scholarly journals A Clinical Study of AWT Measurement and Polynomial Regression Model Analysis in Critically Ill Patients

2021 ◽  
Author(s):  
Hao Tang ◽  
Dongchu Zhao ◽  
Chuan Zhang ◽  
Xiaoying Huang ◽  
Dong Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Model ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Polynomial Regression ◽  
Prognostic Indicators ◽  
Survival Group ◽  
Abdominal Hypertension ◽  
Polynomial Regression Models ◽  
Polynomial Regression Model

Abstract Objective: In this study, a new measurement device was used to measure the AWT in critically ill patients and a polynomial regression model was applied to analyze the correlation between intra-abdominal hypertension (IAH) and AWT in critically ill patients.Methods: A retrospective analysis was conducted in critically ill patients who were admitted to the Department of Critical Care Medicine of Daping Hospital of Army Medical University from August 30, 2018, to June 30, 2020. According to the intravesical pressure (IVP) on the first day of ICU admission and death within 28 days, the patients were divided into the IAH group (IVP ≥12 mmHg), the non-IAH group, the survival group and the nonsurvival group. The demographic and clinical data, prognostic indicators, AWT and IVP on days 1-7 after entering the ICU, IAH risk factors, and 28-day death risk factors were collected.Results: The AWT on the 1st and mean 7th day of the IAH group was (2.89±0.32)N/mm and (2.82±0.46) N/mm, respectively, which was higher than that of the non-IAH group [ (2.45±0.29) N/mm, (2.43±0.39) N/mm], p＜0.001. The average IVP on the 1st and mean 7th day of all patients were 12.78 (6.14, 18.99) and 11.49 (6.66, 19.43) mmHg, and the AWT on the 1st and mean 7th days were (2.75±0.38) and (2.75±0.47) N/mm, respectively, with significant differences (p< 0.0001). The polynomial regression models showed that the average AWT and IVP on the 1st and mean 7th were AWTday1=-2.450×10-3, IVP2+9.695×10-2 IVP+2.046，r=0.667（p＜0.0001），and AWTmean=-2.293×10-3, IVP2+9.273×10-2 IVP+2.081, respectively. The logistic regression analysis showed that AWTday1 2.73-2.97N/mm increased the patient's 28-day mortality risk (OR: 6.834; 95%: 1.105-42.266, p=0.010).Conclusion: There is a nonlinear correlation between AWT and IVP in critically ill patients, and a high AWT may indicate poor prognosis.

scholarly journals A Clinical Study of AWT Measurement and Polynomial Regression Model Analysis in Critically Ill patients: A Retrospective Study

2021 ◽  
Author(s):  
Hao Tang ◽  
Dongchu Zhao ◽  
Chuan Zhang ◽  
Xiaoying Huang ◽  
Dong Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Model ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Polynomial Regression ◽  
Prognostic Indicators ◽  
Survival Group ◽  
Abdominal Hypertension ◽  
Polynomial Regression Models ◽  
Polynomial Regression Model

Abstract Background：In this study, a new measurement device was used to measure the AWT in critically ill patients and a polynomial regression model was applied to analyze the correlation between intra-abdominal hypertension (IAH) and AWT in critically ill patients.Methods: A retrospective analysis was conducted in critically ill patients who were admitted to the Department of Critical Care Medicine of Daping Hospital of Army Medical University from March 13, 2019, to May 23, 2020. According to the intravesical pressure (IVP) on the first day of ICU admission and death within 28 days, the patients were divided into the IAH group (IVP ≥12 mmHg), the non-IAH group, the survival group and the nonsurvival group. The demographic and clinical data, prognostic indicators, AWT and IVP on days 1-7 after entering the ICU, IAH risk factors, and 28-day death risk factors were collected.Results: The AWT on the 1st and mean 7th day of the IAH group was (2.89±0.32)N/mm and (2.82±0.46) N/mm, respectively, which was higher than that of the non-IAH group [ (2.45±0.29) N/mm, (2.43±0.39) N/mm], p＜0.001. The average IVP on the 1st and mean 7th day of all patients were 12.78 (6.14, 18.99) and 11.49 (6.66, 19.43) mmHg, and the AWT on the 1st and mean 7th days were (2.75±0.38) and (2.75±0.47) N/mm, respectively, with significant differences (p< 0.0001). The polynomial regression models showed that the average AWT and IVP on the 1st and mean 7th were AWTday1=-2.450×10-3, IVP2+9.695×10-2 IVP+2.046，r=0.667（p＜0.0001），and AWTmean=-2.293×10-3, IVP2+9.273×10-2 IVP+2.081, respectively. The logistic regression analysis showed that AWTday1 2.73-2.97N/mm increased the patient's 28-day mortality risk (OR: 6.834; 95%: 1.105-42.266, p=0.010).Conclusion: There is a nonlinear correlation between AWT and IVP in critically ill patients, and a high AWT may indicate poor prognosis.Trial registration：ChiCTR，ChiCTR1900020562. Registered 8 January 2019，http://www.chictr.org.cn/showproj.aspx?proj=34441

scholarly journals Polynomial Regression Model Analysis of Abdominal Wall Tension and Intra-abdominal Pressure in Critically ill Patients

2021 ◽  
Author(s):  
Hao Tang ◽  
Dongchu Zhao ◽  
Chuan Zhang ◽  
Xiaoying Huang ◽  
Dong Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Model ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Polynomial Regression ◽  
Prognostic Indicators ◽  
Wall Tension ◽  
Abdominal Hypertension ◽  
Abdominal Compliance ◽  
Polynomial Regression Model

Abstract BackgroundAbdominal wall tension (AWT) plays an important role in the pathogenesis of abdominal compliance (AC). This study uses a polynomial regression model to analyze the correlation between intra-vesical pressure(IVP) and AWT in critically ill patients and provides new ideas for the diagnosis and treatment of critically ill patients with intra-abdominal hypertension（IAH）.MethodsA retrospective analysis was conducted in critically ill patients who met the inclusion criteria and were admitted to the Department of intensive care unit of Daping Hospital of Army Medical University from March 14, 2019, to May 23, 2020. According to the IVP on the first day of ICU admission and death within 28 days, the patients were divided into the IAH group (IVP ≥12 mmHg), the non-IAH group, the survival group and the nonsurvival group. The demographic and clinical data, prognostic indicators, AWT and IVP on days 1-7 after entering the ICU, IAH risk factors, and 28-day death risk factors were collected.ResultsA total of 100 patients were enrolled, with an average age of 45.59±11.4 years. There were 55 males (55%), 30 patients from departments of internal medicine (30%), 43 patients from surgery departments (43%), and 27 trauma patients (27%). In the IAH group, there were 50 patients (29 males, 58%), with an average age of 45.28±12.27 years; there were 50 patients (26 males, 52%) in the non-IAH group, with an average age of 45.90±10.58 years. The IVP on the 1st day and the average IVP within 7 days of the IAH group was 18.99（17.52，20.77）mmHg and 19.43（16.87，22.25）mmHg, respectively, which was higher than that of the non-IAH group [ 6.14（3.48，8.70）mmHg, 6.66（2.74，9.08）mmHg], p＜0.001. The AWT on the 1st day and the average AWT within 7 days of the IAH group was 2.89±0.32 N/mm and 2.82±0.46 N/mm, respectively, which was higher than that of the non-IAH group [(2.45±0.29)N/mm,(2.43±0.39)N/mm],p＜0.001.The polynomial regression models showed that the average AWT and IVP on the 1st day and within 7 days were AWTday1 = -2.450×10-3IVP2+9.695×10-2 IVP+2.046，r=0.667（p＜0.0001），and AWTmean = -2.293×10-3IVP2+9.273×10-2 IVP+2.081, respectively. The logistic regression analysis showed that AWTday1 of 2.73-2.97 N/mm increased the patient's 28-day mortality risk (OR: 6.834; 95%: 1.105-42.266, p=0.010).ConclusionsThere is a nonlinear correlation between AWT and IVP in critically ill patients, and a high AWT may indicate poor prognosis.

scholarly journals Forecasting COVID-19 cases in Algeria using logistic growth and polynomial regression models

2021 ◽  
Author(s):  
Mohamed LOUNIS ◽  
Babu Malavika
Keyword(s):  
Regression Model ◽  
Logistic Model ◽  
Polynomial Regression ◽  
Logistic Growth ◽  
The Novel ◽  
Logistic Growth Model ◽  
Polynomial Regression Models ◽  
Using Data ◽  
Novel Coronavirus ◽  
Polynomial Regression Model

Abstract The novel Coronavirus respiratory disease 2019 (COVID-19) is still expanding through the world since it started in Wuhan (China) on December 2019 reporting a number of more than 84.4 millions cases and 1.8 millions deaths on January 3rd 2021.In this work and to forecast the COVID-19 cases in Algeria, we used two models: the logistic growth model and the polynomial regression model using data of COVID-19 cases reported by the Algerian ministry of health from February 25th to December 2nd, 2020. Results showed that the polynomial regression model fitted better the data of COVID-19 in Algeria the Logistic model. The first model estimated the number of cases on January, 19th 2021 at 387673 cases. This model could help the Algerian authorities in the fighting against this disease.

scholarly journals Incidence, Risk Factors, and Outcomes of Intra-Abdominal Hypertension in Critically Ill Patients—A Prospective Multicenter Study (IROI Study)

2019 ◽  
Vol 47 (4) ◽  
pp. 535-542 ◽  
Author(s):  
Annika Reintam Blaser ◽  
Adrian Regli ◽  
Bart De Keulenaer ◽  
Edward J. Kimball ◽  
Liis Starkopf ◽  
...  
Keyword(s):  
Risk Factors ◽  
Critically Ill ◽  
Multicenter Study ◽  
Critically Ill Patients ◽  
Prospective Multicenter Study ◽  
Abdominal Hypertension ◽  
Incidence Risk

scholarly journals Etiology, incidence, and outcomes of patient–ventilator asynchrony in critically-ill patients undergoing invasive mechanical ventilation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yongfang Zhou ◽  
Steven R. Holets ◽  
Man Li ◽  
Gustavo A. Cortes-Puentes ◽  
Todd J. Meyer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mechanical Ventilation ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Invasive Mechanical Ventilation ◽  
Surgical Intensive Care ◽  
Mechanically Ventilated ◽  
History Of ◽  
Training Background ◽  
The Relationship

AbstractPatient–ventilator asynchrony (PVA) is commonly encountered during mechanical ventilation of critically ill patients. Estimates of PVA incidence vary widely. Type, risk factors, and consequences of PVA remain unclear. We aimed to measure the incidence and identify types of PVA, characterize risk factors for development, and explore the relationship between PVA and outcome among critically ill, mechanically ventilated adult patients admitted to medical, surgical, and medical-surgical intensive care units in a large academic institution staffed with varying provider training background. A single center, retrospective cohort study of all adult critically ill patients undergoing invasive mechanical ventilation for ≥ 12 h. A total of 676 patients who underwent 696 episodes of mechanical ventilation were included. Overall PVA occurred in 170 (24%) episodes. Double triggering 92(13%) was most common, followed by flow starvation 73(10%). A history of smoking, and pneumonia, sepsis, or ARDS were risk factors for overall PVA and double triggering (all P < 0.05). Compared with volume targeted ventilation, pressure targeted ventilation decreased the occurrence of events (all P < 0.01). During volume controlled synchronized intermittent mandatory ventilation and pressure targeted ventilation, ventilator settings were associated with the incidence of overall PVA. The number of overall PVA, as well as double triggering and flow starvation specifically, were associated with worse outcomes and fewer hospital-free days (all P < 0.01). Double triggering and flow starvation are the most common PVA among critically ill, mechanically ventilated patients. Overall incidence as well as double triggering and flow starvation PVA specifically, portend worse outcome.

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