Deep vein thrombosis represents one of the most significant medical challenges in contemporary Healthcare, affecting millions of patients worldwide and contributing substantially to hospital morbidity and mortality. The condition is characterized by the formation of blood clots within the deep venous system, most commonly in the lower extremities, and poses serious complications including pulmonary embolism, chronic venous insufficiency, and post-thrombotic syndrome (Wells et al., 1995). The annual incidence of deep vein thrombosis in the general population ranges from 1-2 per 1000 individuals, with significantly higher rates observed in hospitalized patients due to immobilization, surgical procedures, and underlying comorbidities (Anderson & Spencer, 2003). The clinical presentation of deep vein thrombosis is notoriously unreliable, with classic symptoms of limb swelling, pain, and erythema present in only 23-50% of cases, making accurate diagnosis challenging based solely on clinical assessment (Anand et al., 2002). The absence of pathognomonic clinical findings has necessitated the development of sophisticated diagnostic algorithms incorporating clinical probability scores, laboratory markers, and advanced imaging modalities to achieve accurate and timely diagnosis. The consequences of missed or delayed diagnosis can be catastrophic, with untreated deep vein thrombosis carrying a 25-35% mortality rate from pulmonary embolism, while inappropriate anticoagulation therapy in patients without thrombosis exposes them to significant bleeding risks and healthcare costs. Historically, contrast venography served as the gold standard for deep vein thrombosis diagnosis, providing detailed visualization of the entire venous system and enabling precise identification of thrombus location, extent, and characteristics. However, the invasive nature of venography, associated complications including contrast nephrotoxicity and allergic reactions, technical complexity, and high costs have limited its routine clinical application. The procedure requires specialized expertise, carries risks of venous injury and infection, and may be contraindicated in patients with renal insufficiency or contrast allergies, necessitating the development of non-invasive diagnostic alternatives. Doppler ultrasonography has emerged as the primary diagnostic modality for suspected deep vein thrombosis, revolutionizing the approach to venous thromboembolism diagnosis over the past three decades. The technique combines real-time grayscale imaging with Doppler flow assessment, enabling comprehensive evaluation of venous anatomy, compressibility, and hemodynamics. The evolution from simple continuous-wave Doppler to sophisticated color and duplex systems has significantly enhanced diagnostic accuracy while maintaining the advantages of non-invasive, portable, and cost-effective evaluation (Kearon et al., 1998). The diagnostic principles of Doppler ultrasonography for deep vein thrombosis rely primarily on compression techniques, where the inability to completely compress a venous segment indicates the presence of intraluminal thrombus. Additional criteria include visualization of echogenic material within the vessel lumen, absence or alteration of normal phasic flow patterns, and color flow abnormalities. The combination of these parameters provides comprehensive assessment capabilities, with modern duplex systems achieving sensitivity rates of 89-96% and specificity of 94-99% for proximal deep vein thrombosis in symptomatic patients (Goodacre et al., 2005). Numerous validation studies have established the diagnostic accuracy of Doppler ultrasonography across different patient populations and clinical settings. A systematic review and meta-analysis by Goodacre et al. (2005) analyzing 29 studies comparing ultrasound to venography demonstrated pooled sensitivity of 89% and specificity of 96% for any deep vein thrombosis, with higher accuracy rates for proximal compared to distal thrombosis. The study identified significant heterogeneity between studies, attributable to variations in patient selection, technical protocols, and operator experience, highlighting the importance of standardized approaches and quality assurance measures. The technical advancement in ultrasonographic equipment has contributed significantly to improved diagnostic performance, with contemporary systems incorporating high-frequency transducers, enhanced image processing algorithms, and sophisticated Doppler capabilities. Color Doppler imaging enables rapid identification of flow patterns and vessel patency, while power Doppler techniques provide enhanced sensitivity for detecting low-velocity flow in challenging anatomical locations. The integration of these technologies has expanded the diagnostic capabilities beyond simple compression assessment to include comprehensive hemodynamic evaluation. Point-of-care ultrasonography has gained particular prominence in emergency and critical care settings, where rapid diagnosis of deep vein thrombosis is crucial for appropriate patient management. Multiple studies have demonstrated the feasibility and accuracy of bedside ultrasonographic assessment by emergency physicians and intensivists, with diagnostic performance comparable to formal radiology department examinations. The ability to perform immediate evaluation eliminates delays associated with transportation and scheduling, enabling prompt therapeutic decision-making in critically ill patients (Blaivas et al., 2000). The hospitalized patient population presents unique challenges for deep vein thrombosis diagnosis, with multiple risk factors including prolonged immobilization, surgical procedures, malignancy, central venous catheterization, and underlying medical conditions contributing to increased thrombosis risk. The prevalence of asymptomatic deep vein thrombosis in hospitalized patients may exceed 10-15%, particularly in high-risk populations such as orthopedic surgery patients, making accurate diagnostic methods essential for appropriate screening and management strategies (Kassai et al., 2004). Several factors influence the diagnostic accuracy of Doppler ultrasonography in hospitalized patients, including patient-related variables such as obesity, edema, and inability to cooperate with positioning, as well as technical factors including operator experience, equipment quality, and examination protocols. The presence of bilateral lower extremity edema, chronic venous changes, and previous thrombotic episodes can complicate interpretation and reduce diagnostic confidence. Understanding these limitations is crucial for optimizing diagnostic algorithms and improving patient outcomes. Quality assurance in Doppler ultrasonography requires systematic attention to multiple components including equipment maintenance, standardized protocols, operator training and certification, and continuous quality improvement programs. The development of competency-based training curricula, proficiency assessment tools, and outcome monitoring systems ensures consistent diagnostic performance and identifies opportunities for improvement. Regular correlation with clinical outcomes and follow-up examinations provides valuable feedback for program optimization. The Indian healthcare context presents specific challenges and opportunities for implementing advanced diagnostic imaging strategies for deep vein thrombosis. The diverse patient population, varying healthcare infrastructure, and resource constraints require tailored approaches that balance diagnostic accuracy with cost-effectiveness and accessibility. The increasing availability of ultrasonographic equipment in Indian hospitals provides opportunities for expanding diagnostic capabilities while addressing the growing burden of venous thromboembolism in hospitalized patients. The integration of clinical decision rules, laboratory markers such as D-dimer, and imaging findings represents the contemporary standard for deep vein thrombosis diagnosis. The Wells clinical decision rule, validated in multiple populations, provides structured assessment of pre-test probability and guides appropriate use of diagnostic testing. The combination of low clinical probability and negative D-dimer results can safely exclude deep vein thrombosis in many patients, while intermediate to high probability cases require definitive imaging confirmation. The aim of the study is to evaluate the diagnostic accuracy of Doppler ultrasonography in the assessment of deep vein thrombosis in hospitalized patients by determining its sensitivity, specificity, positive predictive value, and negative predictive value using clinical outcomes and follow-up as reference standards.

Study Design

This study was conducted as a prospective cross sectional diagnostic accuracy study.

Study Site

The study was conducted at Noida International Institute of Medical Sciences, Noida, Uttar Pradesh, a tertiary care teaching hospital serving a large population in western Uttar Pradesh, India.

Study Duration

The study was conducted over a 6-month period from  July 2021 to Dec 2021.

Sampling and Sample Size

The study employed consecutive sampling methodology, enrolling all eligible hospitalized patients with clinical suspicion of deep vein thrombosis during the study period. This approach minimized selection bias and ensured representative sample composition reflecting the actual patient population at risk for venous thromboembolism in the hospital setting. The sample size was calculated based on expected diagnostic accuracy parameters for Doppler ultrasonography, with assumptions derived from published meta analyses indicating sensitivity of 90% and specificity of 95% for deep vein thrombosis detection. Using a precision of ±5% for sensitivity and specificity estimates, with 95% confidence level and expected disease prevalence of 25% in the hospitalized population, a minimum sample size of 200 patients was calculated. Accounting for potential dropouts, incomplete examinations, and lost to follow-up, the target enrollment was set at 220 patients. The sample size calculation also considered the need for adequate statistical power to detect clinically meaningful differences in diagnostic accuracy across patient subgroups and to enable robust confidence interval estimation for performance metrics.

Inclusion and Exclusion Criteria

Inclusion criteria comprised hospitalized patients aged 18 years and above with clinical signs and symptoms suggestive of deep vein thrombosis including unilateral limb swelling, pain, erythema, or warmth, patients with high-risk conditions for venous thromboembolism such as prolonged immobilization, recent surgery, malignancy, or previous thrombotic events, those with intermediate to high clinical probability scores based on validated assessment tools, patients providing informed written consent for study participation and follow-up, and individuals with adequate visualization of deep venous system on initial ultrasonographic examination. Exclusion criteria included patients with known contraindications to anticoagulation therapy that would preclude appropriate treatment if deep vein thrombosis were diagnosed, those with severe peripheral arterial disease limiting accurate venous assessment, patients with extensive chronic venous changes or previous deep vein thrombosis making acute thrombosis assessment difficult, individuals with life-threatening conditions requiring immediate intervention without time for study procedures, those with inability to cooperate with positioning and examination requirements , patients with pregnancy due to altered hemodynamic parameters and different risk profiles, individuals with active bleeding or high bleeding risk conditions, and those unwilling or unable to provide informed consent or comply with follow-up requirements.

Data Collection Tools and Techniques

Data collection was performed using a comprehensive structured case report form designed specifically for this diagnostic accuracy study, incorporating patient demographics, clinical presentation details, risk factor assessment, ultrasonographic findings, and clinical outcome measures. All patients underwent systematic clinical evaluation including detailed history taking with assessment of risk factors, focused physical examination using standardized techniques for detecting signs of deep vein thrombosis, and calculation of clinical probability scores using validated assessment tools. Doppler ultrasonographic examinations were performed using high-resolution ultrasound systems equipped with linear array transducers operating at frequencies of 5-10 MHz, with standardized examination protocols including bilateral lower extremity assessment from inguinal region to ankle level. The ultrasonographic evaluation included grayscale imaging for thrombus visualization, compression testing as the primary diagnostic criterion with inability to compress indicating positive findings, color Doppler assessment for flow evaluation and vessel patency confirmation, and spectral Doppler analysis for hemodynamic pattern assessment including respiratory variation and augmentation responses. All examinations were performed by certified radiologists with minimum 5 years’ experience in vascular ultrasonography, with systematic documentation of findings using standardized terminology and diagnostic criteria. Clinical follow-up included monitoring of therapeutic response to anticoagulation when prescribed, assessment of symptom resolution or progression, and documentation of any complications or adverse events during hospitalization and subsequent outpatient care.

Data Management and Statistical Analysis

Data management was implemented using a secure electronic database system with built-in validation checks and quality control measures to ensure data integrity and completeness. All clinical and imaging data were systematically entered using standardized coding schemes, with double-entry verification for critical variables to minimize transcription errors. Diagnostic accuracy analysis was performed using standard epidemiological methods with calculation of sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy for Doppler ultrasonography using clinical outcomes as the reference standard. Receiver operating characteristic curve analysis was conducted to assess overall diagnostic performance, with calculation of area under the curve and optimal threshold determination. Confidence intervals for all diagnostic accuracy measures were calculated using exact binomial methods or bootstrap techniques as appropriate. Subgroup analyses were planned based on patient characteristics   including age groups, gender, risk factor profiles, anatomical location of suspected thrombosis, and clinical probability categories. Statistical analysis was performed using SPSS version 26.0 software, with significance level set at p<0.05 for all comparisons. Interobserver agreement for ultrasonographic interpretation was assessed using kappa statistics in a subset of cases examined by multiple operators. Missing data were handled using complete case analysis for primary outcomes, with sensitivity analyses performed to assess the impact of missing data on study conclusions.

Ethical Considerations

The study protocol underwent comprehensive review and approval by the Institutional Ethics Committee of Noida International Institute of Medical Sciences, Noida prior to patient recruitment, ensuring compliance with ethical principles and regulatory requirements for medical research involving human subjects. Written informed consent was obtained from all study participants after detailed explanation of study objectives, procedures, potential risks and benefits, alternatives to participation, and confidentiality measures. Patients were explicitly informed that participation was voluntary and that withdrawal from the study at any time would not affect their clinical care or treatment decisions.

Table 1: Demographics and Clinical Characteristics of Study Population (n=208)

Demographics and Clinical Characteristics of Study Population

Table 2: Distribution of Risk Factors for Deep Vein Thrombosis (n=208)

Distribution of Risk Factors for Deep Vein Thrombosis

Table 3: Doppler Ultrasonography Findings and Characteristics (n=208)

Doppler Ultrasonography Findings and Characteristic

Table 4: Reference Standard Outcomes and Clinical Follow-up (n=208)

*Percentages calculated from DVT-positive cases (n=72)

Reference Standard Outcomes and Clinical Follow-up

Table 5: Diagnostic Accuracy of Doppler Ultrasonography for Deep Vein Thrombosis

Table 6: Subgroup Analysis of Diagnostic Accuracy by Patient Characteristics

Subgroup Analysis of Diagnostic Accuracy by Patient Characteristics

Fig: 5

The present study demonstrated excellent diagnostic accuracy of Doppler ultrasonography for deep vein thrombosis detection in hospitalized patients, with overall sensitivity of 94.4% and specificity of 92.6%. These findings are consistent with the comprehensive meta-analysis by Goodacre et al. (2005), which reported pooled sensitivity of 89% and specificity of 96% across 29 studies comparing ultrasound to venography. Our results also align closely with the systematic review by Kearon et al. (1998), who found sensitivity of 97% for proximal deep vein thrombosis and 73% for distal thrombosis, with overall specificity of 94%. The high negative predictive value of 96.4% observed in our study supports the clinical utility of negative ultrasound results in excluding deep vein thrombosis, particularly important for avoiding unnecessary anticoagulation in hospitalized patients with competing bleeding risks. The accuracy of 93.3% achieved in our study compares favorably with contemporary studies evaluating point of- care ultrasonography. Crisp et al. (2010) reported diagnostic accuracy of 95% for emergency physician performed compression ultrasonography, while Blaivas et al. (2000) achieved 95% accuracy in their emergency department cohort. However, our study's performance in the hospitalized population demonstrates the challenges associated with this patient group, where comorbidities, edema, and positioning limitations can affect examination quality and interpretation accuracy. The superior diagnostic performance for proximal compared to distal deep vein thrombosis (sensitivity 97.6% vs 83.3%) observed in our study is consistent with established literature documenting the technical challenges of distal vein assessment. This finding aligns with observations by Rose et al. (1990), who reported significantly higher accuracy for proximal compared to calf vein thrombosis using color duplex imaging. The lower sensitivity for distal thrombosis reflects the inherent limitations of ultrasonographic assessment in smaller caliber vessels, where compression may be incomplete due to surrounding tissue density and acoustic impedance factors.

The distribution of thrombosis locations in our study, with 20.2% proximal and 8.7% distal involvement, is consistent with epidemiological data from hospitalized populations. Van Ramshorst et al. (1991) reported similar anatomical distribution patterns in their duplex scanning study of acute deep vein thrombosis, emphasizing the predominance of proximal disease in symptomatic patients. The clinical significance of this finding is substantial, as proximal thrombosis carries higher risk for pulmonary embolism and requires more aggressive anticoagulation strategies. The demographic profile of our study population, with male predominance (56.7%) and peak incidence in middle-aged patients (42.8% aged 41-60 years), reflects typical characteristics of hospitalized patients at risk for venous thromboembolism. This distribution differs from community-based studies, where female preponderance is often observed due to hormonal and pregnancy-related factors. The high prevalence of immobilization (75.0%) and recent surgery (47.1%) in our cohort underscores the importance of mechanical risk factors in the hospital environment, consistent with established risk assessment models described by Anderson and Spencer (2003). The Wells score distribution in our study population, with 67.8% of patients having moderate to high clinical probability, demonstrates appropriate patient selection for diagnostic imaging. This finding aligns with recommendations from Wells et al. (1997) regarding the clinical utility of structured risk assessment tools in guiding diagnostic testing decisions. The correlation between higher Wells scores and confirmed deep vein validates the clinical decision-making process and supports the integration of clinical probability assessment with imaging findings. The high proportion of examinations with excellent or good visualization (93.3%) in our study reflects both the technical capabilities of modern ultrasound equipment and the expertise of the examining radiologists. However, the 6.7% of examinations limited by patient factors, including obesity, edema, and positioning difficulties, highlights persistent challenges in the hospitalized population. These findings are consistent with observations by Mattos et al. (1992), who identified patient-related factors as significant determinants of examination quality in color-flow duplex scanning. The diagnostic criteria employed in our study, with non-compressible vein segments serving as the primary indicator of thrombosis (29.8% of positive cases), aligns with established ultrasonographic principles described by Lensing et al. (1989). The integration of multiple diagnostic parameters, including direct thrombus visualization, color flow assessment, and spectral Doppler analysis, enhances diagnostic confidence and reduces interpretation errors, particularly in challenging cases with equivocal findings. The subgroup analysis revealed relatively consistent diagnostic performance across different patient demographics, with no statistically significant differences between age groups, gender, or clinical probability categories. This finding suggests that Doppler ultrasonography maintains reliable diagnostic accuracy across diverse patient populations, supporting its widespread clinical application. The slightly lower accuracy observed in obese patients (90.8% vs 94.9%), while not statistically significant, reflects known technical challenges associated with increased tissue attenuation and deeper vessel location in this population. The excellent performance in high-risk patient subgroups, including those with malignancy (32.2% of cohort) and previous thrombotic events (16.3%), demonstrates the reliability of ultrasonographic assessment even in challenging clinical scenarios. These findings support the use of ultrasound as the primary diagnostic modality in high-risk hospitalized patients, where accurate and timely diagnosis is crucial for appropriate therapeutic decision-making. The diagnostic accuracy achieved in our study compares favorably with alternative non-invasive diagnostic approaches reported in contemporary literature. Heijboer et al. (1993) reported sensitivity of 96% and specificity of 97% for real-time compression ultrasonography compared to impedance plethysmography, supporting ultrasound as the preferred non-invasive diagnostic method. The superior performance of ultrasonography compared to clinical assessment alone, as documented by Wells et al. (1995), reinforces the importance of objective diagnostic testing in patients with suspected deep vein thrombosis. The integration of ultrasound findings with clinical probability assessment and D-dimer testing, as advocated by contemporary diagnostic algorithms, provides optimal diagnostic accuracy while minimizing unnecessary imaging and anticoagulation. Our study's findings support this integrated approach, with consistent performance across different clinical probability categories and risk factor profiles. The high negative predictive value (96.4%) observed in our study has significant implications for clinical decision-making, particularly in hospitalized patients where the consequences of inappropriate anticoagulation may be substantial. The ability to confidently exclude deep vein thrombosis based on negative ultrasound findings reduces unnecessary anticoagulation exposure and associated bleeding risks, while enabling focus on alternative diagnoses and appropriate symptomatic management. The identification of alternative diagnoses in 65.4% of patients without deep vein thrombosis, including cellulitis, chronic venous insufficiency, and heart failure, demonstrates the comprehensive diagnostic value of ultrasonographic assessment. This finding supports the cost-effectiveness of ultrasound-based diagnostic algorithms, as documented in health economic analyses comparing imaging strategies with empirical anticoagulation approaches.

This prospective study demonstrated excellent diagnostic accuracy of Doppler ultrasonography for deep vein thrombosis detection in hospitalized patients, achieving sensitivity of 94.4% and specificity of 92.6% with overall accuracy of 93.3%. The superior performance for proximal compared to distal thrombosis (sensitivity 97.6% vs 83.3%) confirms established anatomical limitations while supporting clinical utility for detecting clinically significant proximal disease. The high negative predictive value of 96.4% enables confident exclusion of deep vein thrombosis, reducing unnecessary anticoagulation risks in vulnerable hospitalized patients. Consistent diagnostic performance across patient subgroups, Including different age categories, risk factor profiles, and clinical probability scores, validates the reliability of ultrasonographic assessment in diverse clinical scenarios. The study confirms Doppler ultrasonography as the optimal first-line diagnostic modality for suspected deep vein thrombosis in hospitalized patients, providing accurate, non-invasive, and cost-effective evaluation that facilitates appropriate therapeutic decision-making. The identification of alternative diagnoses in two-thirds of patients without thrombosis demonstrates additional clinical value beyond venous thromboembolism detection, supporting comprehensive diagnostic algorithms integrating clinical assessment with imaging findings for optimal patient care outcomes.

Recommendations

Healthcare institutions should implement standardized Doppler ultrasonography protocols for deep vein thrombosis evaluation in hospitalized patients, incorporating systematic training programs for radiologists and sonographers to maintain consistent diagnostic accuracy. Point-of-care ultrasound training should be expanded to include emergency physicians and intensivists in high-volume centers, enabling rapid bedside assessment and reducing diagnostic delays in critically ill patients. Quality assurance programs should include regular correlation of ultrasound findings with clinical outcomes, inter-observer variability assessment, and equipment maintenance protocols to ensure optimal diagnostic performance.

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