scholarly journals Application of the Caprini risk assessment model for deep vein thrombosis among patients undergoing laparoscopic surgery for colorectal cancer

Medicine ◽  
2021 ◽  
Vol 100 (4) ◽  
pp. e24479
Author(s):  
Xiuying Lu ◽  
Weirong Zeng ◽  
Lin Zhu ◽  
Lu Liu ◽  
Fengmei Du ◽  
...  
Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 452-452
Author(s):  
Sabine Eichinger ◽  
Georg Heinze ◽  
Paul Alexander Kyrle

Abstract Abstract 452 Background: Venous thrombosis is a chronic and potentially fatal disease (case fatality 5-9%). Predicting the likelihood of recurrence is important, as most recurrences can be prevented by antithrombotic therapy, albeit at the price of an increased bleeding risk during anticoagulation. Despite a substantial progress in identifying the determinants of the recurrence risk, predicting recurrence in an individual patient is often not feasible. Venous thromboembolism (VTE) is a multicausal disease and the combined effect of clinical and laboratory factors on the recurrence risk is unknown. It was the aim of our study to develop a simple risk model that improves prediction of the recurrence risk in patients with unprovoked VTE. Methods and Findings: In a prospective multicenter cohort study we followed 929 patients with a first VTE after completion of at least 3 months of anticoagulation. The median observation time was 43.3 months. Patients with VTE provoked by surgery, trauma, cancer, pregnancy or oral contraceptive intake were excluded as were those with a natural inhibitor deficiency or the lupus anticoagulant. The main outcome measure was symptomatic recurrent VTE, which occurred in 176 patients. The probability of recurrence (95% CI) after 2, 5 and 10 years was 13.8% (11.6% to16.5%), 24.6% (21.6% to 28.9%), and 31.8% (27.6% to 37.4%), respectively. To develop a simple and easy to apply risk assessment model, clinical and laboratory variables (age, sex, location of VTE, body mass index, factor V Leiden, prothrombin G20210A mutation, D-Dimer, in vitro thrombin generation) were preselected based on their established relevance for the recurrence risk, simple assessment, and reproducibility. All variables were analyzed in a Cox proportional hazards model, and those significantly associated with recurrence were used to compute risk scores. Only male sex [HR vs. female 1.90 (95% CI 1.31–2.75)], proximal deep vein thrombosis [HR vs. distal 2.08 (95% CI 1.16–3.74)], pulmonary embolism [HR vs. distal thrombosis 2.60 (95% CI 1.49– 4.53)] and elevated levels of D-Dimer [HR per doubling 1.27 (95% CI 1.08–1.51)] or peak thrombin [HR per 100 nM increase 1.38 (95% CI 1.17–1.63)] were related to a higher recurrence risk. We developed a nomogram (Fig. 1) based on sex, location of initial thrombosis, and D-Dimer that can be used to calculate risk scores and to estimate the cumulative probabilities of recurrence in an individual patient. The model has undergone extensive validation by a cross-validation process. The cohort was divided into test and validation samples thereby mimicking independent validation. This process was repeated 1000 times and the results were averaged to avoid dependence of the validation results on a particular partition of our cohort. Patients were assigned to different risk categories according to their risk score, which corresponded well with the recurrence rate as patients with lower scores had lower recurrence rates. Conclusion: By use of a simple scoring system the assessment of the recurrence risk in patients with a first unprovoked VTE can be improved in routine care. Patients with unprovoked VTE in whom the recurrence risk is low enough to consider a limited duration of anticoagulation, can be identified. Disclosures: No relevant conflicts of interest to declare.


2020 ◽  
Vol 26 ◽  
pp. 107602962096145
Author(s):  
Eugene S. Krauss ◽  
MaryAnne Cronin ◽  
Nancy Dengler ◽  
Barry G. Simonson ◽  
Paul Enker ◽  
...  

Two of the more common potential complications after arthroplasty are venous thromboembolism (VTE), which includes deep vein thrombosis (DVT) and pulmonary embolus (PE), and excess bleeding. Appropriate chemoprophylaxis choices are essential to prevent some of these adverse events and from exacerbating others. Risk stratification to prescribe safe and effective medications in the prevention of postoperative VTE has shown benefit in this regard. The Department of Orthopaedic Surgery at Syosset Hospital/Northwell Health, which performs over 1200 arthroplasties annually, has validated and is using the 2013 version of the Caprini Risk Assessment Model (RAM) to stratify each patient for risk of postoperative VTE. This tool results in a culling of information, past and present, personal and familial, that provides a truly thorough evaluation of the patient’s risk for postoperative VTE. The Caprini score then guides the medication choices for thromboprophylaxis. The Caprini score is only valuable if the data is properly collected, and we have learned numerous lessons after applying it for 18 months. Risk stratification requires practice and experience to achieve expertise in perioperative patient evaluation. Having access to pertinent patient information, while gaining proficiency in completing the Caprini RAM, is vital to its efficacy. Ongoing, real time analyses of patient outcomes, with subsequent change in process, is key to improving patient care.


Author(s):  
Sheetal John ◽  
Atiya R. Faruqui ◽  
Soumya Umesh

Background: There is limited data from India on Deep Vein Thrombosis (DVT) Prophylaxis. This study was done in hospitalised patients at high risk for DVT, to determine the patterns and rates of pharmacoprophylaxis, drugs used and their clinical outcomes.Methods: This prospective study screened patients for risk of DVT using the Padua risk assessment model. Padua score ≥4 were included and data on disease demographics, prophylaxis and outcomes of DVT at 12 weeks were collected. Factors affecting prophylaxis were assessed using multivariate logistic regression.Results: Out of 453 screened, 200 eligible patients were recruited. 48.5% were females; mean age was 54.6±16.6; 50.5% received some thromboprophylaxis, of which 24%, 35.5% and 9% received pharmacoprophylaxis, mechanoprophylaxis and a combination of both respectively. Low Molecular Weight Heparin was the most commonly used drug (77.1%). Adverse drug reactions reported were 24, none related to anticoagulant use. At 12 weeks, 18 (9%) patients gave history suggestive of DVT. 5 deaths were reported, but the cause could not be ascertained. Patients who had cardiac/ respiratory failure [OR =5.2 (95%CI - 1.13, 24.6), p = 0.03], acute MI or stroke [OR = 9.0 (3.5, 23.09), p <0.001], those admitted to medical specialties [OR = 3.4 -1.4, 7.9), p = 0.004] and to private wards [OR = 7.4 (3.13, 17.5), p <0.001] had significantly higher chances of receiving prophylaxis.Conclusions: Underutilisation of effective prophylaxis, despite high prevalence of DVT risk. Emphasis on routine risk assessment of hospitalized patients and administration of appropriate prophylaxis to those at high risk is required.


2021 ◽  
Author(s):  
Ying Chen ◽  
SuMei Wang ◽  
Jie Di ◽  
Xian Qin ◽  
Chun Guan ◽  
...  

Abstract Background The objective of this study was to establish a risk assessment model for lower extremity deep venous thrombosis in critically ill patients and compared with Caprini, Padua and Wells risk assessment model to evaluate its efficacy. Methods We conducted a pooled analysis of prospective cohort studies. The outcomes of interest were lower extremity deep vein thrombosis group and Non-lower extremity deep vein thrombosis group were determined by univariate analysis, and SPSS was used to establish the back propagation artificial neural network prediction model. ROC curve was used to evaluate the predictive effectiveness of the model. Medcalc15.2 was used to compare the predictive capabilities of different models. Results 600 cases of intensive care unit patients were selected in this study. The prevalence of lower extremity venous thromboembolism after ICU admission was 12.5%. The results of univariate analysis that showed 16 statistically significant difference influencing factors. The ROC curve area of BP-ANN risk assessment model was 0.828, showing good predictive efficacy. In addition to the ROC curve area of BP-ANN risk assessment model was higher than Caprini, Padua and Wells model. Conclusion BP-ANN risk assessment model can play an auxiliary role in predicting the occurrence of lower extremity venous thromboembolism in critically ill patients. This model can provide a reference for medical staff to take preventive management measures.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xiao-Liang Xing ◽  
Zhi-Yong Yao ◽  
Chaoqun Xing ◽  
Zhi Huang ◽  
Jing Peng ◽  
...  

Abstract Background Colorectal cancer (CRC) is the second most prevalent cancer, as it accounts for approximately 10% of all annually diagnosed cancers. Studies have indicated that DNA methylation is involved in cancer genesis. The purpose of this study was to investigate the relationships among DNA methylation, gene expression and the tumor-immune microenvironment of CRC, and finally, to identify potential key genes related to immune cell infiltration in CRC. Methods In the present study, we used the ChAMP and DESeq2 packages, correlation analyses, and Cox regression analyses to identify immune-related differentially expressed genes (IR-DEGs) that were correlated with aberrant methylation and to construct a risk assessment model. Results Finally, we found that HSPA1A expression and CCRL2 expression were positively and negatively associated with the risk score of CRC, respectively. Patients in the high-risk group were more positively correlated with some types of tumor-infiltrating immune cells, whereas they were negatively correlated with other tumor-infiltrating immune cells. After the patients were regrouped according to the median risk score, we could more effectively distinguish them based on survival outcome, clinicopathological characteristics, specific tumor-immune infiltration status and highly expressed immune-related biomarkers. Conclusion This study suggested that the risk assessment model constructed by pairing immune-related differentially expressed genes correlated with aberrant DNA methylation could predict the outcome of CRC patients and might help to identify those patients who could benefit from antitumor immunotherapy.


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