| Background and objective:Nutritional support is an important means of treatment for patients with severe diseases,but their metabolism is complex.On the micro level,the activation of various catabolic hormones and the changes of related metabolic substrates lead to the changes of metabolic state,which is manifested as the changes of energy consumption on the macro level.This change is not only reflected in the obvious difference in energy consumption compared with normal people,but also in the different stages of the disease,the state of energy metabolism is not the same.There are many factors affecting the metabolism of patients,including age,gender,weight,body temperature,disease type and so on.This makes it difficult to assess energy expenditure.There are two main methods for energy expenditure assessment in clinical practice: indirect calorimetry and predictive equation.Indirect calorimetry is considered as the gold standard of energy consumption measurement.Its principle is to calculate the amount of energy consumption by measuring the amount of oxygen and carbon dioxide consumed by patients.However,due to the technical conditions of the metabolic vehicle itself,its comprehensive use in clinical practice is limited.For example,when the oxygen concentration of the patient is higher than 60% and the value of PEEP supported by the ventilator is too high,indirect calorimetry will cause large errors.In this case,predictive equations are widely used.Different predictive equations were derived from different groups,including healthy people,patients with chronic diseases,and patients with severe diseases.In clinical practice,many predictive equations have been used for energy consumption assessment,but there are some problems.Several studies have shown that there are problems in the accuracy of prediction equations,and none of them can accurately reflect the energy consumption of patients.This study mainly discusses :1.The accuracy of "Penn State equation 2003" in the assessment of energy metabolism in the early stage of mechanical ventilation patients;2.Whether some clinical factors have an impact on the early energy metabolism of patients with mechanical ventilation;3.Whether the early energy metabolism state of patients with mechanical ventilation is related to the clinical outcome.Part ?: To explore the accuracy of "Penn State equation 2003" in the early assessment of energy metabolism in patients with mechanical ventilation42 mechanical ventilation patients admitted to intensive care unit(ICU)of Shanghai changzheng hospital from January 2018 to June 2018 were selected.Indirect calorimetry(metabolic vehicle)was used to measure the daily energy consumption of the enrolled patients in the first 3 days."Penn State equation 2003" was selected to calculate the energy consumption of the enrolled patients,which was the predicted value pREE1.The results of metabolic vehicle measurements were used as the gold standard to evaluate whether the predictive equation was suitable for early energy assessment in patients with mechanical ventilation.Results : 42 patients were included,including 31 males and 11 females.Average age 52.14±15.96 years.Comparing the predicted value of "Penn State equation 2003" with the actual measured value of the metabolic vehicle,pREE1 of "Penn State equation 2003" were(1876.58±234.04)kcal and mREE were(1687.47±401.51)kcal,(pREE1-mREE)wwere 189.1±301.46 kcal.The consistency of the the 95% confidence interval(97.62%)and in the± 10% mREE range(23.8%).Part ?: To explore related factors affecting early metabolic status in patients with severe mechanical ventilationMethods : Forty-two mechanical ventilation patients admitted to intensive care unit(ICU)of Shanghai changzheng hospital from January 2018 to June 2018 were selected.Indirect calorimetry(metabolic vehicle)was used to measure the daily energy consumption of the enrolled patients in the first 3 days."Penn State equation 2003" was selected to calculate the energy consumption of the enrolled patients,which was the predicted value pREE1.Secondly,according to the ratio of the measured energy consumption mREE of the patients and the predicted energy consumption pREE2(h-b equation)of healthy healthy people of the same age,height and weight,the enrolled patients were divided into hypermetabolites(mREE/pREE2 1.1)and non-hypermetabolites(mREE/pREE2 < 1.1).Age,gender,height,weight,CRP,leukocyte,d-dimer,fibrinogen,total bilirubin,albumin,creatinine,SOFA score,APACHEII score,nutritional support level(actual energy supply/actual energy consumption),and minute ventilation were compared between the two groups.Results : 42 patients were included,including 31 males and 11 females.Average age 52.14±15.96 years.Among them,18(42.86%)were in the hypermetabolites group,and 24(57.14%)were in the non-hypermetabolites group.First,single factor correlation analysis between the 2 group were be used,the p value of SOFA score and APACHEII scores is 0.031 and 0.021,the others are greater than 0.05,including age,gender,height,weight,nutritional support level,CRP,WBC,D-dimer,fibrinogen,total bilirubin,albumin,creatinine.Part ?: To investigate the correlation between early energy metabolism and clinical outcomes in patients with mechanical ventilation.Methods:According to the different 60 day clinical outcomes,42 patients were divided into survival group and death group,the comparison between the 2 groups nutrition support level,the actual energy consumption/ predicted energy consumption(H-B)equation,minute ventilation,SOFA score and APACHEII scores,CRP,WBC,RBC,D-dimer,fibrinogen,total bilirubin,albumin,creatinine,such as whether there are differences,the single factor analysis first,in according to the statistical results,select line value is less than 0.05 the logistic regression analysis,To investigate whether energy metabolism is an independent risk factor for prognosis of patients with mechanical ventilation.Results : After univariate analysis,the p values of actual energy consumption/ predicted energy consumption(H-B),SOFA score and APACHEII score were 0.001,0.0177 and 0.049,respectively,and the p values of other indexes were greater than 0.05.Statistical results can be thought of,the prognosis of patients with mechanical ventilation,actual energy consumption values/ predicted energy consumption(H-B),SOFA score and APACHEII scores related,line of statistically significant differences in factor logistic regression analysis,the results suggest energy consumption values/ predicted energy consumption(H-B)index is less than 0.05,the OR value is greater than 1,so the energy consumption values/ predicted energy consumption(H-B)as the independent risk factors for the prognosis of patients with mechanical ventilation.SummaryNutritional support is an important part of patient treatment.Nutritional support depends on the assessment of the patient's nutritional status and energy expenditure,which is a relatively difficult part.At present,the methods of prediction equation and indirect calorimetry are mainly used in clinic.Indirect calorimetry is the gold standard for the evaluation of energy consumption,but the prediction equation is also widely used when conditions do not allow,among which "Penn State equation 2003" is the method widely adopted by patients with mechanical ventilation.In this study,the accuracy of "Penn State equation 2003" in evaluating early energy metabolism of patients with mechanical ventilation was first discussed,and the results indicated that the accuracy of "Penn State equation 2003" was 23.8%.In the influence factors of early metabolism in patients with mechanical ventilation in the study,the patients with mechanical ventilation,early metabolic state may be associated with patient SOFA score and APACHEII scores,line of logistic regression analysis of the statistical significant difference,P values were greater than 0.05,no difference statistically,prompt the above factors are not independent risk factors of high metabolic state.Finally,studies on the correlation between early energy metabolism and clinical outcomes in patients with mechanical ventilation suggest that early high metabolism in patients with mechanical ventilation is an independent risk factor for poor prognosis. |
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