scholarly journals Association of body mass index with in-hospital major adverse outcomes in acute type A aortic dissection patients in Fujian Province, China: a retrospective study

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Lingyu Lin ◽  
Yanjuan Lin ◽  
Qiong Chen ◽  
Yanchun Peng ◽  
Sailan Li ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Aortic Dissection ◽  
Logistic Regression Analysis ◽  
Normal Weight ◽  
Adverse Outcomes ◽  
Multivariable Logistic Regression Analysis ◽  
Acute Type ◽  
Type A Aortic Dissection

Abstract Background Abnormal body mass index (BMI) has been related to a higher risk of adverse outcomes in patients undergoing cardiac surgery. However, the effects of BMI in patients with acute type A aortic dissection (AAAD) on postoperative outcomes remain unclear. This study aimed to explore the relationships between BMI and in-hospital major adverse outcomes (MAO) in AAAD patients. Methods Patients who underwent AAAD surgery at Cardiac Medical Center of Fujian Province from June 2013 to March 2020 were retrospectively evaluated. They were divided into three groups on the basis of Chinese BMI classification established by the World Health Organization: normal weight group (BMI 18.5–23.9 kg/m2), overweight group (BMI 24–27.9 kg/m2), and obese group (BMI >28 kg/m2). Patients’ baseline characteristics, preoperative, operative, and postoperative data were collected. A multivariable logistic regression analysis model was performed to identify the association between BMI and MAO in AAAD patients. Results Of 777 cases, 31.9% were normal weight, 52.5% were overweight, and 15.6% were obese. A total of 160(20.6%) patients died in-hospital. There was a significant difference between the three groups for MAO (62.9% vs 72.1% vs 77.7%, respectively, P = 0.006). The incidence of postoperative complications did not differ among the three groups, except for postoperative bleeding, and prolonged mechanical ventilation, the proportion of which were higher in the overweight and obese groups. Besides, multivariable logistic regression analysis demonstrated that a higher risk of MAO in the overweight [odds ratios (ORs):1.475, 95%CI:1.006–2.162], and obese patients (ORs:2.147, 95%CI:1.219–3.782) with reference to the normal weight patients, and age, white blood cell, prior stroke and cardiopulmonary bypass time were also associated with in-hospital MAO (P<0.05). Conclusions BMI is independently associated with higher in-hospital MAO in patients who underwent AAAD surgery.

scholarly journals Association of body mass index with in-hospital major adverse outcomes in acute type A aortic dissection patients in Fujian Province, China: a retrospective study

2021 ◽  
Author(s):  
Lingyu Lin ◽  
Yanjuan Lin ◽  
Qiong Chen ◽  
Yanchun Peng ◽  
Sailan Li ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Aortic Dissection ◽  
Logistic Regression Analysis ◽  
Normal Weight ◽  
Adverse Outcomes ◽  
Multivariable Logistic Regression Analysis ◽  
Acute Type ◽  
Type A Aortic Dissection

Abstract Background: Abnormal body mass index(BMI) has been related to a higher risk of adverse outcomes in patients undergoing cardiac surgery. However, the effects of BMI in patients with acute type A aortic dissection(AAAD) on postoperative outcomes remain unclear. This study aimed to explore the relationships between BMI and in-hospital major adverse outcomes(MAO) in AAAD patients.Methods: Patients who underwent AAAD surgery at Fujian Province Cardiac Medical Research Center from June 2013 to March 2020 were retrospectively evaluated. They were divided into three groups on the basis of Chinese BMI classification established by the World Health Organization: normal weight group(BMI 18.5-23.9 kg/m2), overweight group(BMI 24-27.9 kg/m2), and obese group(BMI ＞28kg/m2). Patients’ baseline characteristics, preoperative, operative, and postoperative data were collected. A multivariable logistic regression analysis model was performed to identify the association between BMI and MAO in AAAD patients.Results: Of 777 cases, 31.9% were normal weight, 52.5% were overweight, and 15.6% were obese. A total of 160(20.6%) patients died in-hospital. There was a significant difference between the three groups for MAO(62.9% vs 72.1% vs 77.7%, respectively; P=0.006). The incidence of postoperative complications did not differ among the three groups, except for postoperative bleeding, and prolonged mechanical ventilation, the proportion of which were higher in the overweight and obese groups. Besides, multivariable logistic regression analysis demonstrated that a higher risk of MAO in the overweight [odds ratios(ORs):1.475, 95%CI:1.006-2.162], and obese patients(ORs:2.147, 95%CI:1.219-3.782) with reference to the normal weight patients, and age, white blood cell, prior stroke and cardiopulmonary bypass time were also associated with in-hospital MAO (P＜0.05).Conclusions: BMI is independently associated with higher in-hospital MAO in patients who underwent AAAD surgery.

scholarly journals Association of Body Mass Index With Postoperative Early Adverse Outcomes in Acute Type a Aortic Dissection Patients in Fujian Province, China: A Retrospective Study

2020 ◽  
Author(s):  
Lingyu Lin ◽  
Yanjuan Lin ◽  
Qiong Chen ◽  
Yanchun Peng ◽  
Sailan Li ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Aortic Dissection ◽  
Body Mass ◽  
Logistic Regression Analysis ◽  
Adverse Outcomes ◽  
Acute Type ◽  
Obese Patients ◽  
Type A Aortic Dissection

Abstract Background: Abnormal body mass index (BMI) has been related to a higher risk of adverse perioperative outcomes in patients undergoing cardiac surgery. However, the effects of BMI in patients with acute type A aortic dissection (AAAD) on postoperative outcomes remain unclear. The aims of this study were to explore the relationships of BMI and postoperative early adverse outcomes in AAAD patientsMethods: Patients who underwent AAAD surgery at Fujian Province Cardiac Medical Research Center from June 2013 to March 2020 were retrospectively evaluated. They were divided into three groups on the basis of Chinese BMI classification established by the World Health Organization: normal group (BMI 18.5-23.9 kg/m2), overweight group (BMI 24-27.9 kg/m2), and obesity group (BMI > 28kg/m2). Preoperative, intraoperative, and postoperative data were collected. Multivariable and univariable logistic regression analysis models were performed to identify whether BMI was independently associated with postoperative adverse outcomes.Results: Of 777 cases, 31.9% were normal weight, 52.5% were overweight, and 15.6% were obese. The percentage of prolonged mechanical ventilation (44.9% vs 55.8% vs 66.1%, respectively; P<0.001) and the median duration of intensive care unit stays (8.1 vs 9.5 vs 12.0 days, respectively; P<0.001) were higher and longer in the overweight and obese group. Multivariable logistic regression analysis demonstrated that a higher risk of postoperative early adverse outcomes in the overweight (odds ratio [OR]: 2.374, 95%CI: 1.647–3.422), and obese patients (OR: 3.659, 95%CI: 2.122–6.308) with reference to the normal BMI patients, and age, heart rate, and surgery duration were also associated with postoperative early adverse outcomes (P<0.05).Conclusion: Overweight and obese patients are independently associated with higher postoperative early adverse outcomes in patients who underwent AAAD surgery.

scholarly journals The association between body mass index and severity of Coronavirus Disease 2019 (COVID-19): A cohort study

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247023
Author(s):  
Kulapong Jayanama ◽  
Sirawat Srichatrapimuk ◽  
Kanin Thammavaranucupt ◽  
Suppachok Kirdlarp ◽  
Supawadee Suppadungsuk ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cohort Study ◽  
Body Mass ◽  
Logistic Regression Analysis ◽  
Severe Pneumonia ◽  
Adverse Outcomes ◽  
Icu Stay ◽  
Underweight Patients

Objectives The coronavirus disease 2019 (COVID-19) has become a worst pandemic. The clinical characteristics vary from asymptomatic to fatal. This study aims to examine the association between body mass index (BMI) levels and the severity of COVID-19. Methods and study design A cohort study included 147 adult patients with confirmed COVID-19 were categorized into 4 groups by BMI levels on admission: <18.5 (underweight), 18.5–22.9 (normal weight), 23.0–24.9 (overweight), and ≥25.0 kg/m2 (obese). Rates of pneumonia, severe pneumonia, acute kidney injury (AKI), and ICU stay during hospitalization across BMI group was determined. Logistic regression analysis was used to determine the association between BMI and severe pneumonia. Results Of the totals, patients having a BMI <18.5, 18.5–22.9, 23.0–24.9, and ≥25.0 kg/m2 were 12.9%, 38.1%, 17.7%, and 31.3%, respectively. The rates of pneumonia and severe pneumonia tended to be higher in patients with higher BMI, whereas the rates of AKI and ICU stay were higher in patients with BMI <18.5 kg/m2 and ≥ 25 kg/m2, when compared to patients with normal BMI. After controlling for age, sex, diabetes, hypertension and dyslipidemia in the logistic regression analysis, having a BMI ≥25.0 kg/m2 was associated with higher risk of severe pneumonia (OR 4.73; 95% CI, 1.50–14.94; p = 0.003) compared to having a BMI 18.5–22.9 kg/m2. During admission, elevated hemoglobin and alanine aminotransferase levels on day 7 and 14 of illness were associated with higher BMI levels. In contrast, rising of serum creatinine levels was observed in underweight patients on days 12 and 14 of illness. Conclusions Obesity in patients with COVID-19 was associated with severe pneumonia and adverse outcomes such as AKI, transaminitis and ICU stay. Underweight patients should be closely monitored for AKI. Further studies in body composition are warranted to explore the links between adiposity and COVID-19 pathogenesis.

scholarly journals Application of The Sepsis-3 Consensus Criteria in a Geriatric Acute Care Unit: A Prospective Study

2019 ◽  
Vol 8 (3) ◽  
pp. 359 ◽  
Author(s):  
Davide Bastoni ◽  
Andrea Ticinesi ◽  
Fulvio Lauretani ◽  
Simone Calamai ◽  
Maria Catalano ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Hospital Mortality ◽  
Acute Care ◽  
Logistic Regression Analysis ◽  
Adverse Outcomes ◽  
Multivariable Logistic Regression Analysis ◽  
Predictive Capacity ◽  
Multivariable Logistic Regression ◽  
Mortality Difference

The prognostic value of quick Sepsis-related Organ Failure Assessment (qSOFA) score in geriatric patients is uncertain. We aimed to compare qSOFA vs. Systemic Inflammatory Response Syndrome (SIRS) criteria for mortality prediction in older multimorbid subjects, admitted for suspected sepsis in a geriatric ward. We prospectively enrolled 272 patients (aged 83.7 ± 7.4). At admission, qSOFA and SIRS scores were calculated. Mortality was assessed during hospital stay and three months after discharge. The predictive capacity of qSOFA and SIRS was assessed by calculating the Area Under the Receiver Operating Characteristic Curve (AUROC), through pairwise AUROC comparison, and multivariable logistic regression analysis. Both qSOFA and SIRS exhibited a poor prognostic performance (AUROCs 0.676, 95% CI 0.609–0.738, and 0.626, 95% CI 0.558–0.691 for in-hospital mortality; 0.684, 95% CI 0.614–0.748, and 0.596, 95% CI 0.558–0.691 for pooled three-month mortality, respectively). The predictive capacity of qSOFA showed no difference to that of SIRS for in-hospital mortality (difference between AUROCs 0.05, 95% CI −0.05 to 0.14, p = 0.31), but was superior for pooled three-month mortality (difference between AUROCs 0.09, 95% CI 0.01–0.17, p = 0.029). Multivariable logistic regression analysis, accounting for possible confounders, including frailty, showed that both scores were not associated with in-hospital mortality, although qSOFA, unlike SIRS, was associated with pooled three-month mortality. In conclusion, neither qSOFA nor SIRS at admission were strong predictors of mortality in a geriatric acute-care setting. Traditional geriatric measures of frailty may be more useful for predicting adverse outcomes in this setting.

Physical Activity, Overweight, and Perceptions of Neighborhood Environments Among Portuguese Girls

2006 ◽  
Vol 3 (3) ◽  
pp. 314-322 ◽  
Author(s):  
Jorge Mota ◽  
Nuno Delgado ◽  
Mariana Almeida ◽  
José Carlos Ribeiro ◽  
Maria Paula Santos
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Environmental Variables ◽  
Normal Weight ◽  
Activity Levels ◽  
Physical Activity Levels ◽  
Index 2

Background:The purpose of this study was 1) to compare physical activity levels according to body-mass index; 2) to determine which, if any, neighborhood perceived attributes were related to overweight.Methods:The sample comprised 610 girls age 14.7 ± 1.6 y. Girls were grouped into normal weight and overweight. Environmental variables and physical activity were assessed by questionnaire.Results:No significant differences were found in physical activity levels between normal weight and overweight girls. Logistic regression analysis revealed that girls who agreed that “there is so much traffic on the streets that it makes it unpleasant to walk in the neighborhood” were more likely to be overweight (OR = 1.78; 95% CI 1.10 to 2.89).Conclusion:The study found no relationship between perceptions of the environment and overweight among Portuguese girls, except for perceptions of security for walking in the neighborhood.

scholarly journals Development and Validation of a Diagnostic Model to Predict the Risk of Ischemic Liver Injury After Stanford A Aortic Dissection Surgery

2021 ◽  
Vol 8 ◽  
Author(s):  
Maomao Liu ◽  
Wen Tan ◽  
Wen Yuan ◽  
Tengke Wang ◽  
Xuran Lu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Liver Injury ◽  
Aortic Dissection ◽  
Risk Prediction ◽  
Logistic Regression Analysis ◽  
Risk Model ◽  
Multivariable Logistic Regression Analysis ◽  
Diagnostic Model ◽  
Lemeshow Test

Objective: To define the risk factors of ischemic liver injury (ILI) following Stanford A aortic dissection surgery and to propose a diagnostic model for individual risk prediction.Methods: We reviewed the clinical parameters of ILI patients who underwent cardiac surgery from Beijing Anzhen Hospital, Capital Medical University between January 1, 2015 and October 30, 2020. The data was analyzed by the use of univariable and multivariable logistic regression analysis. A risk prediction model was established and validated, which showed a favorable discriminating ability and might contribute to clinical decision-making for ILI after Stanford A aortic dissection (AAD) surgery. The discriminative ability and calibration of the diagnostic model to predict ILI were tested using C statistics, calibration plots, and clinical usefulness.Results: In total, 1,343 patients who underwent AAD surgery were included in the study. After univariable and multivariable logistic regression analysis, the following variables were incorporated in the prediction of ILI: pre-operative serum creatinine, pre-operative RBC count &lt;3.31 T/L, aortic cross-clamp time &gt;140 min, intraoperative lactic acid level, the transfusion of WRBC, atrial fibrillation within post-operative 24 h. The risk model was validated by internal sets. The model showed a robust discrimination, with an area under the receiver operating characteristic (ROC) curve of 0.718. The calibration plots for the probability of perioperative ischemic liver injury showed coherence between the predictive probability and the actual probability (Hosmer-Lemeshow test, P = 0.637). In the validation cohort, the nomogram still revealed good discrimination (C statistic = 0.727) and good calibration (Hosmer-Lemeshow test, P = 0.872). The 10-fold cross-validation of the nomogram showed that the average misdiagnosis rate was 9.95% and the lowest misdiagnosis rate was 9.81%.Conclusion: Our risk model can be used to predict the probability of ILI after AAD surgery and have the potential to assist clinicians in making treatment recommendations.

scholarly journals Prediction of successful de-cannulation of tracheostomised patients in medical intensive care units

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Chul Park ◽  
Ryoung-Eun Ko ◽  
Jinhee Jung ◽  
Soo Jin Na ◽  
Kyeongman Jeon
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Goodness Of Fit ◽  
Characteristic Curve ◽  
Multivariable Logistic Regression Analysis ◽  
Limited Data ◽  
Underlying Malignancy ◽  
Medical Intensive Care ◽  
Good Calibration

Abstract Background Limited data are available on practical predictors of successful de-cannulation among the patients who undergo tracheostomies. We evaluated factors associated with failed de-cannulations to develop a prediction model that could be easily be used at the time of weaning from MV. Methods In a retrospective cohort of 346 tracheostomised patients managed by a standardized de-cannulation program, multivariable logistic regression analysis identified variables that were independently associated with failed de-cannulation. Based on the logistic regression analysis, the new predictive scoring system for successful de-cannulation, referred to as the DECAN score, was developed and then internally validated. Results The model included age > 67 years, body mass index < 22 kg/m2, underlying malignancy, non-respiratory causes of mechanical ventilation (MV), presence of neurologic disease, vasopressor requirement, and presence of post-tracheostomy pneumonia, presence of delirium. The DECAN score was associated with good calibration (goodness-of-fit, 0.6477) and discrimination outcomes (area under the receiver operating characteristic curve 0.890, 95% CI 0.853–0.921). The optimal cut-off point for the DECAN score for the prediction of the successful de-cannulation was ≤ 5 points, and was associated with the specificities of 84.6% (95% CI 77.7–90.0) and sensitivities of 80.2% (95% CI 73.9–85.5). Conclusions The DECAN score for tracheostomised patients who are successfully weaned from prolonged MV can be computed at the time of weaning to assess the probability of de-cannulation based on readily available variables.

scholarly journals Impacts of eosinophil percentage on prognosis acute type A aortic dissection patients

2021 ◽  
Author(s):  
Yue Shao ◽  
Liu Ye ◽  
Hao-ming Shi ◽  
Xin-mei Wang ◽  
Jun Luo ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Aortic Dissection ◽  
Multivariate Regression ◽  
Medical Information ◽  
External Validation ◽  
Inflammatory Cells ◽  
Type A ◽  
Multivariate Regression Analysis ◽  
Acute Type ◽  
Type A Aortic Dissection

Abstract Background Eosinophils are pro-inflammatory cells involved in thrombosis and have been proposed as a prognosis marker in acute ischemic stroke and ST-elevation myocardial Infarction. Here, we sought to clarify the prognostic value of eosinophil percentage (EOS%) in patients with acute type A aortic dissection (AAAD). Methods We examined 183 consecutive AAAD patients. Based on the optimum cut-off value of EOS% determined by X-tile software, patients were classified into the low EOS% (EOS%≤0.1) and high EOS% groups (EOS%>0.1). We performed multivariate regression analysis and Kaplan-Meier (KM) survival curves to assess the association between EOS% and mortality. Eosinophil accumulation in aortic dissection intraluminal thrombus was confirmed using hematoxylin–eosin (H&E) staining. An external cohort from Medical Information Mart for Intensive Care IV was performed to validate the results. Results Relative to surviving patients, those who died during hospitalization had significantly lower EOS% (p=0.001) but significantly higher WBC (p=0.002) and neutrophil (p=0.001) counts. Multivariate regression analysis identified EOS% as an independent predictor of in-hospital and 1-year mortality. KM curves revealed that 1-year cumulative mortality was significantly higher in the low EOS% group, although it was mainly attributed to the higher 30-day mortality. H&E staining revealed massive infiltration of eosinophils in all 20 thrombus specimens. The external validation confirmed that relative to survivors, patients with in-hospital (p=0.010) had significantly lower EOS%. Moreover, multivariate regression analyses identified that decreased EOS% was independently significantly associated with in-hospital mortality. Conclusions Low EOS% is significantly related to increased mortality rates in AAAD patients.

scholarly journals Impact of histologic chorioamnionitis on pulmonary hypertension and respiratory outcomes in preterm infants

2018 ◽  
Vol 8 (2) ◽  
pp. 204589401876016 ◽  
Author(s):  
Sook Kyung Yum ◽  
Min-Sung Kim ◽  
Yoojin Kwun ◽  
Cheong-Jun Moon ◽  
Young-Ah Youn ◽  
...  
Keyword(s):  
Pulmonary Hypertension ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Preterm Infants ◽  
Logistic Regression Analysis ◽  
Multivariable Logistic Regression Analysis ◽  
Multivariable Logistic Regression ◽  
Histologic Chorioamnionitis ◽  
Respiratory Outcomes ◽  
Lower Birthweight

We aimed to evaluate the association between the presence of histologic chorioamnionitis (HC) and development of pulmonary hypertension (PH) during neonatal intensive care unit (NICU) stay. Data of preterm infants born at 32 weeks of gestation or less were reviewed. The development of PH and other respiratory outcomes were compared according to the presence of HC. Potential risk factors associated with the development of PH during NICU stay were used for multivariable logistic regression analysis. A total of 188 infants were enrolled: 72 in the HC group and 116 in the no HC group. The HC group infants were born at a significantly shorter gestational age and lower birthweight, with a greater proportion presenting preterm premature rupture of membrane (pPROM) > 18 h before delivery. More infants in the HC group developed pneumothorax ( P = 0.008), and moderate and severe bronchopulmonary dysplasia (BPD; P = 0.001 and P = 0.006, respectively). PH in the HC group was significantly more frequent compared to the no HC group (25.0% versus 8.6%, P = 0.002). Based on a multivariable logistic regression analysis, birthweight ( P = 0.009, odds ratio [OR] = 0.997, 95% confidence interval [CI] = 0.995–0.999), the presence of HC ( P = 0.047, OR = 2.799, 95% CI = 1.014–7.731), and duration of invasive mechanical ventilation (MV) > 14 days ( P = 0.015, OR = 8.036, 95% CI = 1.051–43.030) were significant factors. The presence of HC and prolonged invasive MV in infants with lower birthweight possibly synergistically act against preterm pulmonary outcomes and leads to the development of PH. Verification of this result and further investigation to establish effective strategies to prevent or ameliorate these adverse outcomes are needed.

Sign in / Sign up

Export Citation Format

Share Document