scholarly journals Development and validation of postoperative predictive recurrence nomograms in patients with persistent atrial fibrillation: a retrospective cohort study

2021 ◽  
Author(s):  
Cong-ying Deng ◽  
Ling Sun ◽  
Yuan Ji
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Prediction Model ◽  
Linear Prediction ◽  
Preoperative Evaluation ◽  
Univariate Analysis ◽  
Persistent Atrial Fibrillation ◽  
Risk Of Recurrence ◽  
Discrimination Ability ◽  
Calibration Curves

Background： Patients with persistent atrial fibrillation（PsAF） still have a higher risk of recurrence after catheter radiofrequency ablation. Nevertheless, effective recurrence forecast tools have not been established for these patients. Thus, this research aimed to develop and validate an easy-to-use linear prediction model for predicting postoperative recurrence in patients with PsAF. Methods： We conducted a single-center, retrospective, observational study of patients with PsAF admitted to our hospital from June 2013 to June 2021. Univariate analysis was used to screen risk factors, then we used multivariate regression analysis to evaluate the independence of each risk factor and construct a combined prediction model which incorporated into a nomogram, finally, we took the receiver operating characteristic (ROC) curve to predict the value of nomogram model. Additionally, the calibration curves and decision curve analysis (DCA) were also performed to assess the clinical utility of the nomogram. Results： A total of 209 subjects were included in the study and 42 (20.10%) were followed up to September 2021 for recurrent AF.  Duration of AF, Left atrial diameter(LAD), BMI, CKMB, and alcohol consumption were independent risk factors (P < 0.05),  these variables were integrated into the nomogram model, and the area under the curve （AUC） was 0.895, the sensitivity was 93.3%, and the specificity was 71.4%, indicating that the model had an excellent predictive performance.  The C-index of the predictive nomogram model was 0.906. The calibration curves and DCA results manifested that the Model had a splendid predictive correction and discrimination ability. Conclusion： This simple and innovative clinical nomogram (that any clinician can use in the daily clinic) can help evaluate the risk of recurrence after catheter ablation in PsAF, facilitate preoperative evaluation as well as the postoperative follow-up, and may also help generate personalized therapeutic strategies.

scholarly journals Risk factors and prediction model construction of post-operative atrial fibrillation after thoracic surgery in Chinese patients

2021 ◽  
Author(s):  
Yunling Lin ◽  
Jianmin Sun ◽  
Xun Yuan ◽  
Hui Liu
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Logistic Regression ◽  
Thoracic Surgery ◽  
Prediction Model ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Chinese Patients ◽  
Multivariate Logistic Regression ◽  
Post Operative Atrial Fibrillation

IntroductionThe purpose of this study was to analyze the risk factors of post-operative atrial fibrillation (POAF) after thoracic surgery, and to build a predictive model for accurate preoperative identification of high-risk patients.Material and methodsIn this study, data of 2072 patients with pulmonary masses and esophageal cancer who attended our hospital in the period from January 1, 2017 to December 31, 2018 were analyzed retrospectively. According to whether AF occurred after the operation, the patients were divided into atrial fibrillation (AF) and non-AF (NAF) groups. The general information (age, sex, height, etc.), previous medical history (chronic lung disease, hypertension, etc.), medication history, preoperative ultrasound and cardiogram results, and preoperative and postoperative electrocardiogram (ECG) were collected. The operation mode, resection scope, histopathology and hospitalization were recorded. Univariate and multivariate logistic regression were used to screen out the risk factors of AF and establish a prediction model.ResultsThe incidence of POAF was 5.98%. Univariate analysis showed that sex, age, body mass index, left atrial diameter and operation organ were the risk factors of POAF. The above factors were included in the multivariate logistic regression analysis, and the results showed that male sex, age, anteroposterior diameter of left atrium and surgical organs were related to POAF. On this basis, a POAF prediction model was constructed, which had good discrimination and calibration. The area under the curve (AUC) is 0.784 with 95% CI: 0.746–0.822.ConclusionsThe prediction model of POAF based on the risk factors selected in this study can accurately predict the occurrence of AF after thoracic surgery.

scholarly journals Development of Predictive Nomograms for Clinical Use to Quantify the Risk of Amputation in Patients with Diabetic Foot Ulcer

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Bocheng Peng ◽  
Rui Min ◽  
Yiqin Liao ◽  
Aixi Yu
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Prediction Model ◽  
Predictive Factors ◽  
Diabetic Foot ◽  
Univariate Analysis ◽  
Foot Ulcer ◽  
Diabetic Foot Ulcer ◽  
Single Factor ◽  
Independent Risk Factors

Objective. To determine the novel proposed nomogram model accuracy in the prediction of the lower-extremity amputations (LEA) risk in diabetic foot ulcer (DFU). Methods and Materials. In this retrospective study, data of 125 patients with diabetic foot ulcer who met the research criteria in Zhongnan Hospital of Wuhan University from January 2015 to December 2019 were collected by filling in the clinical investigation case report form. Firstly, univariate analysis was used to find the primary predictive factors of amputation in patients with diabetic foot ulcer. Secondly, single factor and multiple factor logistic regression analysis were employed to screen the independent influencing factors of amputation introducing the primary predictive factors selected from the univariate analysis. Thirdly, the independent influencing factors were applied to build a prediction model of amputation risk in patients with diabetic foot ulcer by using R4.3; then, the nomogram was established according to the selected variables visually. Finally, the performance of the prediction model was evaluated and verified by receiver working characteristic (ROC) curve, corrected calibration curve, and clinical decision curve. Results. 7 primary predictive factors were selected by univariate analysis from 21 variables, including the course of diabetes, peripheral angiopathy of diabetic (PAD), glycosylated hemoglobin A1c (HbA1c), white blood cells (WBC), albumin (ALB), blood uric acid (BUA), and fibrinogen (FIB); single factor logistic regression analysis showed that albumin was a protective factor for amputation in patients with diabetic foot ulcer, and the other six factors were risk factors. Multivariate logical regression analysis illustrated that only five factors (the course of diabetes, PAD, HbA1c, WBC, and FIB) were independent risk factors for amputation in patients with diabetic foot ulcer. According to the area under curve (AUC) of ROC was 0.876 and corrected calibration curve of the nomogram displayed good fitting ability, the model established by these 5 independent risk factors exhibited good ability to predict the risk of amputation. The decision analysis curve (DCA) indicated that the nomogram model was more practical and accurate when the risk threshold was between 6% and 91%. Conclusion. Our novel proposed nomogram showed that the course of diabetes, PAD, HbA1c, WBC, and FIB are the independent risk factors of amputation in patients with DFU. This prediction model was well developed and behaved a great accurate value for LEA so as to provide a useful tool for screening LEA risk and preventing DFU from developing into amputation.

scholarly journals Tumor marker based survival analysis for patients with pseudomyxoma peritonei of appendiceal origin: A retrospective cohort study

2020 ◽  
Author(s):  
Mingjian Bai ◽  
Shilong Wang ◽  
Ruiqing Ma ◽  
Ying Cai ◽  
Yiyan Lu ◽  
...  
Keyword(s):  
Prediction Model ◽  
Pseudomyxoma Peritonei ◽  
Roc Analysis ◽  
Prediction Models ◽  
Radical Surgery ◽  
Univariate Analysis ◽  
Barthel Index Score ◽  
Discrimination Ability ◽  
First Time ◽  
D Dimer

Abstract Background Pseudomyxoma peritonei (PMP) is a rare disease, the prognosis of overall survival (OS) is affected by many factors, present study aim to screen independent prediction indicators for PMP and establish prediction model for OS rates in PMP.Methods 119 PMP patients received cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) in our center for the first time were included between 01/06/2013 and 22/11/2019 . The log-rank test was used to compare the OS rate among groups, subsequently, variables with P<0.10 were subjected to multivariate Cox model for screening independent prediction indicators. Finally, the prediction models for OS in PMP will be established.Results Univariate analysis showed that Barthel Index Score, albumin, D-dimer, CEA, CA125, CA19-9, CA724, CA242, PCI, degree of radical surgery, histopathological grade were significant predictors for OS in PMP. At multivariate analysis, sex, D-dimer, CA125, CA19-9, and degree of radical surgery were independently associated with OS rate in PMP. ROC analysis was performed to calculate discrimination ability of prediction model and the area under curves (AUC) was 0.902 (95%CI: 0.823-0.954). Finally, nomogram was plotted by the independent predictive factors for PMP.Conclusions Several factors (sex, degree of radical surgery, D-dimer, preoperative CA125 and CA19-9) have independent prognostic value for survival in PMP, the tumor based prediction model has better prediction value, more researches are need to verify and improve the prediction model.

Abstract 9733: Atrial Fibrosis is Associated With Higher DC Cardioversion Failure Rates in Persistent Atrial Fibrillation

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Mohamed R Labedi ◽  
Abdulmohsin Ahmadjee ◽  
Mathias Koopman ◽  
Nassir Marrouche ◽  
Brent Wilson ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Drug Use ◽  
Sinus Rhythm ◽  
Univariate Analysis ◽  
Persistent Atrial Fibrillation ◽  
Class I ◽  
Class Iii ◽  
Atrial Fibrosis ◽  
Dc Cardioversion

Introduction: DC cardioversion (DCCV) is commonly performed in atrial fibrillation (AF). We examined the association between atrial fibrosis quantified using late gadolinium enhancement MRI (LGE-MRI) and acute success and recurrence of AF following DCCV. Methods: Persistent AF patients without previous catheter ablation who underwent LGE-MRI and DCCV were included in the study. Acute DCCV success was defined by achievement of sinus rhythm. Demographic patient data as well as comorbidities and medications were collected from chart revisions. Results: 241 patients were included (63% male). 186 patients (77.48%) were on oral anti-coagulation, 31 (12.9%) were on class I anti-arrhythmic drugs (AAD) and 46 (19.1%) were on class III AAD at the time of cardioversion. DCCV was acutely successful in 183 patients (75.9%). AF recurred after DCCV in 194 patients (80.5%) after an average follow up of 81 days. In univariate analysis, atrial fibrosis (HR 1.04; p=0.049) and body mass index (BMI) (HR 1.04; p=0.03) were associated with DCCV failure, while left atrial area, beta blocker, calcium channel blocker, class I and class III anti-arrhythmic drug use were not. In multivariate analysis, only atrial fibrosis was a significant predictor of DCCV failure (HR 1.03; p=0.03). During follow up, anti-arrhythmic drug use (class I drugs HR 0.21; p=0.045; class III drugs HR 0.27; p=0.042) was associated with maintenance of sinus rhythm. Conclusions: LGE-MRI quantified atrial fibrosis predicts failure of DCCV in persistent AF patients while AAD use was associated with maintenance of sinus rhythm.

Abstract 16187: Incidence, Risk Factors, and Outcomes of Atrial Fibrillation After Blood and/or Marrow Transplant

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Daniel Pinkhas ◽  
John Ning ◽  
Hyun Kim ◽  
Matthew Subramani ◽  
Anita D'Souza ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Univariate Analysis ◽  
Multivariable Analysis ◽  
Early Period ◽  
Marrow Transplant ◽  
Early Mortality ◽  
Incidence Risk ◽  
History Of ◽  
First 90 Days

Introduction: Atrial fibrillation (AF) is known to occur after blood and/or marrow transplant (BMT) and has been shown to increase morbidity and mortality. Our objective was to characterize the incidence, risk factors, and clinical impact of AF in patients within the first 90 days after BMT. Methods: Patients with active malignancy undergoing BMT from 2012-2016 at the Medical College of Wisconsin were included (n=1159). Medical records were reviewed for baseline patient characteristics, AF risk factors, and clinical outcomes. Patients were categorized based on development of AF within 90 days post-BMT. Baseline characteristics and risk factors were analyzed to determine predictors for AF and all-cause mortality at 90 days. Results: Amongst the entire cohort, 5.3% of patients developed AF within the first 90 days after BMT. Significant baseline differences between those with or without AF post-BMT are outlined in Table 1. Multivariable analysis showed that a history of AF (OR: 6.7; 95% CI: 3.3-13.6; P = <0.001) and prior XRT (OR: 2.3; 95% CI: 1.2-4.6; P = 0.018) were independent predictors of developing AF. Univariate analysis demonstrated that AF was associated with 90-day mortality (HR: 7.6; 95% CI: 3.5-16.5; log rank P < 0.001). Multivariable analysis (adjusted for age, gender, race, history of XRT, BMT type, and malignancy type) revealed that female gender (HR: 2.6; 95% CI: 1.2-5.5; P = 0.016), non-Caucasian race (HR: 2.7; 95% CI: 1.1-6.4; P = 0.024) and development of AF (HR: 9.2; 95% CI: 3.7-21.5; P < 0.001) were significant independent predictors of early mortality. Conclusions: This analysis demonstrated that a prior history of AF and prior XRT were independent predictors for the development of AF in the early period post-BMT and AF is a significant independent predictor of early mortality after BMT. Further studies assessing the potential benefits of AF prevention in patients after BMT is warranted.

scholarly journals Predicting atrial fibrillation after acute abdominal surgery

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
C V Madsen ◽  
B Leerhoey ◽  
L Joergensen ◽  
C S Meyhoff ◽  
A Sajadieh ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Atrial Fibrillation ◽  
Chronic Kidney Disease ◽  
At Risk ◽  
Kidney Disease ◽  
Abdominal Surgery ◽  
Prediction Model ◽  
Vital Signs ◽  
Patients At Risk

Abstract Introduction Post-operative atrial fibrillation (POAF) is currently considered a phenomenon rather than a definite diagnosis. Nevertheless, POAF is associated with an increased rate of complications, including stroke and mortality. The incidence of POAF in acute abdominal surgery has not been reported and prediction of patients at risk has not previously been attempted. Purpose We aim to report the incidence of POAF after acute abdominal surgery and provide a POAF prediction model based on pre-surgery risk-factors. Methods Designed as a prospective, single-centre, cohort study of unselected adult patients referred for acute, general, abdominal surgery. Consecutive patients (&gt;16 years) were included during a three month period. No exclusion criteria were applied. Follow-up was based on chart reviews, including medical history, vital signs, blood samples and electrocardiograms. Chart reviews were performed prior to surgery, at discharge, and three months after surgery. Atrial fibrillation was diagnosed either by specialists in Cardiology or Anaesthesiology on ECG or cardiac rhythm monitoring (≥30 seconds duration). Multiple logistic regression with backward stepwise selection was used for model development. Receiver operating characteristic curves (ROC) including area under the curve (AUC) was produced. The study was approved by the Regional Ethics committee (H-19033464) and comply with the principles of the Declaration of Helsinki of the World Medical Association. Results In total, 466 patients were included. Mean (±SD) age was 51.2 (20.5), 194 (41.6%) were female, and cardiovascular comorbidity was present in ≈10% of patients. Overall incidence of POAF was 5.8% (27/466) and no cases were observed in patients &lt;60 years. Incidence was 15.7% (27/172) for patients ≥60 years. Prolonged hospitalization and death were observed in 40.7% of patients with POAF vs 8.4% patients without POAF (p&lt;0.001). Significant age-adjusted risk-factors were previous atrial fibrillation odds ratio (OR) 6.84 [2.73; 17.18] (p&lt;0.001), known diabetes mellitus OR 3.49 [1.40; 8.69] (p=0.007), and chronic kidney disease OR 3.03 [1.20; 7.65] (p=0.019). A prediction model, based on age, previous atrial fibrillation, diabetes mellitus and chronic kidney disease was produced (Figure 1), and ROC analysis displayed AUC 88.26% (Figure 2). Conclusions A simple risk-stratification model as the one provided, can aid clinicians in identifying those patients at risk of developing POAF in relation to acute abdominal surgery. This is important, as patients developing POAF are more likely to experience complications, such as prolonged hospitalization and death. Closer monitoring of heart rhythm and vital signs should be considered in at-risk patients older than 60 years. Model validation is warranted. FUNDunding Acknowledgement Type of funding sources: None.

scholarly journals Tumor marker based survival analysis for patients with pseudomyxoma peritonei of appendiceal origin: A retrospective cohort study

2020 ◽  
Author(s):  
Mingjian Bai ◽  
Shilong Wang ◽  
Ruiqing Ma ◽  
Ying Cai ◽  
Yiyan Lu ◽  
...  
Keyword(s):  
Prediction Model ◽  
Pseudomyxoma Peritonei ◽  
Prediction Models ◽  
Radical Surgery ◽  
Cox Model ◽  
Univariate Analysis ◽  
Rank Test ◽  
Internal Validation ◽  
Discrimination Ability ◽  
D Dimer

Abstract Background Pseudomyxoma peritonei (PMP) is a rare disease, the prognosis of overall survival (OS) is affected by many factors, present study aim to screen independent prediction indicators and establish a nomogram for PMP. Methods 119 PMP patients received cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) in our center for the first time were included between 01/06/2013 and 22/11/2019 . The log-rank test was used to compare the OS rate among groups, subsequently, variables with P<0.10 were subjected to multivariate Cox model for screening independent prediction indicators. Finally, the nomogram prediction models will be established. Results Univariate analysis showed that Barthel Index Score, Albumin, D-Dimer, CEA, CA125, CA19-9, CA724, CA242, PCI, degree of radical surgery, histopathological grade were significant predictors for OS in PMP. At multivariate analysis, Sex, D-Dimer, CA125, CA19-9, PCI, and degree of radical surgery were independently associated with OS rate in PMP. A nomogram was plotted based on the independent predictive factors for PMP and undergone internal validation, ROC analysis was performed to calculate discrimination ability of prediction model, the area under curves (AUC) was 0.880 (95% CI : 0.806- 0.933). Conclusions Several factors (Sex, D-Dimer, CA125, CA19-9, PCI, and degree of radical surgery) have independent prognostic value for survival in PMP, the tumor based prediction model has a better prediction value, more researches are need to verify and improve the prediction model.

scholarly journals Prevalence of Cerebrovascular Accidents in Patients with Ulcerative Colitis in a Single Academic Health System

2021 ◽  
Author(s):  
Erika Horta ◽  
Conor Burke-Smith ◽  
Bryant Megna ◽  
Kendall Nichols ◽  
Byron Vaughn ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Univariate Analysis ◽  
Common Type ◽  
Cerebrovascular Accidents ◽  
Cerebrovascular Complications ◽  
Increased Risk ◽  
Traditional Risk Factors ◽  
Anatomic Locations ◽  
Occipital Lobes

Abstract Background:In general, IBD increases arteriovenous thromboembolic events, though the association between UC and cerebrovascular complications remains inconclusive. Some studies suggest young women with UC have an increased risk of cerebrovascular accidents (CVA). The focus of this study was to characterize the rates, anatomic locations and risk factors for CVA in patients with UC. Methods:We developed a retrospective cohort of patients with UC at a single health care system from June 2010 to June 2015. Neuroimaging was used to document presence, location and type of stroke and traditional risk factors were considered. Results:The prevalence of CVAs increased in both sexes with a peak prevalence of 24.7% (95% CI 17.1 - 34.4) in women with UC over the age of 80. Older age, cancer and atrial fibrillation were risk factors for CVA in univariate analysis for both sexes. In multifactorial analysis, both age and atrial fibrillation were risk factors for CVA in the m-UC cohort, but only age was associated with CVA in f-UC. The most common type of CVA was ischemic stroke (77.7%). The most common locations for CVAs in UC patients were frontal and occipital lobes (19% and 18%, respectively). Conclusions:UC patients have an increased risk for CVA, with women over 80 demonstrating the highest risk. Providers should be aware of these risks in making treatment decisions for UC.

scholarly journals SUN-130 Preoperative Hematological Parameters Associated with Recurrence or Regrowth of Meningiomas

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Carolina Garcia Soares Leães Rech ◽  
Ricardo Kunde Minuzzi ◽  
Camila Batista de Oliveira Silva ◽  
Bruna Araújo ◽  
Tainá Mafalda ◽  
...  
Keyword(s):  
Cox Regression ◽  
Hematological Parameters ◽  
Preoperative Evaluation ◽  
Univariate Analysis ◽  
Tumor Resection ◽  
Prognostic Information ◽  
Free Survival ◽  
Risk Of Recurrence ◽  
Hematological Markers ◽  
Increased Risk

Abstract Meningiomas represent the most frequently diagnosed intracranial tumors. Inflammation and immune processes may play an important role in therapeutic response as well as in anti- and pro-tumor modulating function. In tumors, inflammatory markers have been able to provide useful prognostic information for treatment or clinical evaluation of patients. The aim of this study was to investigate preoperative hematological markers concerning recurrence or regrowth and clinical variables in meningioma. Eighty nine patients with no corticosteroid therapy were included. Blood tests and tumor characteristics were collected from medical records. Recurrence-free survival was evaluated using Cox regression and Kaplan-Meier curves. Of the 89 cases, 73 (82%) were grade I and 16 (18%) grade II. The mean age was 53±13.9 years, with higher frequency in women, 2:1 proportion. The most frequent subtypes were meningothelial (40.4%), transitional (23.5%) and atypical (17.9%), 64% with peripheral location and 64% had a size greater than 3 cm. Regarding tumor resection, 49 (55.1%) underwent complete surgery (40 remained with tumor (81.6%) and 9 relapse (18.3%)) and 40 (44.9%) submitted to partial resection surgery (29 remained with persistent lesion (72.5%) and 11 regrowth (25%)). In total, 20 (22.4%) cases of recurrence or regrowth were observed. The median recurrence-regrowth free survival (RFS) was 62 months, 96.1% at 1 year, 67.4% at 3 years and 51.2% at 5 years. In univariate analysis, anemia (p=0.04), neutrophilia (p=0.02) and neutrophilis/lymphocyts ratio (NLR) (p=0.03) were associated with an increased risk of recurrence or regrowth and poor RFS. In multivariate, the interaction between anemia and NLR &gt;4 represented a higher risk of recurrence or regrowth (p=0.003). The preoperative presence of anemia, neutrophilia, and NLR was associated with an increased risk of recurrence or regrowth in meningiomas, emphasizing the importance of preoperative evaluation of these parameters.

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