Prognostic nomogram for 30-day mortality of deep vein thrombosis patients in intensive care unit

Shen, Runnan; Gao, Ming; Tao, Yangu; Chen, Qinchang; Wu, Guitao; Guo, Xushun; Xia, Zuqi; You, Guochang; Hong, Zilin

doi:10.1186/s12872-020-01823-4

Cited by 9 publications

(8 citation statements)

References 47 publications

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“…Compared with the serum creatinine, BUN was a better index to reflect the DKA severity. Previous studies have also revealed that high BUN levels are correlated with poor prognosis in ICU patients 24 25 . As high BUN was also found to be related to the poor prognosis of patients with acute heart failure, acute respiratory disease syndrome, and hepatic decompensation 26 27 28 , BUN might reflect the degree of injury of multiple important organs, which were also an important risk factor of critically ill patients.…”

Section: Discussionmentioning

confidence: 95%

“…BUN is usually regarded as an important indicator of blood volume. Although many patients with DKA are complicated with acute renal failure, dehydration is the most common state among patients with DKA due to hypovolemia and hypotension Accepted Manuscript also revealed that high BUN levels are correlated with poor prognosis in ICU patients [24,25]. As high BUN was also found to be related to the poor prognosis of patients with acute heart failure, acute respiratory disease syndrome, and hepatic decompensation [26][27][28], BUN might reflect the degree of injury of multiple important organs, which were also found to be an important risk factor of critically ill patients.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

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Blood Urea Nitrogen to Serum Albumin Ratio as A New Prognostic Indicator in Critically Ill Patients with Diabetic Ketoacidosis: A Retrospective Cohort Study

Hang,

Huang,

et al. 2024

Exp Clin Endocrinol Diabetes

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Purpose: Diabetic ketoacidosis (DKA) remains a life-threatening medical emergency. Blood urea nitrogen to serum albumin (BAR) demonstrated good predictive ability in the mortality of patients with various diseases. The study aimed to investigate the predictive value of BAR for in- and out-of-hospital mortality in critically ill patients with DKA. Methods: Data were obtained from the Medical Information Mart for Intensive Care III (MIMIC-III) database and all the eligible subjects were divided into two groups by a cutoff value of BAR. The multiple logistic regression analysis was conducted to determine the association between BAR and in-hospital mortality. The predictive performance of BAR was evaluated by Kaplan–Meier (K-M) analysis. Propensity score matching (PSM) was applied to control confounding factors between the low BAR and high BAR groups. Results: A total of 589 critically ill DKA patients were enrolled. DKA patients with a higher BAR level were associated with higher in-hospital mortality and out-hospital mortality (all p<0.001). There was a significant four-year survival difference between the low and high BAR groups (p<0.0001). After PSM analysis, two PSM groups (202 pairs, n = 404) were generated, and similar results were observed in the K-M curve (p<0.0001). Conclusions: Elevated levels of BAR were associated with an increased risk of in-hospital mortality in critically ill patients with DKA, and BAR could be an independent prognostic factor in in-hospital mortality and out-hospital mortality for patients diagnosed with DKA.

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Section: Discussionmentioning

confidence: 95%

Section: Accepted Manuscriptmentioning

confidence: 99%

Blood Urea Nitrogen to Serum Albumin Ratio as A New Prognostic Indicator in Critically Ill Patients with Diabetic Ketoacidosis: A Retrospective Cohort Study

Hang,

Huang,

et al. 2024

Exp Clin Endocrinol Diabetes

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“…Candidate clinical variables were selected based on published studies, accessibility, and professional knowledge. [7][8][9][10][11]18,19 We collected the basic information (gender, body mass index [BMI], smoking, previous history of VTE, etc. ), laboratory data (preoperative PSA, postoperative D-Dimer, postoperative PLT, coagulation index, T stage, etc.…”

Section: Data Collectionmentioning

confidence: 99%

Construction and Verification of Risk Predicting Models to Evaluate the Possibility of Venous Thromboembolism After Robot-Assisted Radical Prostatectomy

Cheng

Zhou

et al. 2022

Ann Surg Oncol

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Background Venous thromboembolism (VTE) is the second leading cause for death of radical prostatectomy. We aimed to establish new nomogram to predict the VTE risk after robot-assisted radical prostatectomy (RARP). Methods Patients receiving RARP in our center from November 2015 to June 2021, were enrolled in study. They were randomly divided into training and testing cohorts by 8:2. Univariate and multivariate logistic regression (model A) and stepwise logistic regression (model B) were used to fit two models. The net reclassification improvement (NRI), integrated discrimination improvement (IDI), and receiver operating characteristic (ROC) curve were used to compare predictive abilities of two new models with widely used Caprini risk assessment (CRA) model. Then, two nomograms were constructed and received internal validation. Results Totally, 351 patients were included. The area under ROC of model A and model B were 0.967 (95% confidence interval: 0.945–0.990) and 0.978 (95% confidence interval: 0.960–0.996), which also were assayed in the testing cohorts. Both the prediction and classification abilities of the two new models were superior to CRA model (NRI > 0, IDI > 0, p < 0.05). The C-index of Model A and Model B were 0.968 and 0.978, respectively. For clinical usefulness, the two new models offered a net benefit with threshold probability between 0.08 and 1 in decision curve analysis, suggesting the two new models predict VTE events more accurately. Conclusions Both two new models have good prediction accuracy and are superior to CRA model. Model A has an advantage of less variable. This easy-to-use model enables rapid clinical decision-making and early intervention in high-risk groups, which ultimately benefit patients.

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“…SAB model includes sepsis, the maximum of anion gap and the minimum of bicarbonate. Sometimes the treatment of infection is insufficient, which may lead to organ dysfunction or sepsis (25,26). Sepsis significantly increases the length of hospital stay and mortality in ICU patients.…”

Section: Atmentioning

confidence: 99%

Development of SAB model for predicting mortality in intensive care unit after aortic aneurysm surgery

Shen

Peng

et al. 2021

Ann Palliat Med

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Background: Aortic aneurysm (AA) patients after vascular surgery are at high risk of death, some of them need intensive care. Our aim was to develop a simplified model with baseline data within 24 hours of intensive care unit (ICU) admission to early predict mortality.Methods: Univariate analysis and least absolute shrinkage and selection operator were used to select important variables, which were then taken into logistic regression to fit the model. Discrimination and validation were used to evaluate the performance of the model. Bootstrap method was conducted to perform internal validation. Finally, decision clinical analysis curve was used to test the clinical usefulness of the model. Results:We obtained baseline data of 482 AA patients from Medical Information Mart for Intensive Care III database, 33 (6.8%) of whom died in ICU. Our final model contained three variables and was called SAB model based on initials of three items [Sepsis, Anion gap, Bicarbonate (SAB)]. Area under the curve of SAB was 0.904 (95% CI: 0.841-0.967) while brier score was 0.043 (95% CI: 0.028-0.057). After internal validation, corrected area under the curve was 0.898 and brier score was 0.045, which showed good prediction ability of SAB model. The model can be assessed on https://vascularmodel.shinyapps.io/ AorticAneurysm/.Conclusions: SAB model derived in this study can be easily used to predict in-ICU mortality of AA patients after surgery precisely.

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Prognostic nomogram for 30-day mortality of deep vein thrombosis patients in intensive care unit

Cited by 9 publications

References 47 publications

Blood Urea Nitrogen to Serum Albumin Ratio as A New Prognostic Indicator in Critically Ill Patients with Diabetic Ketoacidosis: A Retrospective Cohort Study

Blood Urea Nitrogen to Serum Albumin Ratio as A New Prognostic Indicator in Critically Ill Patients with Diabetic Ketoacidosis: A Retrospective Cohort Study

Construction and Verification of Risk Predicting Models to Evaluate the Possibility of Venous Thromboembolism After Robot-Assisted Radical Prostatectomy

Development of SAB model for predicting mortality in intensive care unit after aortic aneurysm surgery

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