical University, Shijiazhuang, China; 2022-131-1).

Consent to participate

All subjects gave their written informed consent to take part in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, C., Wu, D., He, W. et al. Loss of walking independence one year after primary total hip arthroplasty for osteonecrosis of the femoral head: incidence and risk prediction model. J Orthop Surg Res 19, 580 (2024). https://doi.org/10.1186/s13018-024-05071-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13018-024-05071-6

Keywords

Journal of Orthopaedic Surgery and Research

ISSN: 1749-799X