Preoperative Venous Circumference-Squared-to-Area Ratio (C2/A) and D-dimer for Deep Vein Thrombosis Prediction After Orthopedic Surgery

Summary

This article describes a single preoperative ultrasound-derived venous C²/A measurement, complemented by D-dimer, for identifying orthopedic surgery patients at increased risk of postoperative lower-limb DVT.

Abstract

Deep vein thrombosis (DVT) is a common complication after orthopedic surgery. This prospective observational study evaluated whether a single preoperative baseline measurement of the venous circumference-squared-to-area ratio (C2/A), alone and with D-dimer, was associated with DVT detected during the first 7 postoperative days. One hundred fifty adults undergoing orthopedic surgery were enrolled; 37 developed DVT and 113 did not. Preoperative circumference (C) and area (A) were measured separately at end-expiration with the ultrasound system's built-in measurement package during the same acquisition cycle. Investigators calculated C2/A as C2 divided by A. To apply this rule consistently to the retained participant-level dataset, all revision analyses used C2/A recalculated from the retained C and A fields. Postoperative ultrasound was performed at 12-h intervals for 7 days under a prespecified intensified study-surveillance schedule used only for outcome ascertainment. The areas under the receiver operating characteristic curves were 0.893 for common femoral vein C2/A, 0.817 for superficial femoral vein C2/A, 0.906 for popliteal vein C2/A, and 0.834 for D-dimer. The originally specified superficial femoral vein C2/A plus D-dimer model had an apparent area under the curve of 0.887 and a stratified 5-fold cross-validated out-of-fold area under the curve of 0.877. A 5-variable exploratory model had an out-of-fold area under the curve of 0.938. Using cohort-derived thresholds of 16.26 for superficial femoral vein C2/A and 2.15 mg/L FEU for D-dimer, DVT occurred in 0 of 78 patients with neither marker elevated, 15 of 50 with one elevated, and 22 of 22 with both elevated. Preoperative venous C2/A and D-dimer were associated with early postoperative DVT, but the thresholds and models are exploratory and require external validation.

Introduction

Lower-limb deep vein thrombosis (DVT) remains a major perioperative complication after orthopedic surgery. Surgical trauma, reduced mobility, local venous stasis, and postoperative hypercoagulability converge to increase venous thromboembolism risk, and thrombus propagation or embolization can lead to pulmonary embolism and substantial morbidity^1,2. Although pharmacologic, exercise-based, and mechanical prophylaxis strategies are widely used, postoperative DVT continues to occur, indicating a need for preoperative markers that are non-invasive and closely related to the local venous environment^3,4.

Current screening relies heavily on Doppler ultrasonography and D-dimer testing^5,6. Ultrasonography is non-invasive, repeatable, and central to DVT diagnosis, but conventional measurements such as diameter and flow are often interpreted after thrombus formation or after hemodynamic disturbance is already evident^7,8. D-dimer is sensitive for thrombotic disease but has limited specificity in perioperative patients because age, trauma, inflammation, and surgery-related fibrinolysis can elevate circulating levels without established DVT^9,10. Recent age-adjusted D-dimer work also emphasizes that age materially influences interpretation, although those thresholds were designed for diagnostic exclusion rather than preoperative prediction¹¹. Clinical risk scores such as the Caprini score summarize systemic and historical risk factors, but they do not directly quantify subtle local venous geometry¹².

Venous cross-sectional geometry provides a plausible link between local anatomy and thrombotic risk. The morphology index C²/A, calculated as cross-sectional circumference squared divided by cross-sectional area, increases as a vessel becomes less circular or more distorted. A higher value may reflect flattening, reduced wall compliance, external compression, or abnormal transmural pressure¹³. Morphological studies of venous disease support the relevance of venous wall and lumen structure to clinical venous dysfunction¹³. C²/A may therefore capture local structural susceptibility, whereas D-dimer reflects systemic fibrin turnover. Combined with a clinical score such as Caprini, these two markers may provide a more complete preoperative risk picture¹⁴. Therefore, this study investigated the predictive value of single baseline preoperative C²/A measured in the CFV, SFV, and POV for postoperative DVT after orthopedic surgery, and whether combining C²/A with D-dimer improves discrimination.

Protocol

The study was conducted in accordance with institutional human research guidelines. The study was approved by the Ethics Committee of Xijing Hospital, Air Force Medical University (approval number KY20232031-F-1). All participants were informed of the study procedures and provided written informed consent before enrollment. The main equipment, assays, software, and RRID status are listed in the Table of Materials. Because this was a prospective observational study without an experimental intervention, no separate experimental control group was required.

Study design and participants

This prospective observational study enrolled 150 patients scheduled for orthopedic surgery at the First Affiliated Hospital of Air Force Medical University between December 2023 and July 2024. Eligible patients had no preoperative lower-limb DVT and were able to complete the standardized ultrasound examination. Patients with pre-existing DVT, a previous history of DVT, lower-limb vascular injury or deformity, deep venous valve dysfunction, heart failure, lower-limb venous hypertension caused by pelvic or abdominal tumors, coagulation abnormalities, long-term anticoagulant therapy, a severe fracture preventing cooperation with the examination, or impaired consciousness were excluded. Patients without postoperative DVT served as the comparator group.

Preoperative clinical and laboratory data

Baseline clinical variables included age, sex, body mass index, medical history, Caprini score, C-reactive protein, platelet count, D-dimer, surgical duration, tourniquet duration, and bed-rest duration. D-dimer was measured in a preoperative fasting venous blood sample on a fully automated coagulation analyzer using an immunoturbidimetric method and was reported in mg/L fibrinogen-equivalent units (FEU). The manufacturer, analyzer model, and assay details are listed in the Table of Materials.

Ultrasound examination and C²/A measurement

All ultrasound examinations were performed with a color Doppler ultrasound system equipped with a 12–3 MHz high-frequency linear-array transducer in venous imaging mode. Patients were placed in the supine position with the lower limbs externally rotated. The common femoral vein (CFV), superficial femoral vein (SFV), and popliteal vein (POV) were scanned sequentially at prespecified anatomic levels. Probe pressure was kept as low as possible to avoid visible venous deformation. The manufacturer and exact system and transducer models are listed in the Table of Materials.

For each venous segment, cross-sectional circumference (C) and cross-sectional area (A) were measured separately on transverse images at end-expiration with the bedside ultrasound system's built-in measurement package. C and A were obtained during the same acquisition cycle. Three acquisitions were performed per segment and summarized in the retained participant-level table. Investigators calculated C² and the unitless morphology index C²/A; no external calculation software was used. For the revision analysis, the stated calculation rule was applied uniformly to the retained numerical fields, with C²/A calculated as the square of the retained C value divided by the retained A value. Because C and A were separate device-derived measurements rather than an analytically exported perimeter-area pair from a shared digital contour, C²/A is interpreted as a measurement-derived morphology index. Diameter, flow velocity, and blood flow volume were measured on longitudinal images. All preoperative examinations were performed by the same ultrasound physician, who had more than 5 years of experience and was blinded to the baseline clinical and laboratory data at the time of measurement. Formal intraobserver and interobserver reproducibility analyses were not prospectively performed. Postoperative surveillance was used only to ascertain DVT outcomes.

Postoperative surveillance and outcome definition

Postoperative lower-limb venous ultrasound was performed according to a prespecified intensified study-surveillance schedule at 12-h intervals until postoperative day 7; monitoring stopped when DVT was first detected. The twice-daily schedule was selected to standardize outcome-ascertainment opportunities across participants and to improve temporal resolution for detecting early or asymptomatic DVT. This study schedule was more intensive than routine clinical surveillance, was used only for outcome ascertainment, and should not be interpreted as a clinical monitoring recommendation.

Statistical analysis

Continuous variables were summarized as mean ± standard deviation and compared between DVT and non-DVT groups using Welch two-sample t-tests. Sex distribution was compared using the Pearson chi-square test. Receiver operating characteristic (ROC) curves were used to assess discrimination. Optimal thresholds were selected by maximizing the Youden J index in this development cohort, with values exactly at the threshold classified as positive. AUC 95% confidence intervals were obtained from 3,000 stratified bootstrap resamples, and sensitivity and specificity confidence intervals were obtained using exact Clopper-Pearson intervals. Apparent combined-marker probabilities were estimated with logistic regression in the full cohort. Exploratory internal validation used stratified 5-fold cross-validation; StandardScaler and L2-penalized logistic regression were fitted within each training fold before generating out-of-fold probabilities for the held-out fold. The 5-variable model was considered overfitting-prone because 37 events yielded 7.4 events per variable. All tests were two-sided, with p < 0.05 denoting statistical significance. The locked revision analysis used Python 3.9.6, pandas 2.3.3, NumPy 2.0.2, SciPy 1.13.1, scikit-learn 1.6.1, statsmodels 0.14.6, Matplotlib 3.9.4, and openpyxl 3.1.5.

Results

Study design and participants

The analysis included 150 patients, of whom 69 were male and 81 were female. The mean age was 55.01 years ± 14.25 years. Postoperative DVT occurred in 37 patients (24.7%), whereas 113 patients (75.3%) did not develop DVT during ultrasound surveillance. Figure 1 summarizes the workflow from preoperative enrollment to postoperative outcome ascertainment and analysis.

Discussion

This prospective observational study found that higher preoperative venous C²/A was associated with postoperative lower-limb DVT after orthopedic surgery. After applying the explicit calculation rule uniformly to the retained C and A fields, POV and CFV C²/A provided the strongest single-marker discrimination. The originally specified SFV C²/A plus D-dimer model was retained without post hoc switching of venous segment and showed good apparent and internally cross-validated discrimination...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
C²/A calculation	Investigator-calculated	Not applicable	C and A were measured with the ultrasound system measurement package; C²/A was calculated as C² divided by A
Color Doppler ultrasound diagnostic system	Philips	CX50
D-DI2, Tina-quant D-Dimer Gen.2	Roche Diagnostics	Material No. 07429410190
D-dimer analyzer	Roche Diagnostics	cobas t 711 coagulation analyzer
IBM SPSS Statistics	IBM Corp.	Version 25.0	RRID:SCR_016479. Used for the original statistical summaries.
L12-3 broadband linear-array ultrasound transducer	Philips	L12-3; 12–3 MHz
Matplotlib	Matplotlib Development Team	Version 3.9.4	RRID:SCR_008624. Used for figure generation in the revision analysis.
NumPy	NumPy Developers	Version 2.0.2	RRID:SCR_008633. Used for numerical operations in the revision analysis.
openpyxl	openpyxl Developers	Version 3.1.5	RRID not available. Used for spreadsheet input and output.
pandas	pandas Development Team	Version 2.3.3	RRID:SCR_018214. Used for data handling and tabulation.
Python Programming Language	Python Software Foundation	Version 3.9.6	RRID:SCR_008394. Runtime for the revision analysis.
scikit-learn	scikit-learn Developers	Version 1.6.1	RRID:SCR_002577. Used for cross-validation and ROC modeling.
SciPy	SciPy Community	Version 1.13.1	RRID:SCR_008058. Used for statistical tests.
statsmodels	statsmodels Developers	Version 0.14.6	RRID:SCR_016074. Used for logistic regression and statistical utilities.