Hypertension and grading are important risk factors for occult blood loss in hip arthroplasty: a retrospective study analysis

Objective: To quantify the impact of hypertension and its grading on occult blood loss (HBL) during total hip arthroplasty (THA) and to offer clinical guidance for minimizing HBL.

Methods: Baseline data from femoral neck fracture patients treated with THA between January 2018 and December 2022 were included. SPSS 26.0 statistical software was used for correlation analysis employing statistical methods, including independent samples t-test, Pearson correlation, and multiple linear regression, to identify risk factors for elevated postoperative HBL in THA patients. Hypertension severity was categorized according to international guidelines to investigate the effect of hypertension grading on HBL.

Results: The mean perioperative bleeding (TBL) among all patients was 1,123.39 ± 518.89 mL, and the mean HBL was 923.93 ± 489.04 mL, which accounted for 78.76% ± 16.09% of the TBL. HBL was significantly higher in hypertensive patients (957.98 ± 509.72 mL vs. 895.94 ± 469.97 mL, P = 0.042). Multiple linear regression analysis revealed that hypertension was an independent predictor of HBL (P = 0.030). Grade 2 hypertension increased HBL by 11.2% (996.46 ± 573.80 mL, P = 0.046), while grade 3 hypertension further increased HBL by 18.7% (1,063.76 ± 584.11 mL, P = 0.044). Hypoalbuminemia had a clinically relevant, but not statistically significant, synergistic effect with hypertension (ΔHBL = 119.60 mL, P = 0.297).

Conclusion: Hypertension ≥ grade 2 (systolic blood pressure ≥ 160 mmHg) independently exacerbates HBL in THA patients through a dose-response relationship. It is recommended that preoperative systolic blood pressure be maintained below 160 mmHg, and metabolic status be optimized to reduce the risk of blood transfusion.

Background

As total hip arthroplasty (THA) continues to mature and gain widespread adoption, it has become the gold-standard intervention for patients with end-stage hip diseases, including femoral head necrosis and femoral neck fractures (1). THA provides significant pain relief and effectively restores motor function by enhancing the biomechanical function of the hip joint (2). However, as clinical practice deepens and perioperative management improves, previously overlooked postoperative complications have gradually emerged. Among these, hidden blood loss (HBL) remains a critical yet under-recognized issue.

The concept of HBL was first quantitatively defined by Sehat et al. as the “calculated hemoglobin mass loss exceeding visible surgical blood loss and postoperative drainage” (3). Current evidence indicates that HBL accounts for 30%–50% of total blood loss during joint replacement surgery, primarily due to extravasation into tissue spaces, accumulation within the residual joint, and hemolysis (4). High levels of HBL lead to symptomatic anemia requiring transfusion, prolonged hospitalization, increased costs, and an elevated risk of surgical site infection and venous thromboembolism (5–9).

Hypertension, a modifiable risk factor, contributes to occult blood loss through several pathophysiological mechanisms. Available research evidence indicates that hypertension exacerbates HBL through endothelial dysfunction, which impairs vasoconstriction (10), an altered coagulation-fibrinolytic balance (11), and microvascular fragility in chronic hypertension (12). A recent retrospective study of 206 THA patients demonstrated that hypertension was a risk factor for postoperative blood loss, with a column-line graph weight of 23 (13). Despite these associations, few studies have directly compared HBL patterns between hypertensive and non-hypertensive cohorts, or conducted longitudinal studies comparing different blood pressure classifications and HBL. However, some studies have suggested that hypertension is not an independent risk factor for HBL (14, 15). More crucially, existing evidence predominantly treats hypertension as a binary variable, with few studies investigating the potential graded relationship between its severity and the volume of HBL. Therefore, investigating the impact of hypertension grading on HBL is critically important.

The aim of this study was to quantify differences in HBL between hypertensive and non-hypertensive THA patients, explore the relationship between different degrees of hypertension and HBL, and propose strategies for blood pressure management in THA patients to improve surgical prognostic care and reduce the need for blood transfusions.

Methods

Patients

A total of 952 patients who underwent hip replacement between January 2018 and June 2022 at the People's Hospital of North Jiangsu Province and the Fourth People's Hospital of Taizhou City were included. All patients were managed before and after surgery by orthopedic surgeons from the People's Hospital of North Jiangsu and the Fourth People's Hospital of Taizhou City. This retrospective study was conducted in accordance with the Declaration of Helsinki and was approved with a waiver of informed consent by the Ethics Committees/Institutional Review Boards of Yangzhou University Subei People's Hospital and the Fourth People's Hospital of Taizhou City (Approval/Waiver Nos. 2025ky090 and 2023-EC/TZFH-048).

The inclusion criteria were as follows: (1) Patients with a confirmed diagnosis of femoral neck fracture requiring THA, as determined by imaging and clinical evaluation; (2) Patients who had not previously undergone hip surgery; (3) Age ≥ 18 years; 4. No serious cardiovascular or cerebrovascular issues within 6 months prior to surgery; and 5. Possession of a complete and accurate record of information.

The exclusion criteria were: (1) Hematologic and coagulation disorders; (2) Patients who received a blood transfusion within 4 weeks prior to surgery; (3) Patients with a history of or current oncologic diseases; (4) Presence of other contraindications to surgery; (5) Withdrawal during the procedure or incomplete data.

Data collection

Data were collected from all patients, including gender, age, body mass index (BMI), operative time hypertension, diabetes, cardiovascular diseases, preoperative red blood cells (RBCs), preoperative hemoglobin (HB), preoperative hematocrit (HCT), preoperative platelets (PLTs), preoperative plasminogen time (PT), and preoperative activated partial thromboplastin time (APTT), preoperative international normalized ratio (INR), preoperative thrombin time (TT), preoperative fibrinogen (FIB), preoperative calcium, preoperative C-reactive protein (CRP), preoperative Erythrocyte Sedimentation Rate (ESR), preoperative DD polymers, preoperative albumin (ALB), American Society of Anesthesiologists Score (ASA) rating, intraoperative blood loss, operative time, 3-day postoperative HB and 3-day postoperative HCT. day HCT, etc. Hypertensive patients were controlled with preoperative medication to <140/90 mmHg.

To ensure the objectivity and accuracy of data collection, data were independently extracted from the hospital medical record system by two specialized surgeons. In cases of disputes over data processing, the two physicians reached a preliminary consensus and then discussed with a third physician until a collective agreement was reached.

Blood transfusion management

The hospital adheres to a restrictive blood transfusion management protocol in accordance with the Clinical Blood Transfusion Specifications (16). When the patient's hemoglobin (Hb) level is less than 70 g/L, or when the hemoglobin level is less than 80 g/L with severe anemia symptoms (such as extreme weakness, chest pain, extreme pallor, or hemorrhage), or in the presence of hemodynamic instability (such as a heart rate exceeding 100 beats per minute or systolic blood pressure below 90 mmHg), a blood transfusion will be administered. In this study, all patiens received leukocyte-reduced red blood cell transfusions.

Blood pressure management

This study implemented a standardized preoperative blood pressure management protocol for all enrolled patients with hypertension. In accordance with Chinese clinical guidelines, the preoperative blood pressure control targets were set as follows: <160/100 mmHg for general adult patients, and <150/90 mmHg for patients aged ≥60 years. To ensure these targets were met, the antihypertensive regimen was initiated and optimized at least two weeks prior to surgery during outpatient visits, accompanied by daily blood pressure monitoring. On the morning of the surgery, hypertensive patients were instructed to take their usual antihypertensive medications with a small sip of water to maintain hemodynamic stability and ensure safer surgical conditions.

Calculation of blood volume

The clinical estimation of the patient's blood volume (EBV) is performed using the formula EBV = K₁ × height³ (m) + K₂ × weight (kg) + K₃, with gender-specific coefficients: K₁ = 0.3669, K₂ = 0.03219, K₃ = 0.6041 for males, and K₁ = 0.3561, K₂ = 0.03308, K₃ = 0.1833 for females (17). After calculating the EBV, total blood loss (TBL) was determined using the Gross formula: TBL = EBV × (preoperative HCT—postoperative HCT)/HCT mean (18). Hidden blood loss (HBL) was then calculated using the formula HBL = TBL + blood transfusion—visible bleeding (intraoperative bleeding + postoperative drainage). Intraoperative blood loss was measured as the sum of the blood collected in the suction bottle and the blood absorbed by the surgical gauze.

Statistical methods

All statistical analyses were conducted using SPSS (version 26.0, IBM, USA). For data presentation, continuous variables were expressed as mean ± standard deviation (i.e., M ± SD), while categorical variables were presented as counts and percentages [N (%)]. The independent samples t-test was used to calculate significant differences in HBL between groups, while Pearson's correlation coefficient was used to analyze differences between measurements. A one-way analysis of variance (ANOVA) was employed for comparisons between groups. Statistically significant variables were selected for multiple linear regression analysis to identify independent risk factors associated with HBL. The results were considered statistically significant when the p-value was less than 0.05, in accordance with the statistical criteria set for this study.

Results

Perioperative parameters

Data from 1,035 hypertensive and non-hypertensive patients were retrospectively analyzed, including 364 (35.2%) males and 671 (64.8%) females. Of these, 467 (45.1%) were hypertensive patients with a mean age of 62.89 ± 11.36 years and a mean BMI of 23.25 ± 3.43, while 568 (54.9%) were non-hypertensive patients with a mean age of 69.51 ± 8.40 years and a mean BMI of 24.68 ± 3.33. The hypertensive occult blood loss was 957.98 ± 509.72 mL, while the non-hypertensive occult blood loss was 895.94 ± 469.97 mL, with further details provided in Table 1. Table 2 presents data on TBL, visible blood loss, HBL, and the percentage of HBL calculated for HGB loss, HCT loss, and the number of patients with preoperative and postoperative HGB <100 g/L. The mean TBL was 1,123.39 ± 518.89 mL, and the mean HBL was 923.93 ± 489.04 mL, which accounted for 78.76% ± 16.09% of the TBL. Thirty-six patients (3.5%) had preoperative Hb <100 g/L, which increased to 268 patients (25.9%) after surgery.

Table 1

Table 1. Information on baseline characteristics of patients with hypertension and non-hypertension.

Table 2

Table 2. Parameters related to perioperative blood loss.

Univariate analysis

According to the results of univariate analysis, HBL was statistically significant (P < 0.05) with respect to age, gender, BMI, hypertension, preoperative RBC, preoperative HB, preoperative HCT, preoperative FIB, preoperative DD, preoperative CA, preoperative CRP, preoperative ALB, operative time, ASA, and EBV. There was no statistically significant difference with respect to preoperative PLT, preoperative PT, preoperative PTINR, preoperative APTT, preoperative TT, preoperative ESR, side of surgery, diabetes, cardiovascular diseases, smoking history, drinking history, osteoporosis, drainage volume, intraoperative blood loss, and hospitalization days. The measured data and calculated results are presented in Tables 3, 4, respectively.

Table 3

Table 3. Results of HBL and Pearson's correlation analysis for different count data sets.

Table 4

Table 4. Correlation analysis results of HBL and independent samples t-test for different count data groups in the perioperative period.

Multiple linear regression analysis

Postoperative HBL was used as the dependent variable, with the 15 statistically significant variables mentioned above serving as independent variables in the multiple linear regression analysis. The results indicated that HBL was associated with BMI, hypertension, operative time, preoperative calcium, preoperative HCT, preoperative ALB, and preoperative EBV (Table 5).

Table 5

Table 5. Results of multiple linear regression analysis.

Impact of hypertension stratification

To further investigate the impact of hypertension severity on HBL, hypertension was classified into 3 grades according to international standards (19). Stratification analysis showed that the HBL of grade 1 hypertensive patients (n = 319) was 932.74 ± 475.29 mL, which was not significantly different from that of the non-hypertensive group (895.94 ± 469.97 mL, P = 0.265). HBL in grade 2 hypertensive patients (n = 113) significantly increased to 996.46 ± 573.80 mL, reflecting an 11.2% increase compared to the non-hypertensive group (P = 0.046). Blood loss in grade 3 hypertensive patients (n = 35) further increased to 1,063.76 ± 584.11 mL, corresponding to an 18.7% increase (P = 0.044) (Table 6). In addition, among patients with combined hypoalbuminemia, HBL increased by 119.60 mL compared with the non-hypoalbuminemia group (a relative increase of 11.3%), but this difference was not statistically significant (P = 0.297) (Table 7).

Table 6

Table 6. Exploring the effect of severity of hypertension.

Table 7

Table 7. Exploring the effect of hypertension combined with hypoalbuminemia on HBL.

Discussion

With ongoing advances in medical technology and socio-economic development, there has been a growing emphasis on perioperative management and the postoperative quality of life for patients. In particular, addressing complications such as occult blood loss (HBL) and the need for blood transfusions following total hip arthroplasty (THA) has become a key area of focus (20). In the field of THA, previous literature has generally reported that hidden blood loss (HBL) can account for 50% to more than 80% of total blood loss (TBL) (4, 21), underscoring its critical role in perioperative blood loss. While significant progress has been made in developing strategies to minimize overt blood loss in THA patients (22) the role of HBL, particularly the impact of hypertension and its stratification in relation to HBL, remains inadequately understood. To address this gap, this study analyzes clinical data from 1,035 patients using the Gross equation, a widely used method in orthopedic research. Compared to previous studies, a more precise risk-assessment model for THA blood loss was developed by excluding patients with coagulation disorders, implementing stringent blood pressure control, and monitoring a range of physiological parameters (20, 23). The results showed that the mean HBL in the study cohort was 923.93 ± 489.04 mL, accounting for 78.76% ± 16.09% of the total perioperative blood loss, which averaged 1,123.39 ± 518.89 mL.

Univariate analysis identified hypertension as a significant risk factor for occult blood loss, and multiple linear regression confirmed hypertension as an independent predictor of hip fracture-related blood loss (HBL) (p < 0.05). These findings are consistent with previous research (24). The underlying pathophysiological mechanisms are thought to involve vascular endothelial dysfunction and altered hemostasis. Chronic hypertension has been shown to reduce tight junction proteins (e.g., ZO-1) by 30%–50%, impairing vascular barrier integrity and facilitating erythrocyte extravasation (25–27). Additionally, hypertensive patients exhibit elevated D-dimer levels (1.5- to 2.2-fold increase), suggesting enhanced fibrinolysis and impaired clot stability, a phenomenon also observed in atherosclerotic populations (28). Collectively, these molecular changes contribute to the exacerbation of microvascular leakage.

Notably, unlike the study by Foss et al., which focused solely on surgical factors (29), the present study explores the relationship between hypertension stratification and occult blood loss. Our findings demonstrated a significant increase in HBL in THA patients with hypertension ≥ grade 2 (i.e., systolic blood pressure ≥160 mmHg), with a dose-dependent effect (grade 2: 11.2% increase; grade 3: 18.7% increase). This result extends beyond previous analyses of surgical risk factors, suggesting the presence of a potential clinical threshold. When systolic blood pressure consistently exceeds 160 mmHg, the hemodynamic load increases significantly, exacerbating endothelial damage and potentially increasing the structural fragility of the microvasculature, making it more prone to rupture and bleeding during surgery. Literature has shown that hemodynamic instability, characterized by excessive blood pressure fluctuations during surgery, exacerbates HBL by increasing capillary shear stress and compromising endothelial glycocalyx integrity (30, 31). These findings highlight the critical importance of meticulous preoperative blood pressure management.

Although not statistically significant (p = 0.277), the interaction between hypertension and hypoalbuminemia resulted in an increase in HBL by 119.60 mL (11.30%). This non-significant result could be due to the relatively small sample size in the low albumin subgroup and the considerable inter-individual variability in blood loss. Nonetheless, its potential clinical relevance should not be overlooked. The study also found a significant correlation between blood loss and transfusion likelihood, with each additional unit of blood loss increasing the probability of requiring a transfusion. Similarly, Porcaro et al. reported that for every 1 mL increase in intraoperative blood loss, the risk ratio for blood transfusion was 1.002 (32, 33). These findings suggest that metabolic disorders may exacerbate vascular permeability through multiple mechanisms. Hypoalbuminemia, by reducing plasma colloid osmolality, creates a gradient that further worsens hypertension-induced endothelial dysfunction (34–36). Our result echoes the view proposed by Hosseini-Monfared et al. (37), reinforcing previous studies linking metabolic syndrome to increased surgical complications and emphasizing the need for preoperative metabolic optimization.

Based on the dose-response relationship observed between hypertension grading and HBL, we propose a stratified blood pressure management protocol that integrates preoperative, intraoperative, and metabolic management. This multifaceted approach is intended to enhance therapeutic outcomes through targeted interventions. Specifically, we recommend setting the preoperative systolic blood pressure target below 160 mmHg to intervene effectively in high-risk patients with grade 2 or higher hypertension. This strategy aims to reduce shear stress on the microvascular endothelial barrier caused by excessive hemodynamic pressure, thereby minimizing vascular leakage at its source. However, it is important to note that this threshold is based on retrospective data and should be validated in prospective studies. In addition, continuous intraoperative hemodynamic monitoring is essential to maintain blood pressure stability, preventing endothelial glycocalyx shedding and capillary stress injuries due to excessive blood pressure fluctuations, thereby mitigating intraoperative exacerbation of HBL. Furthermore, correcting metabolic disturbances such as hypoalbuminemia can increase plasma colloid osmotic pressure, reinforcing vascular wall integrity and synergistically enhancing blood pressure management to reduce erythrocyte extravasation. This comprehensive, multimodal management strategy is expected to reduce HBL by 11%–19% in high-risk patients, decrease transfusion requirements, and improve early rehabilitation outcomes by optimizing perioperative physiological conditions, ultimately enhancing postoperative recovery.

Limitations

This study has several limitations. First, its retrospective, single-center design introduces the risk of selection bias and limits the external validity of our findings, making it difficult to generalize the results to other populations or clinical settings. Second, key perioperative data were neither standardized nor consistently available, which may have affected the robustness of our analysis. In particular, the lack of ambulatory blood pressure monitoring precluded the evaluation of blood pressure variability, a potential confounder that could have influenced the assessment of hidden blood loss. Furthermore, although certain surgical variables, such as operative approach, duration, and surgeon experience, were not included in the analysis, we also note the absence of standardized data on intraoperative use of hemostatic agents, a critical factor that may have influenced bleeding outcomes. Third, while hypertension was identified as an independent risk factor for blood loss, our analysis could not account for all relevant confounders. Specifically, we were unable to assess the differential effects of various classes of antihypertensive medications on bleeding risk due to the unavailability of detailed pharmacological data. Finally, while the estimation of hidden blood loss using the Gross formula is widely used and practical, it is based on theoretical calculations that rely on estimated blood volumes, which may not fully capture the complex dynamics of perioperative fluid shifts.

Summary and outlook

In conclusion, this study confirmed hypertension as a risk factor for hidden blood loss (HBL) through a retrospective analysis of 1,035 cases. The stratified analysis demonstrated that HBL increased in a dose-dependent manner when hypertension reached ≥ grade 2. Additionally, metabolic disorders such as hypoalbuminemia further exacerbated HBL. Therefore, we recommend the implementation of individualized strategies for hypertensive patients, including preoperative control of systolic blood pressure to <160 mmHg and optimization of metabolic indices. These measures are expected to reduce HBL and subsequently lower the rate of postoperative transfusions in hypertensive patients undergoing total hip arthroplasty (THA).

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.

Ethics statement

The studies involving humans were approved by the Ethics Committees/Institutional Review Boards of Yangzhou University Northern Jiangsu People's Hospital and the Fourth People's Hospital of Taizhou City (Approval/Waiver Nos. 2025ky090 and 2023-EC/TZFH-048). The studies were conducted in accordance with the local legislation and institutional requirements. The ethics committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants' legal guardians/next of kin.

Author contributions

ES: Data curation, Methodology, Writing – original draft. FG: Investigation, Methodology, Validation, Writing – review & editing. GZ: Conceptualization, Supervision, Writing – review & editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Kahn TL, Frandsen JJ, Blackburn BE, Anderson LA, Pelt CE, Gililland JM, et al. Anterior-based approaches to total hip arthroplasty: beyond the learning curve. J Arthroplasty. (2022) 37(7):S552–5. doi: 10.1016/j.arth.2022.01.042

PubMed Abstract | Crossref Full Text | Google Scholar

2. Bloch BV, White JJE, Matar HE, Berber R, Manktelow ARJ. Should patient age thresholds dictate fixation strategy in total hip arthroplasty? Bone Joint J. (2022) 104-B(2):206–11. doi: 10.1302/0301-620X.104B2.BJJ-2021-1199.R1

PubMed Abstract | Crossref Full Text | Google Scholar

3. Jaramillo S, Montane-Muntane M, Gambus PL, Capitan D, Navarro-Ripoll R, Blasi A. Perioperative blood loss: estimation of blood volume loss or haemoglobin mass loss? Blood Transfus. (2019) 18(1):20. doi: 10.2450/2019.0204-19

PubMed Abstract | Crossref Full Text | Google Scholar

4. Sun Y, Miao H, Gong H, Zhang Y, Hong W. Risk factors analysis and nomogram model establishment of hidden blood loss in overweight and obese elderly patients after total hip arthroplasty. Clin Interv Aging. (2024) 19:57–66. doi: 10.2147/CIA.S428307

PubMed Abstract | Crossref Full Text | Google Scholar

5. Zhu J, Xu C, Jiang Y, Zhu J, Tu M, Yan X. Development and validation of a machine learning algorithm to predict the risk of blood transfusion after total hip replacement in patients with femoral neck fractures: a multicenter retrospective cohort study. Orthop Surg. (2024) 16(8):2066–80. doi: 10.1111/os.14160

PubMed Abstract | Crossref Full Text | Google Scholar

6. Li G, Yu F, Liu S, Weng J, Qi T, Qin H, et al. Patient characteristics and procedural variables are associated with length of stay and hospital cost among unilateral primary total hip arthroplasty patients: a single-center retrospective cohort study. BMC Musculoskelet Disord. (2023) 24(1):6. doi: 10.1186/s12891-022-06107-w

PubMed Abstract | Crossref Full Text | Google Scholar

7. Lewis SR, Macey R, Parker MJ, Cook JA, Griffin XL. Arthroplasties for hip fracture in adults. Cochrane Database Syst Rev. (2022) 2(2):CD013410. doi: 10.1002/14651858.CD013410.pub2

PubMed Abstract | Crossref Full Text | Google Scholar

8. Liu J, Lei Y, Liao J, Liang X, Hu N, Huang W. Pre-emptive antifibrinolysis: its role and efficacy in hip fracture patients undergoing total hip arthroplasty. J Arthroplasty. (2022) 37(4):755–62. doi: 10.1016/j.arth.2021.12.034

PubMed Abstract | Crossref Full Text | Google Scholar

9. Li ZJ, Zhao MW, Zeng L. Additional dose of intravenous tranexamic acid after primary total knee arthroplasty further reduces hidden blood loss. Chin Med J. (2018) 131(06):638–42. doi: 10.4103/0366-6999.226884

PubMed Abstract | Crossref Full Text | Google Scholar

10. Gallo G, Volpe M, Savoia C. Endothelial dysfunction in hypertension: current concepts and clinical implications. Front Med (Lausanne). (2022) 8:798958. doi: 10.3389/fmed.2021.798958

PubMed Abstract | Crossref Full Text | Google Scholar

11. Bellien J, Iacob M, Richard V, Wils J, Cam-Duchez VL, Joannides R. Evidence for wall shear stress-dependent t-PA release in human conduit arteries: role of endothelial factors and impact of high blood pressure. Hypertens Res. (2021) 44(3):310–7. doi: 10.1038/s41440-020-00554-5

PubMed Abstract | Crossref Full Text | Google Scholar

12. Durante A, Mazzapicchi A, Baiardo Redaelli M. Systemic and cardiac microvascular dysfunction in hypertension. Int J Mol Sci. (2024) 25(24):13294. doi: 10.3390/ijms252413294

PubMed Abstract | Crossref Full Text | Google Scholar

13. Hong WS, Zhang YX, Lin Q, Sun Y. Risk factors analysis and the establishment of nomogram prediction model of hidden blood loss after total hip arthroplasty for femoral neck fracture in elderly women. Clin Interv Aging. (2022) 17:707–15. doi: 10.2147/CIA.S363682

PubMed Abstract | Crossref Full Text | Google Scholar

14. Cui H, Chen K, Lv S, Yuan C, Wang Y. An analysis of perioperative hidden blood loss in femoral intertrochanteric fractures: bone density is an important inXuencing factor. BMC Musculoskelet Disord. (2021) 22(1):6. doi: 10.1186/s12891-020-03922-x

PubMed Abstract | Crossref Full Text | Google Scholar

15. Wei D, Jiang Y, Long X, Huang N, Xiang J, Cheng J, et al. Predicting the perioperative transfusion risk of proximal femoral antirotation nailing (PFNA) for elderly patients with intertrochanteric fractures: a new predictive nomogram. Biomed Eng Online. (2025) 24(1):80. doi: 10.1186/s12938-025-01419-z

PubMed Abstract | Crossref Full Text | Google Scholar

16. Cap AP, Beckett A, Benov A, Borgman M, Chen J, Corley JB, et al. Whole blood transfusion. Mil Med. (2018) 183(suppl_2):44–51. doi: 10.1093/milmed/usy120

PubMed Abstract | Crossref Full Text | Google Scholar

17. Nadler SB, Hidalgo JU, Bloch T. Prediction of blood volume in normal human adults. Surgery. (1962) 51(2):224–32.21936146

PubMed Abstract | Google Scholar

18. Gross JB. Estimating allowable blood loss: corrected for dilution. Anesthesiology. (1983) 58(3):277–80. doi: 10.1097/00000542-198303000-00016

PubMed Abstract | Crossref Full Text | Google Scholar

19. Carey RM, Whelton PK. 2017 ACC/AHA hypertension guideline writing committee*. prevention, detection, evaluation, and management of high blood pressure in adults: synopsis of the 2017 American College of Cardiology/American Heart Association hypertension guideline. Ann Intern Med. (2018) 168(5):351–8. doi: 10.7326/M17-3203

PubMed Abstract | Crossref Full Text | Google Scholar

20. Yoon PW, Kim HJ, Yoon JY, Moon J, Lee S. The efficacy of oxidised regenerated cellulose powder in reducing blood loss during primary total hip arthroplasty: a retrospective cohort study. J Orthop Surg Res. (2025) 20(1):368. doi: 10.1186/s13018-025-05782-4

PubMed Abstract | Crossref Full Text | Google Scholar

21. Jin JF, Chen HR, Peng YJ, Dai J, Wang QL, Yan J. Risk factors for hidden blood loss in unilateral biportal endoscopic lumbar interbody fusion: a single-center retrospective study. BMC Musculoskelet Disord. (2024) 25(1):1–7. doi: 10.1186/s12891-024-08104-7

PubMed Abstract | Crossref Full Text | Google Scholar

22. Nehls F, Schlppi M, Madjdpour C, Meier C, Wahl P. Blood loss in primary total hip arthroplasty occurs mainly postoperatively, but current formulas for calculating blood loss are inaccurate: a retrospective study of 208 cases. Arch Orthop Trauma Surg. (2025) 145(1):283. doi: 10.1007/s00402-025-05815-x

PubMed Abstract | Crossref Full Text | Google Scholar

23. Wood RC III, Stewart DW, Slusher L, El-Bazouni H, Cluck D, Freshour J, et al. Retrospective evaluation of postoperative bleeding events in patients receiving rivaroxaban after undergoing total hip and total knee arthroplasty: comparison with clinical trial data. Pharmacotherapy. (2015) 35(7):663–9. doi: 10.1002/phar.1608

PubMed Abstract | Crossref Full Text | Google Scholar

24. Wang T, Guo J, Hou Z. Risk factors for perioperative hidden blood loss after intertrochanteric fracture surgery in Chinese patients: a meta-analysis. Geriatr Orthop Surg Rehabil. (2022) 13:21514593221083816. doi: 10.1177/21514593221083816

PubMed Abstract | Crossref Full Text | Google Scholar

25. El Bakkouri Y, Chidiac R, Delisle C, Corriveau J, Cagnone G, Gaonac’h-Lovejoy V, et al. ZO-1 interacts with YB-1 in endothelial cells to regulate stress granule formation during angiogenesis. Nat Commun. (2024) 15(1):4405. doi: 10.1038/s41467-024-48852-7

PubMed Abstract | Crossref Full Text | Google Scholar

26. Hansen ES, Rinde FB, Edvardsen MS, Hindberg K, Latysheva N, Aukrust P, et al. Elevated plasma D-dimer levels are associated with risk of future incident venous thromboembolism. Thromb Res. (2021) 208:121–6. doi: 10.1016/j.thromres.2021.10.020

PubMed Abstract | Crossref Full Text | Google Scholar

27. Chen YC, Huang AL, Kyaw TS, Bobik A, Peter K. Atherosclerotic plaque rupture: identifying the straw that breaks the camel’s back. Arterioscler Thromb Vasc Biol. (2016) 36(8):e63–72. doi: 10.1161/ATVBAHA.116.307993

PubMed Abstract | Crossref Full Text | Google Scholar

28. Degroote C, von Känel R, Thomas L, Zuccarella-Hackl C, Messerli-bürgy N, Saner H, et al. Lower diurnal HPA-axis activity in male hypertensive and coronary heart disease patients predicts future CHD risk. Front Endocrinol (Lausanne). (2023) 14:1080938. doi: 10.3389/fendo.2023.1080938

PubMed Abstract | Crossref Full Text | Google Scholar

29. Foss NB, Kehlet H. Hidden blood loss after surgery for hip fracture. J Bone Joint Surg Br. (2006) 88(8):1053–9. doi: 10.1302/0301-620X.88B8.17534

PubMed Abstract | Crossref Full Text | Google Scholar

30. Zhao N, Liu C, Tian X, Yang J, Wang T. Acute brain injury increases pulmonary capillary permeability via sympathetic activation-mediated high fluid shear stress and destruction of the endothelial glycocalyx layer. Exp Cell Res. (2024) 434(2):113873. doi: 10.1016/j.yexcr.2023.113873

PubMed Abstract | Crossref Full Text | Google Scholar

31. Cheng Z, Zhang L, Liu M, Liang D, Huang X, Peng L. Factors inXuencing preoperative blood pressure Xuctuations in patients undergoing elective surgery: a retrospective observational study. Int J Gen Med. (2025) 18:1615–22. doi: 10.2147/IJGM.S507706

PubMed Abstract | Crossref Full Text | Google Scholar

32. Newman JM, Webb MR, Klika AK, Murray TG, Barsoum WK, Higuera CA. Quantifying blood loss and transfusion risk after primary vs conversion total hip arthroplasty. J Arthroplasty. (2017) 32(6):1902–9. doi: 10.1016/j.arth.2017.01.038

PubMed Abstract | Crossref Full Text | Google Scholar

33. Porcaro AB, Rizzetto R, Amigoni N, Tafuri A, Shakir A, Tiso L, et al. Severe intraoperative bleeding predicts the risk of perioperative blood transfusion after robot-assisted radical prostatectomy. J Robot Surg. (2022) 16(2):463–71. doi: 10.1007/s11701-021-01262-z

PubMed Abstract | Crossref Full Text | Google Scholar

34. Valeriani E, Pannunzio A, Palumbo IM, Bartimoccia S, Cammisotto V, Castellani V, et al. Risk of venous thromboembolism and arterial events in patients with hypoalbuminemia: a comprehensive meta-analysis of more than 2 million patients. J Thromb Haemostasis. (2024) 22(10):2823–33. doi: 10.1016/j.jtha.2024.06.018

PubMed Abstract | Crossref Full Text | Google Scholar

35. Wiedermann CJ. Moderator effect of hypoalbuminemia in volume resuscitation and plasma expansion with intravenous albumin solution. Int J Mol Sci. (2022) 23(22):14175. doi: 10.3390/ijms232214175

PubMed Abstract | Crossref Full Text | Google Scholar

36. McLean C, Mocanu V, Birch DW, Karmali S, Switzer NJ. Hypoalbuminemia predicts serious complications following elective bariatric surgery. Obes Surg. (2021) 31(10):4519–27. doi: 10.1007/s11695-021-05641-1

PubMed Abstract | Crossref Full Text | Google Scholar

37. Hosseini-Monfared P, Mirahmadi A, Sarzaeem MM, Pourshahryari S, Aminnia P, Poursalehian M, et al. Ascorbic acid reduces the blood boss after total knee arthroplasty: insights from a randomized controlled trial. Arthroplasty Today. (2025) 32:101618. doi: 10.1016/j.artd.2025.101618

PubMed Abstract | Crossref Full Text | Google Scholar