Patient Safety Implications of PSI‑12 Misclassification and the Role of Early Venous Duplex Screening: A Retrospective Cohort Study

Patient Safety Implications of PSI‑12 Misclassification and the Role of Early Venous Duplex Screening: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Patient Safety Implications of PSI‑12 Misclassification and the Role of Early Venous Duplex Screening: A Retrospective Cohort Study Adam S. Surti, Robert T. Matthews, Oana Popescu, Malak Bentaleb, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9087206/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background Venous thromboembolism (VTE) is a major cause of morbidity among surgical patients. Patient Safety Indicator 12 (PSI-12) identifies perioperative VTE events. This study evaluates whether early admission duplex ultrasound identifies VTEs associated with PSI-12 coding and assesses PSI-12 classification accuracy. Methods A single-center retrospective analysis was conducted on surgical patients with a venous duplex ultrasound within 48 hours of admission at a large academic medical center (2013–2024). Two cohorts were analyzed: (1) all surgical patients with early duplex imaging, (2) PSI-12 positive elective surgical patients with early duplex imaging. The primary outcome was the prevalence of pre-existing DVT identified within 48 hours among PSI-12 positive patients. Diagnostic accuracy of early abnormal duplex findings for predicting PSI-12 classification was assessed using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results Among all 10,498 surgical patients, 10.6% had positive duplex findings for DVT. PSI-12 positive patients had double the prevalence compared to PSI-12 negatives (20.9% vs 10.4%, p < 0.001). In PSI-12 positive elective cases, 10.7% of preoperative duplex studies identified a DVT. Misclassification, defined as PSI-12 positive admissions without imaging-confirmed DVT or pulmonary embolism, occurred in 8.7% of elective cases. Overall, 36.7% of PSI-12 positive patients had abnormal early duplex findings. Early duplex demonstrated limited sensitivity but high specificity (sensitivity 36.7%, specificity 81.7%, PPV 3.7%, NPV 98.5%). Conclusions Our findings suggest possible pre-existing disease rather than hospital-acquired VTE in PSI-12 positive patients. Incorporating admission duplex studies could improve PSI-12 classification accuracy, reduce costs, and enhance patient safety. VTE Venous duplex ultrasound PSI-12 Misclassification Patient Safety. Background Perioperative venous thromboembolism (VTE), encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE), is a significant source of morbidity and mortality in hospitalized patients. The incidence of VTE varies based on surgery type and patient-specific risk factors, with particularly high rates observed in patients undergoing major surgery (15–40%), hip and knee arthroplasty (40–60%), and trauma operations (60–80%) 1 . Preoperative duplex screening in asymptomatic high-risk cancer patients has revealed a VTE prevalence of 10% 2 , underscoring the critical importance of accurate perioperative risk assessment and preventive strategies in surgical care. To address these challenges and track hospital quality improvement, the Agency for Healthcare Research and Quality (AHRQ) developed the Patient Safety Indicators (PSIs) in 2003. These metrics are designed to identify potentially avoidable adverse events occurring during hospital stays, promote quality improvement initiatives, rank surgical program performance, and impose financial penalties on hospitals 3 , 4 . PSI-12 is one of these metrics that specifically focuses on perioperative DVT and PE events, which are associated with an estimated additional cost of $ 17,367 per event and a 4.3% increase in excess mortality 5 .PSI-12 events are determined from administrative ICD-10 codes documented by hospital coders, capturing any DVT or PE events during the hospital admission as hospital acquired and thus perioperative. PSI-12 is calculated using administrative discharge data and is structured as a numerator–denominator-based quality measure, in which the denominator defines the population at risk and the numerator captures qualifying postoperative VTE. A hospitalization enters the denominator if the patient is ≥ 18 years old with a qualifying surgical MS-DRG and an operating room procedure as defined by AHRQ specifications 6 . The numerator includes hospitalizations with secondary ICD-10 diagnosis code of proximal DVT, or pulmonary embolism assigned during the hospitalization only when the diagnosis is not marked Present on Admission (POA) 6 . Cases are excluded if VTE is POA, if certain conditions or procedures are present (e.g., ECMO, HIT, early IVC filter), or if key data are missing 6 . Recently, however, the validity and accuracy of these PSIs have been increasingly questioned. Studies suggest limitations in its ability to accurately identify in-hospital complications and reflect true quality of care 7 . A study published in the Journal of Hospital Medicine found that PSI-12 rarely identifies problems with care quality 8 , and another study in the Journal of Vascular Surgery found that PSIs are inferior to metrics like the Vascular Quality Initiative (VQI) and National Surgical Quality Improvement Program (NSQIP) in identifying complications 9 . Additional research has demonstrated these indicators are unable to capture clinically relevant complications 10 , 11 , and that these quality evaluations often rely on inaccurate medical record documentation 12 or miscoded diagnoses and inaccurate ICD-10 codes 13 . Further, unless explicitly documented as Present on Admission (POA), any pre-existing DVT or PEs found during a hospital admission can be classified as a PSI-12 positive admission. Critically, because PSI-12 classifications rely solely on coded diagnoses without requiring clinical validation or imaging interpretation review, pre-existing DVTs may be misclassified as hospital-acquired events. This supports the need for ongoing evaluation and refinement of these indicators. Given these challenges, this study aims to evaluate whether early admission duplex ultrasound in surgical patients can identify pre-existing DVTs among PSI-12 coded surgical patients, and to assess the accuracy of PSI-12 coding by quantifying the rate of misclassification. By examining the relationship between early duplex ultrasound and PSI-12 classification, we seek to assess the effectiveness of current screening protocols and propose improvements in perioperative VTE detection and prevention strategies. Methods Study Design and Population: This study data was generated from a quality improvement database at Cedars-Sinai Medical Center that contained de-identified data. Analysis of deidentified data generated for purposes other than research is determined to meet “Not Regulated” status by the Institutional Review Board (IRB) of Cedars-Sinai Medical Center and ensures compliance with ethical standards in research. We conducted a single-center retrospective analysis of all adults (≥ 18 years) patients who underwent a surgical procedure and had a venous duplex ultrasound study performed within the first 48 hours of their admission at a large quaternary, academic medical center and Level 1 trauma hospital from 2013 to 2024. The 48 hours threshold was selected based on prior studies which treated VTE diagnosed within 48 hours of admission as likely present on admission rather than hospital acquired 14 – 17 . At our institution, routine venous duplex screening within 48 hours of admission is frequently performed for high-risk patients (e.g. oncologic or trauma operations) but is not universally protocolized. In our study, the most common indications reported for duplex ultrasound evaluation were “swelling”, “history of thrombus”, and “surveillance”. Ordering typically reflects surgeon or admitting physician discretion based on patient risk profiles. Demographic and clinical characteristics collected include age, sex, admission diagnoses (diabetes, hypertension, congestive heart failure, etc.) and Elixhauser and Charlson comorbidity indices. Duplex Interpretation: All duplex ultrasound impressions were analyzed and reviewed by two independent reviewers using custom text-mining software that flagged key terms such as “thrombus”, “acute”, “chronic”, "reflux”, etc, enabling identification of patients with positive or abnormal findings. Impressions with findings of acute basilic, cephalic, and external jugular were classified as acute superficial upper thrombus. Impressions with findings of acute brachial, axillary, subclavian, innominate and internal jugular were classified as acute deep upper thrombus. Impressions with findings of acute great saphenous and small saphenous were classified as acute superficial lower thrombus. Impressions with findings of acute soleal, gastrocnemius, peroneal, anterior or posterior tibial, popliteal, femoral, deep femoral or iliac were classified as acute deep lower thrombus. Chronic thrombi and venous reflux were recorded separately as abnormal findings. Abnormal findings were analyzed because they represent potential precursors to acute thrombus formation later during hospitalization, which, if not present within the first 48 hours, could ultimately result in new DVTs classified as PSI-12 positive admissions. The prevalence of venous thrombi was calculated as the proportion of patients with acute deep vein thrombosis PSI-12 Classification: PSI-12 status was determined using administrative ICD-10 diagnosis codes and Present-on-Admission (POA) indicators according to AHRQ specifications. Patients with postoperative proximal DVT or pulmonary embolism not marked POA were classified as PSI-12 positive. Primary outcome: The primary outcome of this study is to determine the prevalence of pre-existing DVT in patients classified as PSI-12 positive, using duplex ultrasound performed within 48 hours of admission. Cohort Definitions: The study cohort was divided into two subsets: All Surgical Patients with Early Venous Duplex Ultrasound The first cohort included all patients who underwent elective or emergent surgery and had received a venous duplex ultrasound performed within the first 48 hours of admission. Venous duplex ultrasound impressions were analyzed to identify positive findings, including acute superficial or deep thrombus. Patients were stratified by PSI-12 status and prevalence of early acute thrombus was compared. Comparisons between these two groups were performed using a two-sample unpaired z-test, with statistical significance defined as p < 0.05. Elective Surgical Patients with PSI-12 Hospital Admissions The second cohort consisted of patients who underwent solely elective surgical procedures and were classified as PSI-12 positive admissions. To further analyze the timing and potential origin of thrombi, this cohort was divided into preoperative and postoperative groups based on the timing of their duplex ultrasound. All preoperative ultrasound scans were performed within 48 hours of admission and prior to surgical incision. Additionally, to evaluate PSI-12 coding accuracy, all patient full charts in this cohort were reviewed individually by two independent reviewers to further assess PSI-12 classification accuracy – as individual chart review would allow for capturing if any DVT or PE was present in their hospital admission after the initial 48 hours. Secondary Outcome: The secondary outcome of this study was to determine misclassification of patients within the elective cohort. Any patient characterized as a PSI-12 positive admission without evidence of a DVT or PE in that admission (duplex ultrasound with positive acute deep vein thrombus or CT chest with findings of pulmonary embolism) was characterized as misclassified. Statistical Analysis: Data were summarized using mean ± standard deviation for continuous variables and proportions for categorical variables. Comparisons between PSI-12 positive and negative groups were performed using an unpaired, two-tailed z-test and Mann-Whitney U test. Statistical significance was defined as p < 0.05. All analyses were conducted using R software 4.4.2 GUI 1.81 Big Sur ARM build. Diagnostic accuracy of early abnormal venous duplex findings for predicting PSI-12 positivity was assessed using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), with PSI-12 status serving as the reference standard. Results A total of 10,498 surgical patients who underwent venous duplex ultrasounds within 48 hours of admission were included in the analysis. Of these, 196 (1.9%) patients were classified as PSI-12 positive, and 10,302 were PSI-12 negative. The mean age across the entire cohort was 65 years, with no significant differences between PSI-12 positive and negative groups. Gender distribution was similar, with 47.5% female in both groups. However, ethnic disparities were noted, with a higher proportion of White patients in the PSI-12 positive group compared to the PSI-12 negative group (63% vs. 56%, p = 0.04), and a lower proportion of Asian patients in the PSI-12 positive group (2.5% vs. 6.2%, p = 0.03). (Table 1 ) Table 1 Demographic Information Demographics PSI Positive N = 196 PSI Negative N = 10302 Total N = 10498 P value Age at admission Average (Year, +/- SD) 63.3, +/-15.3 65.1, +/- 16.5 65.0, +/- 16.0 0.085 BMI > 30 on admission P value Prevalence (n, %) 59, 29.9% 3246, 31.5% 3305, 31.5% 0.631 Gender (Female) Prevalence (n, %) 96, 47.9% 4823, 46.8% 4919, 46.6% 0.757 Ethnicity Asian Prevalence (n, %) 5, 2.6% 641, 6.1% 646, 6.2% 0.041 African American Prevalence (n, %) 27, 13.8% 1769, 16.9 1796, 17.1% 0.250 Hispanic P revalence (n, %) 27, 13.8% 1509, 14.4% 1536, 14.7% 0.810 White Prevalence (n, %) 124, 63.3% 5849, 56.0% 5973, 56.9% 0.041 Other Prevalence (n, %) 13, 6.6% 685, 6.5% 698, 6.6% 0.952 Table 1 Demographic information of all surgical patients with venous duplex performed in the first 48 hours of admission grouped by PSI–12 designation. Ages were compared with Mann-Whitney U test and prevalences were compared with unpaired two sample z test. P value of < 0.05 was used for significance. Table 2 Comorbidity Information Comorbidities PSI Positive N = 196 PSI Negative N = 10302 Total N = 10498 P value Any malignancy Prevalence (n, %) 68, 34.5% 3198, 30.9% 3266, 31.1% 0.280 Cerebrovascular disease Prevalence (n, %) 9, 4.6% 651, 6.3% 660, 6.3% 0.332 Coagulopathy Prevalence (n, %) 77, 39.1% 3285, 31.8% 3362, 32.0% 0.105 Congestive heart failure Prevalence (n, %) 82, 41.6% 5125, 49.6% 5207, 49.6% 0.026 Diabetes Prevalence (n, %) 60, 30.5% 3738, 36.2% 3798, 36.2% 0.220 Fluid and electrolyte disorders Prevalence (n, %) 147, 74,6% 6804, 65.8% 6951, 66.2% 0.010 Hypertension Prevalence (n, %) 160, 81.2% 8088, 78.2% 8248, 78.6% 0.379 Myocardial infarction Prevalence (n, %) 43, 21.8% 2637, 25.5% 2680, 25.5% 0.238 Metastatic Cancer Prevalence (n, %) 42, 21.3% 1670, 16.2% 1712, 16.3% 0.055 Obesity Prevalence (n, %) 60, 30.5% 3155, 30.5% 3215, 30.6% 0.989 Paralysis Prevalence (n, %) 20, 10.2% 654, 6.3% 674, 6.4% 0.027 Solid tumor without metastasis Prevalence (n, %) 65, 33.0% 2793, 27.0% 2858, 27.2% 0.061 Weight loss Prevalence (n, %) 40, 20.3% 1552, 15.0% 1592, 15.2% 0.049 ICD 10 Exclusion in admission diagnosis Prevalence (n, %) 88, 44.9% 1164, 11.3% 1252, 12.2% < 0.001 Charlson Score Average (Score, +/- SD) 4.7, +/- 3.8 4.4, +/- 3.6 4.4, +/- 3.6 0.452 Elixhauser IP Mortality Index Average (Index, +/- SD) 28.4 +/- 18.3 24.1 +/- 17.3 24.2, +/- 17.3 0.009 Table 2: Comorbidity information of all surgical patients with venous duplex performed in the first 48 hours of admission grouped by PSI – 12 designation. Indexes were compared with Mann-Whitney U test and prevalences were compared with unpaired two sample z test. P value of < 0.05 was used for significance Comorbidity indices revealed a sicker population among PSI-12 positive patients, with significantly higher rates of congestive heart failure (49.7% vs. 41.6%, p = 0.03) and electrolyte disorders (74.6% vs. 66%, p = 0.01). Additionally, conditions such as paralysis (10.2% vs. 6.4%, p = 0.03) and metastatic cancer (21.3% vs. 16.2%, p = 0.05) were more prevalent in the PSI-12 positive group. The Elixhauser comorbidity indices also indicated a sicker PSI-12 population (28.4 +/- 18.3 vs 24.1 +/- 17.3, p < 0.001). (Table 2) PSI-12 positive patients had significantly longer operations, with 28.8% lasting over three hours compared to 14.7% of PSI-12 negative patients (p < 0.01). Length of hospital stay was also notably longer in PSI-12 positive patients, with 81.1% staying over seven days compared to 53.2% of PSI-12 negative patients (p 3 hours) Prevalence (n, %) 56, 28.8% 1512, 14.7% 1568, 14.9% 7 days) Prevalence (n, %) 159, 81.1% 3246, 31.5% 3405, 32.4% < 0.001 Table 3: Procedure and Admission time for patients were compared using unpaired two sample z test. P value of < 0.05 was used for significance. Among all surgical patients, 10.6% had positive duplex studies within the first 48 hours of admission. In the PSI-12 positive group, 20.9% had positive duplex findings compared to 10.4% in the PSI-12 negative group (p < 0.01), indicating a significantly higher prevalence of early thrombi in PSI-12 patients. Notably, in this PSI-12 positive group, 140 out of 196 duplex ultrasounds (71.4%) were performed preoperatively. Superficial thrombi were also more frequent in PSI-12 positive patients (9.6% vs. 3.7%, p < 0.01). In total, 36.7% of the PSI-12 positive group had any abnormality when compared to the 18.3% in the PSI-12 negative group (p < 0.001) (Table 4 ). These abnormal findings represent early venous pathology that may progress to acute thrombus formation later in the hospitalization. Table 4 Ultrasound Findings Ultrasound Findings PSI Positive N = 196 PSI Negative N = 10302 Total N = 10498 P value Venous Reflux Prevalence (n, %) 2, 10.2% 268, 2.6% 270, 2.5% 0.166 Chronic Thrombus Prevalence (n, %) 5, 2.6% 399, 3.9% 404, 3.8% 0.341 Acute superficial upper venous thrombus Prevalence (n, %) 14, 7.1% 313, 3.0% 327, 3.1% 0.001 Acute superficial lower venous thrombus P revalence (n, %) 5, 2.6% 70, 0.7% 75, 0.7% 0.002 Acute deep upper venous thrombus Prevalence (n, %) 2, 1.0% 96, 0.9% 98, 0.9% 0.898 Acute deep lower venous thrombus Prevalence (n, %) 39, 19.9% 980, 9.5% 1019, 9.7% < 0.001 Acute superficial venous thrombus Prevalence (n, %) 19, 9.6% 383, 3.7% 402, 3.5% < 0.001 Acute deep venous thrombus Prevalence (n, %) 41, 20.8% 1076, 10.4% 1117, 10.6% < 0.001 Total Abnormal Prevalence (n, %) 72, 36.7% 1881, 18.3% 1953, 18.6% < 0.001 Table 4: Ultrasound findings of all surgical patients with venous duplex performed in the first 48 hours of admission grouped by PSI–12 designations. Prevalences were compared with unpaired two sample z test. P value of < 0.05 was used for significance. In the elective cohort, 56 out of 104 duplex ultrasounds were performed preoperatively, with 10.7% of these duplex studies identifying DVTs. Additionally, 13.5% of patients with abnormal initial duplex findings (e.g., chronic thrombus, superficial clot, or reflux) later developed a DVT or PE, suggesting that chronic or superficial disease may serve as an indicator for subsequent thrombosis. Misclassification remained a critical issue in the elective cohort, with 8.7% of patients classified as PSI-12 positive having no evidence of DVT or PE found on chart review underscoring the limitations of coding-based classification. When any abnormality on early duplex ultrasound (acute, superficial, chronic thrombus, or venous reflux) was evaluated as a predictor of PSI-12 classification, diagnostic accuracy was modest. Sensitivity was 36.7%, and specificity was 81.7%. The positive predictive value (PPV) was 3.7%, while the negative predictive value (NPV) was 98.5%, reflecting the low overall prevalence of PSI-12 events in the cohort (Table 5 ). These findings indicate that while a normal early duplex effectively excludes PSI-12 positivity, abnormal early duplex findings alone are insufficient as a screening tool to predict PSI-12 events. Table 5 Sensitivity, Specificity, PPV, and NPV of PSI-12 Using Early (≤ 48 hours) Duplex Ultrasound Abnormal Duplex Positive PSI-12 Positive PSI-12 Negative Total 72 1,885 1,957 Abnormal Duplex Negative 124 8,417 8,541 Total 196 10,302 10,498 Table 5 : All metrics were calculated using standard 2×2 contingency table Discussion This study highlights key insights into the use of PSI-12 metrics in identifying perioperative venous thromboembolism (VTE) and its associated clinical and financial implications. Our findings demonstrate that a significant portion of PSI-12 classified VTE events were likely present at the time of admission rather than hospital-acquired. Among the larger cohort of all surgical patients, PSI-12 positive patients had a significantly higher prevalence of DVTs on early admission duplex compared to PSI-12 negative patients, with nearly 1 in 5 PSI-12 positive patients having an acute DVT identified within 48 hours of admission, a rate that was double that observed in PSI-12 negative patients. Importantly, more than 70% of duplex ultrasounds in the PSI-12 positive group were performed preoperatively (performed within 48 hours of admission and prior to surgical incision), strongly indicating that many thrombi attributed to postoperative complications may in fact represent pre-existing disease. Additionally, PSI-12 positive patients had higher rates of superficial thrombi (9.6% vs. 3.7%), further suggesting a potential progression from superficial to deep thrombi or pulmonary embolism over time during hospitalization. The presence of early abnormalities supports the hypothesis that a subset of PSI-12 positive categorized events was a progression of pre-existing venous disease rather than de novo hospital-acquired thrombosis. These findings suggest early screening for PSI-12 positive admissions could help distinguish pre-existing disease from in-hospital complications if used in select high-risk patient populations. This would reduce morbidity associated with PSI-12 admissions through early treatment initiation and allow for possible more accurate PSI-12 subcategorization of thrombi that may have been pre-existing. From a diagnostic performance perspective, early duplex abnormalities demonstrated limited sensitivity (36.7%) but good specificity (81.7%) for predicting PSI-12 classification. The positive predictive value was low (3.7%), reflecting the low prevalence of PSI-12 events in the overall surgical population, whereas the negative predictive value was very high (98.5%), indicating that a normal early duplex reliably excludes subsequent PSI-12 classification. This illustrates that while early duplex alone is insufficient as a standalone screening test for PSI-12 classification, it provides clinically meaningful additive information regarding thrombus timing. Early duplex ultrasound should not be used as a universal screening tool to predict PSI-12 events, but rather as a targeted confirmatory tool in high-risk patients where the probability of pre-existing disease is higher. Among the elective cohort, misclassification remains a major concern in PSI-12 reporting, with nearly 1 in 10 of elective PSI-12 positive cases showing no documented evidence of DVT or PE upon chart review at any point during hospitalization. These errors not only inflate PSI-12 rates but also distort hospital performance metrics, leading to misdirected quality improvement efforts and unjustified financial burdens. Given PSI-12 reliance on administrative coding rather than clinical validation, this further highlights a critical opportunity to improve documentation practices and coding accuracy. In addition, we found a preoperative prevalence of true DVTs in 10.7% of elective cases in our hospital, which aligns with prior studies from our institution 2 . These findings underscore the vulnerability of PSI-12 and the importance of integrating more rigorous clinical reviews into PSI-12 reporting processes. The financial implications of PSI-12 misclassification are substantial. According to AHRQ estimates, each PSI-12 event adds $ 17,367 in costs per hospital admission 5 , with even modest rates of misclassification translating into hundreds of thousands of dollars in unnecessary expenditures. In our population, if accurate identification and reclassification of pre-existing thrombi cases had been correctly classified as present on admission (POA), the estimated cost savings would have ranged from $ 714,000 to $ 1,000,000. Beyond financial implications, inflated PSI-12 rates may lead to unwarranted quality investigations and misdirect hospital resources. This highlights the urgent need for hospitals to refine PSI-12 classification criteria and ensure accurate documentation to prevent unnecessary financial penalties. At our institution, we have implemented a collaborative effort between clinical documentation integrity teams and physicians to conduct weekly clinical reviews of PSI-12 events. This initiative has led to a significant reduction in PSI-12 rates by ensuring that thrombi identified on early duplex imaging are appropriately classified as POA when applicable. Expanding similar programs at other institutions could mitigate the impact of PSI-12 misclassification and improve the accuracy of quality metrics used for hospital performance assessment. One important consideration in this study is the concept of “the more you look, the more you find.” As the use of early duplex studies increases, more clinically insignificant DVTs or thrombi of unknown chronicity may be detected. Current guidelines are not well-defined on how to manage these incidental findings, particularly when their clinical significance is unclear. Management should therefore be individualized, considering factors such as patient risk profile, surgical urgency, and thrombus characteristics. Treatment options may include delayed surgery with anticoagulation, placement of an inferior vena cava (IVC) filter, or proceeding with surgery with close postoperative monitoring. Further studies are needed to establish standardized protocols for incidental DVT management in preoperative patients. This study has several limitations. First, its retrospective design may introduce selection bias, particularly in how PSI-12 events were recorded and reviewed. Second, while early duplex studies were performed within 48 hours of admission, this timeframe does not necessarily confirm that thrombi were pre-existing, as some duplexes were obtained postoperatively and may reflect hospital-acquired thrombi. Third, this cohort included only patients who underwent early duplex studies, meaning it likely represents a higher-risk population with a higher prevalence of disease compared to the general surgical population. Finally, as this was conducted at a single institution, the findings may not be generalizable to all hospitals, particularly those with different patient populations, surgical case mixes, or PSI-12 reporting practices. Our findings suggest that early duplex ultrasound screening in select patients can identify potentially pre-existing DVTs, and that PSI-12 misclassification is both common and carries significant implications for hospital quality metrics and finances. Incorporating admission venous duplex studies into PSI-12 evaluations could provide a more accurate assessment of thrombus timing and etiology, thus reducing misclassification rates and improving patient safety. As hospitals continue to refine quality improvement strategies, integrating early duplex screening, enhanced documentation review processes, and standardized classification criteria may help ensure that PSI-12 remains a valid and meaningful measure of surgical quality. Future multi-institutional studies are needed to validate these findings and refine standardized approaches to perioperative VTE surveillance. Conclusions Our findings suggest that a substantial proportion of PSI-12 positive venous thromboembolism events may represent pre-existing disease rather than truly hospital-acquired VTE. One third of PSI-12 positive patients had abnormal early duplex findings, and nearly 9% of cases were misclassified, highlighting important limitations of PSI-12 as a surgical quality metric. Incorporating admission duplex studies in selected high-risk patients may improve the accuracy of PSI-12 classification, reduce unnecessary healthcare costs, and ensure that patient safety metrics more accurately reflect preventable harm. Abbreviations VTE Venous thromboembolism DVT Deep vein thrombosis PE Pulmonary embolism AHRQ Agency for Healthcare Research and Quality PSI Patient Safety Indicator POA Present on Admission VQI Vascular Quality Initiative NSQIP National Surgical Quality Improvement Program Declarations Ethics approval and consent to participate: This study utilized de-identified data obtained from a quality improvement database at Cedars-Sinai Medical Center. Analysis of de-identified data generated for purposes other than research was determined to meet “Not Regulated” status by the Cedars-Sinai Medical Center Institutional Review Board (IRB). Therefore, formal IRB approval and informed consent were not required. Consent for publication: Not Applicable Availability of data and materials: The datasets used are not publicly available as they originate from an institutional quality improvement database but are available from the corresponding author on reasonable request and with appropriate institutional approvals. Competing interests: None Funding: None Authors' contributions: ASS contributed to conceptualization, methodology, software development, formal analysis, visualization, and writing of the original draft. RTM contributed to methodology, software development, formal analysis, and writing of the original draft. OP contributed to investigation, resources, and data curation. MB contributed to writing, review, and editing of the manuscript. RFA contributed to conceptualization, methodology, visualization, supervision, and project administration. All authors read and approved the final manuscript. Acknowledgements: None References Valsami S, Asmis LM. A Brief Review of 50 Years of Perioperative Thrombosis and Hemostasis Management. Semin Hematol. 2013;50(2):79–87. 10.1053/j.seminhematol.2013.04.001 . Gainsbury ML, Erdrich J, Taubman D, et al. Prevalence and Predictors of Preoperative Venous Thromboembolism in Asymptomatic Patients Undergoing Major Oncologic Surgery. Ann Surg Oncol. 2018;25(6):1640–5. 10.1245/s10434-018-6461-2 . AHRQ QI: Patient Safety Indicators Overview. Accessed December 23. 2025. https://qualityindicators.ahrq.gov/measures/psi_resources? Chen Q, Rosen AK, Borzecki A, Shwartz M. Using Harm-Based Weights for the AHRQ Patient Safety for Selected Indicators Composite (PSI ‐90): Does It Affect Assessment of Hospital Performance and Financial Penalties in Veterans Health Administration Hospitals? Health Serv Res. 2016;51(6):2140–57. 10.1111/1475-6773.12596 . Estimating the Additional Hospital Inpatient Cost and Mortality Associated With Selected Hospital-Acquired Conditions. Accessed December 23. 2025. https://www.ahrq.gov/hai/pfp/haccost2017.html PSI_12_Perioperative_Pulmonary_Embolism_or_Deep_Vein_Thrombosis_Rate.pdf. Accessed December 23. 2025. https://qualityindicators.ahrq.gov/Downloads/Modules/PSI/V2024/TechSpecs/PSI_12_Perioperative_Pulmonary_Embolism_or_Deep_Vein_Thrombosis_Rate.pdf Havranek MM, Rüter F, Bilger S, et al. Validity of 16 AHRQ Patient Safety Indicators to identify in-hospital complications: a medical record review across nine Swiss hospitals. Int J Qual Health Care. 2023;35(4):0–0. 10.1093/intqhc/mzad092 . Held N, Jung B, Sommervold L, Singh S, Kreuziger LB. Patient Safety Indicator-12 Rarely Identifies Problems with Quality of Care in Perioperative Venous Thromboembolism. J Hosp Med. 2020;15(2):75–80. 10.12788/jhm.3298 . Sorber R, Giuliano KA, Hicks CW, Black JH. Patient Safety Indicators are an insufficient performance metric to track and grade outcomes of open aortic repair. J Vasc Surg. 2021;73(1):240–e2495. 10.1016/j.jvs.2020.04.517 . Cima RR, Lackore KA, Nehring SA, et al. How best to measure surgical quality? comparison of the Agency for Healthcare Research and Quality Patient Safety Indicators (AHRQ-PSI) and the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) postoperative adverse events at a single institution. Surgery. 2011;150(5):943–9. 10.1016/j.surg.2011.06.020 . Kubasiak JC, Francescatti AB, Behal R, Myers JA. Patient Safety Indicators for Judging Hospital Performance: Still Not Ready for Prime Time. Am J Med Qual. 2017;32(2):129–33. 10.1177/1062860615618782 . Elkbuli A, Godelman S, Miller A, et al. Improved clinical documentation leads to superior reportable outcomes: An accurate representation of patient’s clinical status. Int J Surg. 2018;53:288–91. 10.1016/j.ijsu.2018.03.081 . Rajahraman V, Fassihi SC, Patel V, Pope CA, Rozell JC, Schwarzkopf R. Accuracy of ICD-10 Coding for Femoral Head Bearing Surfaces in Hip Arthroplasty. J Arthroplast. 2023;38(5):794–7. 10.1016/j.arth.2022.12.002 . Häfliger E, Kopp B, Darbellay Farhoumand P, et al. Risk Assessment Models for Venous Thromboembolism in Medical Inpatients. JAMA Netw Open. 2024;7(5):e249980. 10.1001/jamanetworkopen.2024.9980 . Parks AL, Auerbach AD, Schnipper JL et al. Venous thromboembolism (VTE) prevention and diagnosis in COVID-19: Practice patterns and outcomes at 33 hospitals. Cugno M, ed. PLoS ONE . 2022;17(5):e0266944. 10.1371/journal.pone.0266944 Neeman E, Liu V, Mishra P, et al. Trends and Risk Factors for Venous Thromboembolism Among Hospitalized Medical Patients. JAMA Netw Open. 2022;5(11):e2240373. 10.1001/jamanetworkopen.2022.40373 . Shapiro S, Majert J, Obeidalla A, et al. Same-day emergency care: a retrospective observational study of the incidence and predictors of venous thromboembolism following hospital-based acute ambulatory medical care. J Thromb Haemost. 2025;23(1):97–107. 10.1016/j.jtha.2024.09.017 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 07 May, 2026 Reviews received at journal 07 May, 2026 Reviews received at journal 06 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviews received at journal 28 Apr, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers invited by journal 28 Apr, 2026 Editor assigned by journal 14 Mar, 2026 Submission checks completed at journal 13 Mar, 2026 First submitted to journal 10 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9087206","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":635726265,"identity":"6dcb8338-3859-4433-9586-cbb2802ee2a7","order_by":0,"name":"Adam S. Surti","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIie3RsQrCMBCA4QuBdLnQuRR8hoAgiIOvUnHoIujkKJ0yib6KIBTHQgYXB8eMOujkYBdB6OAVFJxi3QTzQzvl6yUpgM/3gwlI6F3Rw3kBLGtAwpowDYBcJM1IlNWEViKgakbUdnhascyM+wGW5X0zgzDe7t1kd+5YqEx3zuU6ljsD0WI0cRObEBFGIZc5Z7qgj2DiJH2b3p4Ez+yuZ5+JsqPXFBQgNScSFB/OcpnagU4VGtGOpTYYzdEp6MbS3F6rngqW5ljSxlohBge3qXvfO42gH/RtTab4fD7fP/UA9bZFqP7toxcAAAAASUVORK5CYII=","orcid":"","institution":"Cedars-Sinai Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Adam","middleName":"S.","lastName":"Surti","suffix":""},{"id":635726266,"identity":"3539203d-7432-4c7b-846e-daa6d1cc3d94","order_by":1,"name":"Robert T. Matthews","email":"","orcid":"","institution":"Cedars-Sinai Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"T.","lastName":"Matthews","suffix":""},{"id":635726267,"identity":"5e24e1c2-5291-4f25-829c-8499d537d61f","order_by":2,"name":"Oana Popescu","email":"","orcid":"","institution":"Cedars-Sinai Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Oana","middleName":"","lastName":"Popescu","suffix":""},{"id":635726268,"identity":"4d35c67b-2b38-442a-8cd3-07528de5ce49","order_by":3,"name":"Malak Bentaleb","email":"","orcid":"","institution":"Khalifa University","correspondingAuthor":false,"prefix":"","firstName":"Malak","middleName":"","lastName":"Bentaleb","suffix":""},{"id":635726269,"identity":"82c5c673-6328-4afc-9a41-06db51c35307","order_by":4,"name":"Rodrigo F. Alban","email":"","orcid":"","institution":"Cedars-Sinai Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Rodrigo","middleName":"F.","lastName":"Alban","suffix":""}],"badges":[],"createdAt":"2026-03-10 19:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9087206/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9087206/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108805787,"identity":"00fa3a0d-55d6-46fe-a203-7fb832417537","added_by":"auto","created_at":"2026-05-08 15:26:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":419070,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9087206/v1/7a5a576c-2bd1-48da-bf29-c74c8c091ee6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Patient Safety Implications of PSI‑12 Misclassification and the Role of Early Venous Duplex Screening: A Retrospective Cohort Study","fulltext":[{"header":"Background","content":"\u003cp\u003ePerioperative venous thromboembolism (VTE), encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE), is a significant source of morbidity and mortality in hospitalized patients. The incidence of VTE varies based on surgery type and patient-specific risk factors, with particularly high rates observed in patients undergoing major surgery (15\u0026ndash;40%), hip and knee arthroplasty (40\u0026ndash;60%), and trauma operations (60\u0026ndash;80%)\u003csup\u003e1\u003c/sup\u003e. Preoperative duplex screening in asymptomatic high-risk cancer patients has revealed a VTE prevalence of 10% \u003csup\u003e2\u003c/sup\u003e, underscoring the critical importance of accurate perioperative risk assessment and preventive strategies in surgical care.\u003c/p\u003e \u003cp\u003eTo address these challenges and track hospital quality improvement, the Agency for Healthcare Research and Quality (AHRQ) developed the Patient Safety Indicators (PSIs) in 2003. These metrics are designed to identify potentially avoidable adverse events occurring during hospital stays, promote quality improvement initiatives, rank surgical program performance, and impose financial penalties on hospitals\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. PSI-12 is one of these metrics that specifically focuses on perioperative DVT and PE events, which are associated with an estimated additional cost of \u003cspan\u003e$\u003c/span\u003e17,367 per event and a 4.3% increase in excess mortality\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.PSI-12 events are determined from administrative ICD-10 codes documented by hospital coders, capturing any DVT or PE events during the hospital admission as hospital acquired and thus perioperative. PSI-12 is calculated using administrative discharge data and is structured as a numerator\u0026ndash;denominator-based quality measure, in which the denominator defines the population at risk and the numerator captures qualifying postoperative VTE. A hospitalization enters the denominator if the patient is \u0026ge;\u0026thinsp;18 years old with a qualifying surgical MS-DRG and an operating room procedure as defined by AHRQ specifications \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The numerator includes hospitalizations with secondary ICD-10 diagnosis code of proximal DVT, or pulmonary embolism assigned during the hospitalization only when the diagnosis is not marked Present on Admission (POA)\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Cases are excluded if VTE is POA, if certain conditions or procedures are present (e.g., ECMO, HIT, early IVC filter), or if key data are missing\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRecently, however, the validity and accuracy of these PSIs have been increasingly questioned. Studies suggest limitations in its ability to accurately identify in-hospital complications and reflect true quality of care\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. A study published in the \u003cem\u003eJournal of Hospital Medicine\u003c/em\u003e found that PSI-12 rarely identifies problems with care quality\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, and another study in the \u003cem\u003eJournal of Vascular Surgery\u003c/em\u003e found that PSIs are inferior to metrics like the Vascular Quality Initiative (VQI) and National Surgical Quality Improvement Program (NSQIP) in identifying complications\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Additional research has demonstrated these indicators are unable to capture clinically relevant complications\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, and that these quality evaluations often rely on inaccurate medical record documentation\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e or miscoded diagnoses and inaccurate ICD-10 codes \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Further, unless explicitly documented as Present on Admission (POA), any pre-existing DVT or PEs found during a hospital admission can be classified as a PSI-12 positive admission. Critically, because PSI-12 classifications rely solely on coded diagnoses without requiring clinical validation or imaging interpretation review, pre-existing DVTs may be misclassified as hospital-acquired events. This supports the need for ongoing evaluation and refinement of these indicators.\u003c/p\u003e \u003cp\u003eGiven these challenges, this study aims to evaluate whether early admission duplex ultrasound in surgical patients can identify pre-existing DVTs among PSI-12 coded surgical patients, and to assess the accuracy of PSI-12 coding by quantifying the rate of misclassification. By examining the relationship between early duplex ultrasound and PSI-12 classification, we seek to assess the effectiveness of current screening protocols and propose improvements in perioperative VTE detection and prevention strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy Design and Population:\u003c/p\u003e \u003cp\u003eThis study data was generated from a quality improvement database at Cedars-Sinai Medical Center that contained de-identified data. Analysis of deidentified data generated for purposes other than research is determined to meet \u0026ldquo;Not Regulated\u0026rdquo; status by the Institutional Review Board (IRB) of Cedars-Sinai Medical Center and ensures compliance with ethical standards in research.\u003c/p\u003e \u003cp\u003eWe conducted a single-center retrospective analysis of all adults (\u0026ge;\u0026thinsp;18 years) patients who underwent a surgical procedure and had a venous duplex ultrasound study performed within the first 48 hours of their admission at a large quaternary, academic medical center and Level 1 trauma hospital from 2013 to 2024. The 48 hours threshold was selected based on prior studies which treated VTE diagnosed within 48 hours of admission as likely present on admission rather than hospital acquired \u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAt our institution, routine venous duplex screening within 48 hours of admission is frequently performed for high-risk patients (e.g. oncologic or trauma operations) but is not universally protocolized. In our study, the most common indications reported for duplex ultrasound evaluation were \u0026ldquo;swelling\u0026rdquo;, \u0026ldquo;history of thrombus\u0026rdquo;, and \u0026ldquo;surveillance\u0026rdquo;. Ordering typically reflects surgeon or admitting physician discretion based on patient risk profiles.\u003c/p\u003e \u003cp\u003eDemographic and clinical characteristics collected include age, sex, admission diagnoses (diabetes, hypertension, congestive heart failure, etc.) and Elixhauser and Charlson comorbidity indices.\u003c/p\u003e \u003cp\u003eDuplex Interpretation:\u003c/p\u003e \u003cp\u003e All duplex ultrasound impressions were analyzed and reviewed by two independent reviewers using custom text-mining software that flagged key terms such as \u0026ldquo;thrombus\u0026rdquo;, \u0026ldquo;acute\u0026rdquo;, \u0026ldquo;chronic\u0026rdquo;, \"reflux\u0026rdquo;, etc, enabling identification of patients with positive or abnormal findings. Impressions with findings of acute basilic, cephalic, and external jugular were classified as acute superficial upper thrombus. Impressions with findings of acute brachial, axillary, subclavian, innominate and internal jugular were classified as acute deep upper thrombus. Impressions with findings of acute great saphenous and small saphenous were classified as acute superficial lower thrombus. Impressions with findings of acute soleal, gastrocnemius, peroneal, anterior or posterior tibial, popliteal, femoral, deep femoral or iliac were classified as acute deep lower thrombus. Chronic thrombi and venous reflux were recorded separately as abnormal findings. Abnormal findings were analyzed because they represent potential precursors to acute thrombus formation later during hospitalization, which, if not present within the first 48 hours, could ultimately result in new DVTs classified as PSI-12 positive admissions. The prevalence of venous thrombi was calculated as the proportion of patients with acute deep vein thrombosis\u003c/p\u003e \u003cp\u003ePSI-12 Classification:\u003c/p\u003e \u003cp\u003ePSI-12 status was determined using administrative ICD-10 diagnosis codes and Present-on-Admission (POA) indicators according to AHRQ specifications. Patients with postoperative proximal DVT or pulmonary embolism not marked POA were classified as PSI-12 positive.\u003c/p\u003e \u003cp\u003ePrimary outcome:\u003c/p\u003e \u003cp\u003eThe primary outcome of this study is to determine the prevalence of pre-existing DVT in patients classified as PSI-12 positive, using duplex ultrasound performed within 48 hours of admission.\u003c/p\u003e \u003cp\u003eCohort Definitions:\u003c/p\u003e \u003cp\u003eThe study cohort was divided into two subsets:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAll Surgical Patients with Early Venous Duplex Ultrasound\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe first cohort included all patients who underwent elective or emergent surgery and had received a venous duplex ultrasound performed within the first 48 hours of admission. Venous duplex ultrasound impressions were analyzed to identify positive findings, including acute superficial or deep thrombus. Patients were stratified by PSI-12 status and prevalence of early acute thrombus was compared. Comparisons between these two groups were performed using a two-sample unpaired z-test, with statistical significance defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eElective Surgical Patients with PSI-12 Hospital Admissions\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe second cohort consisted of patients who underwent solely elective surgical procedures and were classified as PSI-12 positive admissions. To further analyze the timing and potential origin of thrombi, this cohort was divided into preoperative and postoperative groups based on the timing of their duplex ultrasound. All preoperative ultrasound scans were performed within 48 hours of admission and prior to surgical incision. Additionally, to evaluate PSI-12 coding accuracy, all patient full charts in this cohort were reviewed individually by two independent reviewers to further assess PSI-12 classification accuracy \u0026ndash; as individual chart review would allow for capturing if any DVT or PE was present in their hospital admission after the initial 48 hours.\u003c/p\u003e \u003cp\u003eSecondary Outcome:\u003c/p\u003e \u003cp\u003eThe secondary outcome of this study was to determine misclassification of patients within the elective cohort. Any patient characterized as a PSI-12 positive admission without evidence of a DVT or PE in that admission (duplex ultrasound with positive acute deep vein thrombus or CT chest with findings of pulmonary embolism) was characterized as misclassified.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis:\u003c/h2\u003e \u003cp\u003eData were summarized using mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation for continuous variables and proportions for categorical variables. Comparisons between PSI-12 positive and negative groups were performed using an unpaired, two-tailed z-test and Mann-Whitney U test. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All analyses were conducted using R software 4.4.2 GUI 1.81 Big Sur ARM build. Diagnostic accuracy of early abnormal venous duplex findings for predicting PSI-12 positivity was assessed using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), with PSI-12 status serving as the reference standard.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 10,498 surgical patients who underwent venous duplex ultrasounds within 48 hours of admission were included in the analysis. Of these, 196 (1.9%) patients were classified as PSI-12 positive, and 10,302 were PSI-12 negative.\u003c/p\u003e\n\u003cp\u003eThe mean age across the entire cohort was 65 years, with no significant differences between PSI-12 positive and negative groups. Gender distribution was similar, with 47.5% female in both groups. However, ethnic disparities were noted, with a higher proportion of White patients in the PSI-12 positive group compared to the PSI-12 negative group (63% vs. 56%, p\u0026thinsp;=\u0026thinsp;0.04), and a lower proportion of Asian patients in the PSI-12 positive group (2.5% vs. 6.2%, p\u0026thinsp;=\u0026thinsp;0.03). (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003cbr\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic Information\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDemographics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePSI Positive\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;196\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePSI Negative\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10302\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10498\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge at admission\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage (Year, +/- SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.3, +/-15.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.1, +/- 16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.0, +/- 16.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u0026thinsp;\u0026gt;\u0026thinsp;30 on admission\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59, 29.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3246, 31.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3305, 31.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender (Female)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96, 47.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4823, 46.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4919, 46.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5, 2.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e641, 6.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e646, 6.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfrican American\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27, 13.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1769, 16.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1796, 17.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHispanic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003erevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27, 13.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1509, 14.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1536, 14.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhite\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124, 63.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5849, 56.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5973, 56.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13, 6.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e685, 6.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e698, 6.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.952\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003eTable 1 Demographic information of all surgical patients with venous duplex performed in the first 48 hours of admission grouped by PSI\u0026ndash;12 designation. Ages were compared with Mann-Whitney U test and prevalences were compared with unpaired two sample z test. P value of \u0026lt;\u0026thinsp;0.05 was used for significance.\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable\u0026nbsp;2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComorbidity Information\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePSI Positive\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;196\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePSI Negative\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10302\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10498\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAny malignancy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68, 34.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3198, 30.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3266, 31.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCerebrovascular disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9, 4.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e651, 6.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e660, 6.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoagulopathy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77, 39.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3285, 31.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3362, 32.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCongestive heart failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82, 41.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5125, 49.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5207, 49.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60, 30.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3738, 36.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3798, 36.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFluid and electrolyte disorders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e147, 74,6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e6804, 65.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e6951, 66.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160, 81.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e8088, 78.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e8248, 78.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.379\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMyocardial infarction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43, 21.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2637, 25.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2680, 25.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.238\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetastatic Cancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42, 21.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1670, 16.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1712, 16.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eObesity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60, 30.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3155, 30.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3215, 30.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.989\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eParalysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20, 10.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e654, 6.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e674, 6.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSolid tumor without metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65, 33.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2793, 27.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2858, 27.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight loss\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40, 20.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1552, 15.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1592, 15.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eICD 10 Exclusion in admission diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88, 44.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1164, 11.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1252, 12.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharlson Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage (Score, +/- SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7, +/- 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4.4, +/- 3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4.4, +/- 3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eElixhauser IP Mortality Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage (Index, +/- SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.4 +/- 18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e24.1 +/- 17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e24.2, +/- 17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Comorbidity information of all surgical patients with venous duplex performed in the first 48 hours of admission grouped by PSI \u0026ndash; 12 designation. Indexes were compared with Mann-Whitney U test and prevalences were compared with unpaired two sample z test. P value of \u0026lt; 0.05 was used for significance\u003c/p\u003e\n\u003cp\u003eComorbidity indices revealed a sicker population among PSI-12 positive patients, with significantly higher rates of congestive heart failure (49.7% vs. 41.6%, p\u0026thinsp;=\u0026thinsp;0.03) and electrolyte disorders (74.6% vs. 66%, p\u0026thinsp;=\u0026thinsp;0.01). Additionally, conditions such as paralysis (10.2% vs. 6.4%, p\u0026thinsp;=\u0026thinsp;0.03) and metastatic cancer (21.3% vs. 16.2%, p\u0026thinsp;=\u0026thinsp;0.05) were more prevalent in the PSI-12 positive group. The Elixhauser comorbidity indices also indicated a sicker PSI-12 population (28.4 +/- 18.3 vs 24.1 +/- 17.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). (Table 2)\u003c/p\u003e\n\u003cp\u003ePSI-12 positive patients had significantly longer operations, with 28.8% lasting over three hours compared to 14.7% of PSI-12 negative patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Length of hospital stay was also notably longer in PSI-12 positive patients, with 81.1% staying over seven days compared to 53.2% of PSI-12 negative patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eProcedure and Admission Time\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProcedure and Admission Time\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePSI Positive\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;196\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePSI Negative\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10302\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10498\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of Operation (\u0026gt;\u0026thinsp;3 hours)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e56, 28.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1512, 14.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1568, 14.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of Admission (\u0026gt;\u0026thinsp;7 days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e159, 81.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3246, 31.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3405, 32.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u003c/strong\u003e Procedure and Admission time for patients were compared using unpaired two sample z test. P value of \u0026lt; 0.05 was used for significance.\u003c/p\u003e\n\u003cp\u003eAmong all surgical patients, 10.6% had positive duplex studies within the first 48 hours of admission. In the PSI-12 positive group, 20.9% had positive duplex findings compared to 10.4% in the PSI-12 negative group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating a significantly higher prevalence of early thrombi in PSI-12 patients. Notably, in this PSI-12 positive group, 140 out of 196 duplex ultrasounds (71.4%) were performed preoperatively. Superficial thrombi were also more frequent in PSI-12 positive patients (9.6% vs. 3.7%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In total, 36.7% of the PSI-12 positive group had any abnormality when compared to the 18.3% in the PSI-12 negative group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). These abnormal findings represent early venous pathology that may progress to acute thrombus formation later in the hospitalization.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUltrasound Findings\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUltrasound Findings\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePSI Positive\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;196\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePSI Negative\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10302\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10498\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVenous Reflux\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2, 10.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e268, 2.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e270, 2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic Thrombus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5, 2.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e399, 3.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e404, 3.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcute superficial upper venous thrombus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e14, 7.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e313, 3.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e327, 3.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcute superficial lower venous thrombus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003erevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5, 2.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e70, 0.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e75, 0.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcute deep upper venous thrombus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2, 1.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e96, 0.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e98, 0.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcute deep lower venous thrombus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e39, 19.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e980, 9.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1019, 9.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcute superficial venous thrombus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e19, 9.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e383, 3.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e402, 3.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcute deep venous thrombus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e41, 20.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1076, 10.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1117, 10.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Abnormal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e72, 36.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1881, 18.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1953, 18.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u003c/strong\u003e Ultrasound findings of all surgical patients with venous duplex performed in the first 48 hours of admission grouped by PSI\u0026ndash;12 designations. Prevalences were compared with unpaired two sample z test. P value of \u0026lt; 0.05 was used for significance.\u003c/p\u003e\n\u003cp\u003eIn the elective cohort, 56 out of 104 duplex ultrasounds were performed preoperatively, with 10.7% of these duplex studies identifying DVTs. Additionally, 13.5% of patients with abnormal initial duplex findings (e.g., chronic thrombus, superficial clot, or reflux) later developed a DVT or PE, suggesting that chronic or superficial disease may serve as an indicator for subsequent thrombosis. Misclassification remained a critical issue in the elective cohort, with 8.7% of patients classified as PSI-12 positive having no evidence of DVT or PE found on chart review underscoring the limitations of coding-based classification.\u003c/p\u003e\n\u003cp\u003eWhen any abnormality on early duplex ultrasound (acute, superficial, chronic thrombus, or venous reflux) was evaluated as a predictor of PSI-12 classification, diagnostic accuracy was modest. Sensitivity was 36.7%, and specificity was 81.7%. The positive predictive value (PPV) was 3.7%, while the negative predictive value (NPV) was 98.5%, reflecting the low overall prevalence of PSI-12 events in the cohort (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). These findings indicate that while a normal early duplex effectively excludes PSI-12 positivity, abnormal early duplex findings alone are insufficient as a screening tool to predict PSI-12 events.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSensitivity, Specificity, PPV, and NPV of PSI-12 Using Early (\u0026le;\u0026thinsp;48 hours) Duplex Ultrasound\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbnormal Duplex Positive\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePSI-12 Positive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePSI-12 Negative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1,885\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1,957\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbnormal Duplex Negative\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e8,417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e8,541\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e10,302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e10,498\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e: All metrics were calculated using standard 2\u0026times;2 contingency table\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study highlights key insights into the use of PSI-12 metrics in identifying perioperative venous thromboembolism (VTE) and its associated clinical and financial implications. Our findings demonstrate that a significant portion of PSI-12 classified VTE events were likely present at the time of admission rather than hospital-acquired. Among the larger cohort of all surgical patients, PSI-12 positive patients had a significantly higher prevalence of DVTs on early admission duplex compared to PSI-12 negative patients, with nearly 1 in 5 PSI-12 positive patients having an acute DVT identified within 48 hours of admission, a rate that was double that observed in PSI-12 negative patients. Importantly, more than 70% of duplex ultrasounds in the PSI-12 positive group were performed preoperatively (performed within 48 hours of admission and prior to surgical incision), strongly indicating that many thrombi attributed to postoperative complications may in fact represent pre-existing disease.\u003c/p\u003e \u003cp\u003eAdditionally, PSI-12 positive patients had higher rates of superficial thrombi (9.6% vs. 3.7%), further suggesting a potential progression from superficial to deep thrombi or pulmonary embolism over time during hospitalization. The presence of early abnormalities supports the hypothesis that a subset of PSI-12 positive categorized events was a progression of pre-existing venous disease rather than de novo hospital-acquired thrombosis.\u003c/p\u003e \u003cp\u003eThese findings suggest early screening for PSI-12 positive admissions could help distinguish pre-existing disease from in-hospital complications if used in select high-risk patient populations. This would reduce morbidity associated with PSI-12 admissions through early treatment initiation and allow for possible more accurate PSI-12 subcategorization of thrombi that may have been pre-existing.\u003c/p\u003e \u003cp\u003eFrom a diagnostic performance perspective, early duplex abnormalities demonstrated limited sensitivity (36.7%) but good specificity (81.7%) for predicting PSI-12 classification. The positive predictive value was low (3.7%), reflecting the low prevalence of PSI-12 events in the overall surgical population, whereas the negative predictive value was very high (98.5%), indicating that a normal early duplex reliably excludes subsequent PSI-12 classification. This illustrates that while early duplex alone is insufficient as a standalone screening test for PSI-12 classification, it provides clinically meaningful additive information regarding thrombus timing. Early duplex ultrasound should not be used as a universal screening tool to predict PSI-12 events, but rather as a targeted confirmatory tool in high-risk patients where the probability of pre-existing disease is higher.\u003c/p\u003e \u003cp\u003eAmong the elective cohort, misclassification remains a major concern in PSI-12 reporting, with nearly 1 in 10 of elective PSI-12 positive cases showing no documented evidence of DVT or PE upon chart review at any point during hospitalization. These errors not only inflate PSI-12 rates but also distort hospital performance metrics, leading to misdirected quality improvement efforts and unjustified financial burdens. Given PSI-12 reliance on administrative coding rather than clinical validation, this further highlights a critical opportunity to improve documentation practices and coding accuracy. In addition, we found a preoperative prevalence of true DVTs in 10.7% of elective cases in our hospital, which aligns with prior studies from our institution\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. These findings underscore the vulnerability of PSI-12 and the importance of integrating more rigorous clinical reviews into PSI-12 reporting processes.\u003c/p\u003e \u003cp\u003eThe financial implications of PSI-12 misclassification are substantial. According to AHRQ estimates, each PSI-12 event adds \u003cspan\u003e$\u003c/span\u003e17,367 in costs per hospital admission\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, with even modest rates of misclassification translating into hundreds of thousands of dollars in unnecessary expenditures. In our population, if accurate identification and reclassification of pre-existing thrombi cases had been correctly classified as present on admission (POA), the estimated cost savings would have ranged from \u003cspan\u003e$\u003c/span\u003e714,000 to \u003cspan\u003e$\u003c/span\u003e1,000,000. Beyond financial implications, inflated PSI-12 rates may lead to unwarranted quality investigations and misdirect hospital resources. This highlights the urgent need for hospitals to refine PSI-12 classification criteria and ensure accurate documentation to prevent unnecessary financial penalties.\u003c/p\u003e \u003cp\u003eAt our institution, we have implemented a collaborative effort between clinical documentation integrity teams and physicians to conduct weekly clinical reviews of PSI-12 events. This initiative has led to a significant reduction in PSI-12 rates by ensuring that thrombi identified on early duplex imaging are appropriately classified as POA when applicable. Expanding similar programs at other institutions could mitigate the impact of PSI-12 misclassification and improve the accuracy of quality metrics used for hospital performance assessment.\u003c/p\u003e \u003cp\u003eOne important consideration in this study is the concept of \u0026ldquo;the more you look, the more you find.\u0026rdquo; As the use of early duplex studies increases, more clinically insignificant DVTs or thrombi of unknown chronicity may be detected. Current guidelines are not well-defined on how to manage these incidental findings, particularly when their clinical significance is unclear. Management should therefore be individualized, considering factors such as patient risk profile, surgical urgency, and thrombus characteristics. Treatment options may include delayed surgery with anticoagulation, placement of an inferior vena cava (IVC) filter, or proceeding with surgery with close postoperative monitoring. Further studies are needed to establish standardized protocols for incidental DVT management in preoperative patients.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, its retrospective design may introduce selection bias, particularly in how PSI-12 events were recorded and reviewed. Second, while early duplex studies were performed within 48 hours of admission, this timeframe does not necessarily confirm that thrombi were pre-existing, as some duplexes were obtained postoperatively and may reflect hospital-acquired thrombi. Third, this cohort included only patients who underwent early duplex studies, meaning it likely represents a higher-risk population with a higher prevalence of disease compared to the general surgical population. Finally, as this was conducted at a single institution, the findings may not be generalizable to all hospitals, particularly those with different patient populations, surgical case mixes, or PSI-12 reporting practices.\u003c/p\u003e \u003cp\u003eOur findings suggest that early duplex ultrasound screening in select patients can identify potentially pre-existing DVTs, and that PSI-12 misclassification is both common and carries significant implications for hospital quality metrics and finances. Incorporating admission venous duplex studies into PSI-12 evaluations could provide a more accurate assessment of thrombus timing and etiology, thus reducing misclassification rates and improving patient safety. As hospitals continue to refine quality improvement strategies, integrating early duplex screening, enhanced documentation review processes, and standardized classification criteria may help ensure that PSI-12 remains a valid and meaningful measure of surgical quality. Future multi-institutional studies are needed to validate these findings and refine standardized approaches to perioperative VTE surveillance.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur findings suggest that a substantial proportion of PSI-12 positive venous thromboembolism events may represent pre-existing disease rather than truly hospital-acquired VTE. One third of PSI-12 positive patients had abnormal early duplex findings, and nearly 9% of cases were misclassified, highlighting important limitations of PSI-12 as a surgical quality metric. Incorporating admission duplex studies in selected high-risk patients may improve the accuracy of PSI-12 classification, reduce unnecessary healthcare costs, and ensure that patient safety metrics more accurately reflect preventable harm.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVTE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVenous thromboembolism\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDVT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDeep vein thrombosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePulmonary embolism\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAHRQ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAgency for Healthcare Research and Quality\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePatient Safety Indicator\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePOA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePresent on Admission\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVQI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVascular Quality Initiative\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSQIP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Surgical Quality Improvement Program\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003eThis study utilized de-identified data obtained from a quality improvement database at Cedars-Sinai Medical Center. Analysis of de-identified data generated for purposes other than research was determined to meet “Not Regulated” status by the Cedars-Sinai Medical Center Institutional Review Board (IRB). Therefore, formal IRB approval and informed consent were not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe datasets used are not publicly available as they originate from an institutional quality improvement database but are available from the corresponding author on reasonable request and with appropriate institutional approvals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u0026nbsp;\u003c/strong\u003eASS contributed to conceptualization, methodology, software development, formal analysis, visualization, and writing of the original draft. RTM contributed to methodology, software development, formal analysis, and writing of the original draft. OP contributed to investigation, resources, and data curation. MB contributed to writing, review, and editing of the manuscript. RFA contributed to conceptualization, methodology, visualization, supervision, and project administration. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eValsami S, Asmis LM. A Brief Review of 50 Years of Perioperative Thrombosis and Hemostasis Management. Semin Hematol. 2013;50(2):79\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1053/j.seminhematol.2013.04.001\u003c/span\u003e\u003cspan address=\"10.1053/j.seminhematol.2013.04.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGainsbury ML, Erdrich J, Taubman D, et al. Prevalence and Predictors of Preoperative Venous Thromboembolism in Asymptomatic Patients Undergoing Major Oncologic Surgery. Ann Surg Oncol. 2018;25(6):1640\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1245/s10434-018-6461-2\u003c/span\u003e\u003cspan address=\"10.1245/s10434-018-6461-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAHRQ QI: Patient Safety Indicators Overview. Accessed December 23. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://qualityindicators.ahrq.gov/measures/psi_resources?\u003c/span\u003e\u003cspan address=\"https://qualityindicators.ahrq.gov/measures/psi_resources?\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Q, Rosen AK, Borzecki A, Shwartz M. Using Harm-Based Weights for the AHRQ Patient Safety for Selected Indicators Composite (PSI ‐90): Does It Affect Assessment of Hospital Performance and Financial Penalties in Veterans Health Administration Hospitals? Health Serv Res. 2016;51(6):2140\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/1475-6773.12596\u003c/span\u003e\u003cspan address=\"10.1111/1475-6773.12596\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEstimating the Additional Hospital Inpatient Cost and Mortality Associated With Selected Hospital-Acquired Conditions. Accessed December 23. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ahrq.gov/hai/pfp/haccost2017.html\u003c/span\u003e\u003cspan address=\"https://www.ahrq.gov/hai/pfp/haccost2017.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePSI_12_Perioperative_Pulmonary_Embolism_or_Deep_Vein_Thrombosis_Rate.pdf. Accessed December 23. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://qualityindicators.ahrq.gov/Downloads/Modules/PSI/V2024/TechSpecs/PSI_12_Perioperative_Pulmonary_Embolism_or_Deep_Vein_Thrombosis_Rate.pdf\u003c/span\u003e\u003cspan address=\"https://qualityindicators.ahrq.gov/Downloads/Modules/PSI/V2024/TechSpecs/PSI_12_Perioperative_Pulmonary_Embolism_or_Deep_Vein_Thrombosis_Rate.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHavranek MM, R\u0026uuml;ter F, Bilger S, et al. Validity of 16 AHRQ Patient Safety Indicators to identify in-hospital complications: a medical record review across nine Swiss hospitals. Int J Qual Health Care. 2023;35(4):0\u0026ndash;0. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/intqhc/mzad092\u003c/span\u003e\u003cspan address=\"10.1093/intqhc/mzad092\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeld N, Jung B, Sommervold L, Singh S, Kreuziger LB. Patient Safety Indicator-12 Rarely Identifies Problems with Quality of Care in Perioperative Venous Thromboembolism. J Hosp Med. 2020;15(2):75\u0026ndash;80. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.12788/jhm.3298\u003c/span\u003e\u003cspan address=\"10.12788/jhm.3298\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSorber R, Giuliano KA, Hicks CW, Black JH. Patient Safety Indicators are an insufficient performance metric to track and grade outcomes of open aortic repair. J Vasc Surg. 2021;73(1):240\u0026ndash;e2495. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jvs.2020.04.517\u003c/span\u003e\u003cspan address=\"10.1016/j.jvs.2020.04.517\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCima RR, Lackore KA, Nehring SA, et al. How best to measure surgical quality? comparison of the Agency for Healthcare Research and Quality Patient Safety Indicators (AHRQ-PSI) and the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) postoperative adverse events at a single institution. Surgery. 2011;150(5):943\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.surg.2011.06.020\u003c/span\u003e\u003cspan address=\"10.1016/j.surg.2011.06.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKubasiak JC, Francescatti AB, Behal R, Myers JA. Patient Safety Indicators for Judging Hospital Performance: Still Not Ready for Prime Time. Am J Med Qual. 2017;32(2):129\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1062860615618782\u003c/span\u003e\u003cspan address=\"10.1177/1062860615618782\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElkbuli A, Godelman S, Miller A, et al. Improved clinical documentation leads to superior reportable outcomes: An accurate representation of patient\u0026rsquo;s clinical status. Int J Surg. 2018;53:288\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijsu.2018.03.081\u003c/span\u003e\u003cspan address=\"10.1016/j.ijsu.2018.03.081\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRajahraman V, Fassihi SC, Patel V, Pope CA, Rozell JC, Schwarzkopf R. Accuracy of ICD-10 Coding for Femoral Head Bearing Surfaces in Hip Arthroplasty. J Arthroplast. 2023;38(5):794\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.arth.2022.12.002\u003c/span\u003e\u003cspan address=\"10.1016/j.arth.2022.12.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eH\u0026auml;fliger E, Kopp B, Darbellay Farhoumand P, et al. Risk Assessment Models for Venous Thromboembolism in Medical Inpatients. JAMA Netw Open. 2024;7(5):e249980. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jamanetworkopen.2024.9980\u003c/span\u003e\u003cspan address=\"10.1001/jamanetworkopen.2024.9980\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParks AL, Auerbach AD, Schnipper JL et al. Venous thromboembolism (VTE) prevention and diagnosis in COVID-19: Practice patterns and outcomes at 33 hospitals. Cugno M, ed. \u003cem\u003ePLoS ONE\u003c/em\u003e. 2022;17(5):e0266944. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0266944\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0266944\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeeman E, Liu V, Mishra P, et al. Trends and Risk Factors for Venous Thromboembolism Among Hospitalized Medical Patients. JAMA Netw Open. 2022;5(11):e2240373. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jamanetworkopen.2022.40373\u003c/span\u003e\u003cspan address=\"10.1001/jamanetworkopen.2022.40373\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShapiro S, Majert J, Obeidalla A, et al. Same-day emergency care: a retrospective observational study of the incidence and predictors of venous thromboembolism following hospital-based acute ambulatory medical care. J Thromb Haemost. 2025;23(1):97\u0026ndash;107. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jtha.2024.09.017\u003c/span\u003e\u003cspan address=\"10.1016/j.jtha.2024.09.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"patient-safety-in-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psis","sideBox":"Learn more about [Patient Safety in Surgery](http://pssjournal.biomedcentral.com/)","snPcode":"13037","submissionUrl":"https://submission.nature.com/new-submission/13037/3","title":"Patient Safety in Surgery","twitterHandle":"@EMSurgeryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"VTE, Venous duplex ultrasound, PSI-12, Misclassification, Patient Safety.","lastPublishedDoi":"10.21203/rs.3.rs-9087206/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9087206/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eVenous thromboembolism (VTE) is a major cause of morbidity among surgical patients. Patient Safety Indicator 12 (PSI-12) identifies perioperative VTE events. This study evaluates whether early admission duplex ultrasound identifies VTEs associated with PSI-12 coding and assesses PSI-12 classification accuracy.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA single-center retrospective analysis was conducted on surgical patients with a venous duplex ultrasound within 48 hours of admission at a large academic medical center (2013\u0026ndash;2024). Two cohorts were analyzed: (1) all surgical patients with early duplex imaging, (2) PSI-12 positive elective surgical patients with early duplex imaging. The primary outcome was the prevalence of pre-existing DVT identified within 48 hours among PSI-12 positive patients. Diagnostic accuracy of early abnormal duplex findings for predicting PSI-12 classification was assessed using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong all 10,498 surgical patients, 10.6% had positive duplex findings for DVT. PSI-12 positive patients had double the prevalence compared to PSI-12 negatives (20.9% vs 10.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In PSI-12 positive elective cases, 10.7% of preoperative duplex studies identified a DVT. Misclassification, defined as PSI-12 positive admissions without imaging-confirmed DVT or pulmonary embolism, occurred in 8.7% of elective cases. Overall, 36.7% of PSI-12 positive patients had abnormal early duplex findings. Early duplex demonstrated limited sensitivity but high specificity (sensitivity 36.7%, specificity 81.7%, PPV 3.7%, NPV 98.5%).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur findings suggest possible pre-existing disease rather than hospital-acquired VTE in PSI-12 positive patients. Incorporating admission duplex studies could improve PSI-12 classification accuracy, reduce costs, and enhance patient safety.\u003c/p\u003e","manuscriptTitle":"Patient Safety Implications of PSI‑12 Misclassification and the Role of Early Venous Duplex Screening: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-07 13:42:43","doi":"10.21203/rs.3.rs-9087206/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-07T19:05:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T15:12:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-06T19:10:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13971702239651658283025710662139947255","date":"2026-05-06T19:08:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227265540355291645404775460793174367878","date":"2026-05-06T17:09:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-28T18:04:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"156410785083536002490845978954603387261","date":"2026-04-28T17:51:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-28T17:36:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-14T13:11:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-13T06:16:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Patient Safety in Surgery","date":"2026-03-10T18:51:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"patient-safety-in-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psis","sideBox":"Learn more about [Patient Safety in Surgery](http://pssjournal.biomedcentral.com/)","snPcode":"13037","submissionUrl":"https://submission.nature.com/new-submission/13037/3","title":"Patient Safety in Surgery","twitterHandle":"@EMSurgeryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1f20a8c3-3fdb-4882-90e7-be0e592750cd","owner":[],"postedDate":"May 7th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-07T19:05:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T15:12:02+00:00","index":18,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-06T19:10:07+00:00","index":17,"fulltext":""},{"type":"reviewerAgreed","content":"13971702239651658283025710662139947255","date":"2026-05-06T19:08:48+00:00","index":16,"fulltext":""},{"type":"reviewerAgreed","content":"227265540355291645404775460793174367878","date":"2026-05-06T17:09:37+00:00","index":15,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T12:09:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-07 13:42:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9087206","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9087206","identity":"rs-9087206","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}