scholarly journals Development and Validation of a Nomogram Based on Noninvasive Liver Reserve and Fibrosis (PALBI and FIB-4) Model to Predict Posthepatectomy Liver Failure Grade B-C in Patients with Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wenhui Zhong ◽  
Feng Zhang ◽  
Kaijun Huang ◽  
Yiping Zou ◽  
Yubin Liu
Keyword(s):  
Risk Factors ◽  
Hepatocellular Carcinoma ◽  
Logistic Regression ◽  
Liver Failure ◽  
Roc Curves ◽  
Postoperative Liver Failure ◽  
Multivariate Logistic Regression ◽  
Training Set ◽  
Independent Risk Factors ◽  
Validation Set

Hepatectomy is currently one of the most effective treatments for hepatocellular carcinoma (HCC). However, postoperative liver failure (PHLF) is a serious complication and the leading cause of mortality in patients with HCC after hepatectomy. This study attempted to develop a novel nomogram based on noninvasive liver reserve and fibrosis models, platelet-albumin-bilirubin grade (PALBI) and fibrosis-4 index (FIB-4), able to predict PHLF grade B-C. This was a single-centre retrospective study of 574 patients with HCC undergoing hepatectomy between 2014 and 2018. The independent risk factors of PHLF were screened using univariate and multivariate logistic regression analyses. Multivariate logistic regression was performed using the training set, and the nomogram was developed and visualised. The utility of the model was evaluated in a validation set using the receiver operating characteristic (ROC) curve. A total of 574 HCC patients were included (383 in the training set and 191 for the validation set) and included PHLF grade B-C complications of 14.8, 15.4, and 13.6%, respectively. Overall, cirrhosis ( P < 0.026 , OR = 2.296, 95% confidence interval (CI) 1.1.02–4.786), major hepatectomy ( P = 0.031 , OR = 2.211, 95% CI 1.077–4.542), ascites ( P = 0.014 , OR = 3.588, 95% 1.299–9.913), intraoperative blood loss ( P < 0.001 , OR = 4.683, 95% CI 2.281–9.616), PALBI score >−2.53 (, OR = 3.609, 95% CI 1.486–8.764), and FIB-4 score ≥1.45 ( P < 0.001 , OR = 5.267, 95% CI 2.077–13.351) were identified as independent risk factors associated with PHLF grade B-C in the training set. The areas under the ROC curves for the nomogram model in predicting PHLF grade B-C were significant for both the training and validation sets (0.832 vs 0.803). The proposed nomogram predicted PHLF grade B-C among patients with HCC with a better prognostic accuracy than other currently available fibrosis and noninvasive liver reserve models.

Multifocal Papillary Thyroid Carcinoma，Hashimoto's Thyroiditis and Lymph Node Metastasis：A Retrospective Cohort Study

2021 ◽  
Author(s):  
Denghui Wang ◽  
Jiang Zhu ◽  
Chang Deng ◽  
Zhixin Yang ◽  
Daixing Hu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lymph Node ◽  
Lymph Node Metastases ◽  
Protective Factor ◽  
Roc Curves ◽  
Multivariate Logistic Regression ◽  
Lateral Lymph Node ◽  
Node Metastases ◽  
Independent Risk Factors ◽  
Central Lymph

Abstract Objective: Few studies have evaluated the influence of HT and Multifocality on central lymph node metastases(CLNM) and lateral lymph node metastases(LLNM) of PTC. The present study focused on risk factors for lymph node metastasis in PTC according to the presence of HT or multifocality. Materials and methods:1413 patients were identified.The relationship between HT or multifocality and lymph nodemetastasis was analyzed by univariate and multivariate logistic regression, ROC curves were constructed to show the predictive effect of each variable on the target outcome.Results: The PTCs with HT were more likely to be multifocal.(40.0% versus 17.5%,P ＜0.001). Compared to MPTC without HT, MPTC with HT showed a lower number of metastatic CLNs and LLNs (P < 0.05). HT was identifified as an independent protective factor for CLNM in all PTC patients (OR, 0.480; 95% CI, 0.359-0.643; P< .001) and in MPTC patients (OR, 0.094; 95% CI, 0.044-0.204; P < 0.001), the multicocality was independent risk factors for CLNM(OR, 2.316; 95% CI, 1.667-3.217; P< 0.001) and LLNM(OR, 2.004; 95% CI, 1.469-2.733; P< 0.001).The variables concluded HT or MPTC were screened to predict CLNM in all patients, CLNM in patients with MPTC and LLNM in all patients (AUCs: 0.731, 0.843 and 0.696, respectively, P < 0.0001). The two type of diseases existed concurrently may result in the decrease of CLNM and LLNM, AUCs of ROC to predict CLNM and LLNM are 0.696 and 0.63(P<0.0001). Conclusions: Our study identified multifocality as an independent risk factor predicting CLNM and LLNM in PTC patients. HT was proven to be a protective factor that reduced the CLNM risk in all patients and in patients with MPTC. The existence of both type of diseases can result in the reduction of CLNM and LLNM.

Risk Factors and Neurologic Outcomes in Patients With Traumatic Brain Injury and Coagulopathy Within 72 Hours Post-operatively

2021 ◽  
Author(s):  
Tao Chang ◽  
Xigang Yan ◽  
Chao Zhao ◽  
Yufu Zhang ◽  
Bao Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Traumatic Brain Injury ◽  
Logistic Regression ◽  
Brain Injury ◽  
Multivariate Logistic Regression ◽  
Neurologic Outcomes ◽  
Post Operative Period ◽  
Duration Of Surgery ◽  
Independent Risk Factors ◽  
Time Of Admission

Abstract Background There are few studies on the development and effect of coagulopathy in patients with a traumatic brain injury (TBI) during the early post-operative period. We determined the risk factors and neurologic outcomes of in patients with a TBI and coagulopathy diagnosed by routine laboratory tests within 72 hours post-operatively. Methods The baseline characteristics, intra-operative management, and follow-up results of 462 patients with TBIs were obtained and retrospectively analyzed by multivariate logistic regression from January 2015 to June 2019. Coagulopathy was defined as an activated partial thromboplastin time > 40 seconds, international normalized ratio >1.4, or a platelet count < 100×109 /L.Results Multivariate logistic regression analysis revealed that the Glasgow Coma Scale (GCS) at the time of admission, Injury Severity Score (ISS) at the time of admission, pupil mydriasis, duration of surgery, intra-operative blood loss, and intra-operative crystalloid resuscitation were independent risk factors for patients who developed a coagulopathy post-operatively. There were statistical differences in mortality (p = 0.049), the Glasgow Outcome Scale-Extended (GCS-E; p = 0.024), and the modified Rankin Scale (p = 0.043) between patients with and without coagulopathy 1 week after surgery. Coagulopathy within 72 h after surgery revealed a trend for higher mortality at 1 week (66.7%), 3 months (71.4%), and 6 months (76.2%). Furthermore, coagulopathy and contusion expansion in the early post-operative period were independent risk factors for TBI mortality after surgery. Intra-operative crystalloid resuscitation had a substantial diagnostic accuracy in predicting coagulopathy within 72 h post-operatively (area under the curve [AUC] = 0.972).Conclusion Coagulopathy within 72 h post-operatively in patients with a TBI predicted worse disease progression and unfavorable neurologic outcomes. Hence, we should take practical and reasonable measures to manage these risk factors, which may protect patients with a TBI from post-operative coagulopathy.

Middle Cerebral Artery-to-Uterine Artery Pulsatility Index Ratio Independently Predicts Adverse Perinatal Outcome in Pregnancies at Term

2020 ◽  
Author(s):  
Sufen Zhou ◽  
Hongyan Guo ◽  
Heng Liu ◽  
Mingqun Li
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Middle Cerebral Artery ◽  
Perinatal Outcome ◽  
Pulsatility Index ◽  
Uterine Artery ◽  
Regression Analyses ◽  
Multivariate Logistic Regression ◽  
Adverse Perinatal Outcome ◽  
Independent Risk Factors

Abstract Background: This study aimed to investigate potential predictors, including cerebroplacental ratio (CPR), middle cerebral artery (MCA)/uterine artery pulsatility index (PI) ratio, for adverse perinatal outcome in pregnancies at term.Methods: This was an observational, prospective study of recruited pregnancies at term. An adverse perinatal outcome was set as the primary observational endpoint. The receiver operating characteristic (ROC) curve was plotted to investigate the predictive and cut-off values of risk factors for adverse perinatal outcome. Independent risk factors (maternal, neonatal, prenatal ultrasound and Doppler variables) for adverse perinatal outcome were evaluated by the univariate and multivariate logistic regression analyses.Results: A total of 392 pregnancies at term were included and 19.4% of them had suffered adverse perinatal outcome. CPR (OR: 0.42, 95%CI: 0.20-0.93, P=0.032) and MCA/uterine artery PI ratio (OR: 0.25, 95%CI: 0.16-0.42, P=0.032) were two independent risk factors for adverse perinatal outcome by univariate and multivariate logistic regression analyses.Conclusions: MCA/uterine artery PI ratio is a good predictor of adverse perinatal outcome in pregnancies at term.

scholarly journals In-hospital gastrointestinal bleeding in patients with acute myocardial infarction: incidence, outcomes and risk factors analysis from China Acute Myocardial Infarction Registry

BMJ Open ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. e044117
Author(s):  
Wence Shi ◽  
Xiaoxue Fan ◽  
Jingang Yang ◽  
Lin Ni ◽  
Shuhong Su ◽  
...  
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Logistic Regression ◽  
Gastrointestinal Bleeding ◽  
Secondary Outcome ◽  
Multivariate Logistic Regression ◽  
Independent Risk Factors ◽  
Receptor Inhibitor

ObjectiveTo investigate the incidence of gastrointestinal bleeding (GIB) in patients with acute myocardial infarction (AMI), clarify the association between adverse clinical outcomes and GIB and identify risk factors for in-hospital GIB after AMI.DesignRetrospective cohort study.Setting108 hospitals across three levels in China.ParticipantsFrom 1 January 2013 to 31 August 2014, after excluding 2659 patients because of incorrect age and missing GIB data, 23 794 patients with AMI from 108 hospitals enrolled in the China Acute Myocardial Infarction Registry were divided into GIB-positive (n=282) and GIB-negative (n=23 512) groups and were compared.Primary and secondary outcome measuresMajor adverse cardiovascular and cerebrovascular events (MACCEs) are a composite of all-cause death, reinfarction and stroke. The association between GIB and endpoints was examined using multivariate logistic regression and Cox proportional hazards models. Independent risk factors associated with GIB were identified using multivariate logistic regression analysis.ResultsThe incidence of in-hospital GIB in patients with AMI was 1.19%. GIB was significantly associated with an increased risk of MACCEs both in-hospital (OR 2.314; p<0.001) and at 2-year follow-up (HR 1.407; p=0.0008). Glycoprotein IIb/IIIa (GPIIb/IIIa) receptor inhibitor, percutaneous coronary intervention (PCI) and thrombolysis were novel independent risk factors for GIB identified in the Chinese AMI population (p<0.05).ConclusionsGIB is associated with both in-hospital and follow-up MACCEs. Gastrointestinal prophylactic treatment should be administered to patients with AMI who receive primary PCI, thrombolytic therapy or GPIIb/IIIa receptor inhibitor.Trial registration numberNCT01874691.

scholarly journals Incidence and risk factors for hypoglycemia in patients with hepatocellular carcinoma

2021 ◽  
Author(s):  
XiaoJing Zheng ◽  
Hong-Hong Yan ◽  
Bin Gan ◽  
Xiao-Ting Qiu ◽  
Jie Qiu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hepatocellular Carcinoma ◽  
Logistic Regression ◽  
Hba1c Level ◽  
Glycated Hemoglobin ◽  
Multivariate Logistic Regression Analysis ◽  
Cancer Center ◽  
Regression Analyses ◽  
Multivariate Logistic Regression ◽  
Factors Associated

Abstract AimTo evaluate the incidence and risk factors for hypoglycemia in patients with hepatocellular carcinoma (HCC).MethodsWe collected and analyzed the clinical data of patients with HCC in our cancer center between April 2020 and June 2021. Univariate and multivariate logistic regression analyses were performed to identify the risk factors associated with hypoglycemia.ResultsThe incidence rate of hypoglycemia in patients with HCC was 28.9% (67/232). Multivariate logistic regression analysis showed a significant association between hypoglycemia and Child-Pugh grade C (odds ratio [OR]=7.3, 95% confidence interval [CI] 2.28–23.31, p=0.001), alpha-fetoprotein (AFP) level (OR=1.000035, 95% CI 1.000007–1.000063, p=0.015), and glycated hemoglobin (HbA1c) level (OR=0.46, 95% CI 0.29–0.73, p=0.001).ConclusionChild-Pugh stage and HbA1c and AFP levels were associated with hypoglycemia in patients with HCC. Our study suggests that these three factors should be comprehensively considered when estimating the risk of hypoglycemia in these patients, and the diagnosis, treatment, and nursing plan should be adjusted in time to reduce the incidence of hypoglycemia.

scholarly journals Nomogram for Predicting Persistent Organ Failure with Acute Pancreatitis in Pregnancy

2022 ◽  
Author(s):  
Chengcheng Sheng ◽  
Zongxu Xu ◽  
Jun Wang
Keyword(s):  
Risk Factors ◽  
Acute Pancreatitis ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Organ Failure ◽  
Multivariate Logistic Regression Analysis ◽  
Concordance Index ◽  
Multivariate Logistic Regression ◽  
Independent Risk Factors ◽  
In Pregnancy

Abstract Background: Acute pancreatitis in pregnancy (APIP) with persistent organ failure (POF) poses a high risk of death for mother and fetus. This study sought to create a nomogram model for early prediction of POF with APIP patients.Methods: We conducted a cross-sectional study on APIP patients with organ failure (OF) between January 2012 and March 2021 in a university hospital. 131 patients were collected. Their clinical courses and pregnancy outcomes were obtained. Risk factors for POF were identified by univariate and multivariate logistic regression analysis. Prediction models with POF were built and nomogram was plotted. The performance of the nomogram was evaluated by using a bootstrapped-concordance index and calibration plots.Results: Hypertriglyceridemia was the most common etiology in this group of APIP patients, which accounted for 50% of transient organ failure (TOF) and 72.3% of POF. All in-hospital maternal death was in the POF group (P<0.05), which also had a significantly higher perinatal mortality rate than the TOF group (P<0.05). Univariate and multivariate logistic regression analysis determined that lactate dehydrogenase, triglycerides, serum creatinine, and procalcitonin were independent risk factors for predicting POF in APIP. A nomogram for POF was created by using the four indicators. The area under the curve was 0.875 (95% confidence interval 0.80–0.95). The nomogram had a bootstrapped-concordance index of 0.85 and was well-calibrated.Conclusions: Hypertriglyceridemia was the leading cause of organ failure-related APIP. Lactate dehydrogenase, triglycerides, serum creatinine, and procalcitonin were the independent risk factors of POF in APIP. Our nomogram model showed an effective prediction of POF with the four indicators in APIP patients.

scholarly journals Risk Factors for Mortality in 220 Patients With COVID-19 in Wuhan, China: A Single-Center, Retrospective Study

2020 ◽  
pp. 014556132097260
Author(s):  
Shuliang Zhou ◽  
Sulin Mi ◽  
Shuilian Luo ◽  
Ying Wang ◽  
Bin Ren ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Respiratory Rate ◽  
Sofa Score ◽  
Laboratory Data ◽  
Older Age ◽  
Univariable Analysis ◽  
Multivariate Logistic Regression ◽  
Failure Assessment ◽  
Independent Risk Factors

Background: An outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 infection occurred in Wuhan, China, in December 2019. To date, the analysis of fatal cases and the risk factors for death have rarely been reported. Methods: In this study, 220 adult patients with confirmed and suspected COVID-19 were enrolled. Clinical characteristics, laboratory data, treatments, and complications were compared between 168 survivors and 52 nonsurvivors. Univariable analysis and multivariable logistic regression were used to investigate the risk factors for mortality. Results: A total of 220 patients (168 were discharged and 52 died in the hospital) were enrolled in the study. The median age of all patients was 59.5 (47.0-69.0) years, and the median age of patients who died was significantly older than that of patients who survived (70.5 vs 56.0 years, respectively; P < .001). According to multivariate logistic regression, older age (odds ratio: 1.09, 95% CI: 1.03-1.15; P = .001), initial Sequential Organ Failure Assessment (SOFA) score >2 (37.4, 9.4-148.0; P = .011), and respiratory rate >24 per minute (10.89, 1.47-80.67; P = .019) were independent risk factors for mortality. Conclusion: Clinical and laboratory parameters predicting poor prognosis including older age, baseline SOFA score >2, and respiratory rate >24 per minute were identified.

scholarly journals Risk factors for peritoneal dialysis–associated peritonitis

2018 ◽  
Vol 16 ◽  
pp. 205873921877224
Author(s):  
Hongyue Wang ◽  
Xiangtuo Wang ◽  
Haichuan Dou ◽  
Chenhao Li ◽  
Mingji Cui ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Peritoneal Dialysis ◽  
Serum Albumin ◽  
Multivariate Logistic Regression Analysis ◽  
Roc Curves ◽  
Multivariate Logistic Regression Model ◽  
Phosphorus Concentration ◽  
Multivariate Logistic Regression ◽  
Gram Positive

The purpose of this study was to summarize the pathogens that cause peritoneal dialysis (PD)-associated peritonitis and to identify risk factors for PD-associated peritonitis. This retrospective study included 115 end-stage renal disease (ESRD) patients receiving PD therapy. Patients were categorized into two groups: peritonitis group (n = 41) and non-peritonitis group (n = 74). Clinical data and laboratory tests were collected from medical records. The multivariate logistic regression model was used to evaluate associations between PD-associated peritonitis and potential risk factors. PD-associated peritonitis occurred 54 times in 41 patients. The most frequently identified pathogen was Gram-positive cocci (57.78%). Multivariate logistic regression analysis showed that serum albumin (β = –0.208, P < 0.001), blood phosphorus concentration (β = –1.732, P = 0.001), gastrointestinal disorders (β = 1.624, P = 0.043), and use of calcitriol (β = –2.239, P = 0.048) were significantly correlated with PD-associated peritonitis. Receiver operating characteristic (ROC) curves showed that the areas under the curve were 0.832 for serum albumin and 0.700 for blood phosphorus concentration with optimal cut-off values of 29.1 g/L for serum albumin and 1.795 mmol/L for blood phosphorus concentration. Gram-positive coccus is the major pathogen responsible for PD-associated peritonitis. Serum albumin <29.1 g/L, blood phosphorus concentration <1.795 mmol/L, and intestinal disorders are risk factors for PD-associated peritonitis, whereas the use of calcitriol can reduce the risk of PD-associated peritonitis.

Development of a prediction model for 1-year poor prognosis in patients with acute ischemic stroke

2019 ◽  
Vol 67 (6) ◽  
pp. 957-963 ◽  
Author(s):  
Xia Ling ◽  
Bo Shen ◽  
Kangzhi Li ◽  
Lihong Si ◽  
Xu Yang
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Ischemic Stroke ◽  
Prediction Model ◽  
Acute Ischemic Stroke ◽  
Poor Prognosis ◽  
Multivariate Logistic Regression ◽  
Lemeshow Test ◽  
Independent Risk Factors ◽  
Auc Value

The goals of this study were to develop a new prediction model to predict 1-year poor prognosis (death or modified Rankin scale score of ≥3) in patients with acute ischemic stroke (AIS) and to compare the performance of the new prediction model with other prediction scales. Baseline data of 772 patients with AIS were collected, and univariate and multivariate logistic regression analyses were performed to identify independent risk factors for 1-year poor prognosis in patients with AIS. The area under the receiver operating characteristics curve (AUC) value of the new prediction model and the THRIVE, iScore and ASTRAL scores was compared. The Hosmer-Lemeshow test was used to assess the goodness of fit of the model. We identified 196 (25.4%) patients with poor prognosis at 1-year follow-up, and of these 68 (68/196, 34.7%) had died. Multivariate logistic regression and receiver operating characteristic curve analyses showed that age ≥70 years, consciousness (lethargy or coma), history of stroke or transient ischemic attack, cancer, abnormal fasting blood glucose levels ≥7.0 mmol/L, and National Institutes of Health Stroke Scale score were independent risk factors for 1-year poor prognosis in patients with AIS. Scores were assigned for each variable by rounding off β coefficient to the integer score, and a new prediction model with a maximum total score of 9 points was developed. The AUC value of the new prediction model was higher than the THRIVE score (p<0.05). The χ2 value for the Hosmer-Lemeshow test was 7.337 (p>0.05), suggesting that the prediction model had a good fit. The new prediction model can accurately predict 1-year poor prognosis in Chinese patients with AIS.

scholarly journals Risk Factors for Maternal and Fetal Mortality in Acute Fatty Liver of Pregnancy and New Predictive Models

2021 ◽  
Vol 8 ◽  
Author(s):  
Zhaoli Meng ◽  
Wei Fang ◽  
Mei Meng ◽  
Jicheng Zhang ◽  
Qizhi Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Maternal Mortality ◽  
Predictive Models ◽  
Multivariate Logistic Regression Analysis ◽  
Fetal Mortality ◽  
Multivariate Logistic Regression ◽  
Acute Fatty Liver ◽  
Independent Risk Factors

Acute fatty liver of pregnancy (AFLP) is a rare but potentially life-threatening hepatic disorder that leads to considerable maternal and fetal mortality. To explore the risk factors for maternal and fetal mortality in AFLP and develop new predictive models, through this retrospective study, we analyzed the demographic characteristics, clinical symptoms, and laboratory findings of 106 patients with AFLP who were admitted to Shandong Provincial Hospital. Risk factors for maternal and fetal mortality were analyzed by univariate and multivariate logistic regression analysis. The new models based on the multivariate logistic regression analysis and the model for end-stage liver disease (MELD) were tested in AFLP. The receiver operating characteristic curve (ROC) was applied to compare the predictive efficiency, sensitivity, and specificity of the two models. Prenatal nausea (p = 0.037), prolonged prothrombin time (p = 0.003), and elevated serum creatinine (p = 0.003) were independent risk factors for maternal mortality. The ROC curve showed that the area under the curve (AUC) of the MELD was 0.948, with a sensitivity of 100% and a specificity of 83.3%. The AUC of the new model for maternal mortality was 0.926, with a sensitivity of 90% and a specificity of 94.8%. Hepatic encephalopathy (p = 0.016) and thrombocytopenia (p = 0.001) were independent risk factors for fetal mortality. Using the ROC curve, the AUC of the MELD was 0.694, yielding a sensitivity of 68.8% and a specificity of 64.4%. The AUC of the new model for fetal mortality was 0.893, yielding a sensitivity of 100% and a specificity of 73.3%. Both the new predictive model for maternal mortality and the MELD showed good predictive efficacy for maternal mortality in patients with AFLP (AUC = 0.926 and 0.948, respectively), and the new predictive model for fetal mortality was superior to the MELD in predicting fetal mortality (AUC = 0.893 and 0.694, respectively). The two new predictive models were more readily available, less expensive, and easier to implement clinically, especially in low-income countries.

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