What is Heterodox Economics?
The population variable has two characteristics. One is to describe the typical level of the population variable with concentrated characteristics, which is represented by the mean. The other is to describe the discrete situation of the population variable with scattered characteristics, which is the degree of variation. To represent. [1]
- Variability
- The degree of variability reflects the degree of relative dispersion. A large degree of variability indicates a large relative variability relative to the mean. Variability is often used to compare the variability of multiple sets of data with different units of measurement (such as height and weight) and the variability of multiple sets of data with very different means.
- There are many indicators that reflect the degree of variation (variability) between the overall units within the population, and can be roughly divided into three categories according to their comparison standards:
- The role of variability is: to evaluate the representativeness of the mean.
- Combined with the average index
- The calculation of the index of variability is the same as
- In order to analyze the relationship between blood glucose levels and mortality of sepsis patients and to provide reference data for the prediction of prognostic quality of patients with sepsis and adjustment of treatment strategies, researchers have adopted the following methods: 204 adult patients with sepsis According to the outcome of the patients, they were divided into the death group and the survival group. The general clinical data and differences in blood glucose levels, insulin resistance, and blood glucose variability were compared between the two groups of patients. Statistically significant factors were included in the Logistic multivariate regression analysis to explore blood glucose. Of Levels on Mortality in Sepsis Patients. Results: Among the 204 patients, 81 died and the mortality rate was 39.71%. There was no significant difference in age, gender, and primary disease between the two groups (P> 0.05). Multivariate logistic regression analysis showed that FPG, FINS, HOMA-IR, and blood glucose variability were independent risk factors affecting mortality in patients with sepsis, and HOMA- was a protective factor (P <0.05). It is concluded that an increase in blood glucose levels and blood glucose variability can increase the risk of death in patients with sepsis. Paying attention to monitoring of blood glucose levels and timely administration of insulin hypoglycemic treatment is expected to improve the quality of patients' prognosis. [5]
- In order to explore the accuracy and threshold change of stroke volume variability and pulse pressure variability in elderly general anesthesia surgery. The researchers used the following method: 40 elderly patients who planned to undergo nasal septum deviation correction under general anesthesia were continuously monitored for heart rate, mean arterial pressure, stroke output, stroke output index SVI, stroke volume after general anesthesia. Hemodynamic indexes such as variability, pulse pressure variability, etc., before the start of the operation, a volume load test was performed, the values of the above hemodynamic indexes were recorded before and after the infusion, and then the patients were divided into Two groups, namely, the response group (R group, SVI 10%) and the non-response group (NR group, SVI <10%), plot the stroke characteristics and pulse pressure variation to determine the working characteristics of the participants (ROC) curve, to determine the accuracy of the stroke volume variability and pulse pressure variability in elderly patients under general anesthesia for predicting volume status accuracy, diagnostic threshold, and the correlation between the two. Results The area under the ROC curve for stroke volume variability and pulse pressure variability for judging capacity expansion were 0.802 and 0.873, respectively. The diagnostic threshold for stroke variability was 13.5%, and the diagnostic threshold for pulse pressure variability was 14.0%. The correlation was r = 0.762 (P <0.01). It is concluded that the stroke volume variability and pulse pressure variability can accurately predict the accuracy of fluids and threshold changes during general anesthesia in the elderly. The accuracy of the prediction of the capacity status of the two is similar and positively correlated, but the diagnostic threshold of both is higher than the standard value. [6]