Metabolic dysfunction-associated steatotic liver disease:The question of long-term high-normal alanine aminotransferase as a screening test

The growing prevalence of metabolic dysfunction-associated steatotic liver disease(MASLD)is being driven by the obesity epidemic.The quest for solutions continues particularly with regard to early detection.This editorial comments on the utility of long-term high-normal alanine aminotransferase(ALT)in screening for MASLD.Chen et al found that new onset MASLD can be detected by repetitively high normal ALT.Implicit in this concept is the question of what should be the accepted upper limit of normal(ULN)for ALT.It was previously set at 40 IU/L based on studies that included people with subclinical liver disease but the new consensus is 30/19 U/L in healthy males/females.Thus,when Chen et al defines the ULN as 40 U/L,others may view it as excessively high.It is important to recognize the variables affecting ULN e.g.instrumentation,diurnal variations,exercise and ageing.These variables matter when the distinctions are subtle e.g.normal vs high-normal.In this regard,the utility of long-term high normal ALT as a disease marker could be enhanced by combining it with other biomarkers,imaging and MASLD genetics to create machine learning classifiers.All in all,Chen et al’s work on long-term high normal ALT as a marker of new-onset MASLD deserves merit.

CLASSICAL LIMITS FOR THE COEFFICIENT OF VARIATION FOR THE NORMAL DISTRIBUTION

The exact classical limits for the coefficient of variation c for the normal distribution are derived. The hand-calculating approximated classical limits for c having high accuracy are given to meet practical engineering needs. Using Odeh and Owen's computational method and Brent's algorithm, the tables for the r-upper exact classical limits of coefficient of variation for normal distribution are calculated for the different confidence coefficient y, the sample size n=1(1)30,40,60,120, the sample coefficient of variation c=0.01(0.01)0.20. It is shown that if n<8,c<0.20, then the V -upper exact classical limits cu for c are slightly higher than the exact fiducial limits cu,F for c if. n>8, c<0.02,then cu-cu,f<5x10-6

Classical regression equations of spirometric parameters are not applicable for diagnosing spirometric abnormalities in adipotic adults

The prevalence of overweighing and obese adults (defined as "adipotic" adults),has markedly increased over the world. A remarkable increase in the adipotic population urgently needs developing the regression equations for predicting spirometric parameters (SPs), which are specifically applicable to adipotic adults.Unfortunately, however, the reliable equations suitable for adipotic adults have not been reported to date. Recently, Yamaguchi et al have proposed the quantitative method to estimate the effects of adiposity on deciding the SPs incorporating with age-specific contributions of various explanatory,independent variables such as age (A), standing height (H), body weight (BW),and fat fraction of body mass(F). Extending the method proposed by Yamaguchi et al, we attempted to elaborate the novel regression equations applicable for diagnosing the spirometric abnormality in adipotic adults. For accomplishing this purpose, never-smoking, adipotic adults with body mass index (BMI) over 25 kg/m^2 and no respiratory illness were recruited from the general population in Japan (n = 3696, including men: 1890 and women: 1806). Introducing the four explanatory variables of A, H, BW, and F, gender-specific and age-dependent regression equations that allowed for prescribing the SPs in adipotic adults were constructed. Comparing the results obtained for non-adipotic adults (i.e., those with normal BMI), the negative or positive impact of height on SPs was preserved in adipotic adults, as well. However, the negative impact of age on SPs was blunted in adipotic men and the positive effect of BW on SPs was impeded in adipotic men and women. The fat fraction of body mass-elicited negative impact on SPs vanished in adipotic women. These results indicate that the regression equations of SPs for adipotic adults differ significantly from those for nonadipotic adults, leading to the conclusion that the regression equations for nonadipotic adults should not be used while judging the spirometric abnormalities in adipotic adults.

Predicted lower limit of normal reduces misclassification risk of airflow limitation in asymptomatic elderly never-smokers

Background It remains controversial what better defines abnormal lung function at the extremes of age. This study aimed to establish new spirometric reference equations for residents in Jinan and compare the most accepted two spirometric definitions of chronic obstructive pulmonary disease （COPD）--a fixed post-bronchodilator ratio of forced expiratory volume in one second to forced vital capacity （FEVJFVC） below 70% vs. FEV1/FVC 〈lower limit of normal （LLN）-in an elderly population （age 〉60 years）. Methods Among 10 002 cases, only never-smokers who had no respiratory symptoms or diagnoses of cardio- pulmonary diseases and whose lung function measurements strictly followed the American Thoracic Society guidelines, were included in the statistical analysis. For each gender, prediction equations of FEV1, FVC, FEV1/FVC and corresponding LLN values were developed using multiple regression models. Results In this cross-sectional study, spirometric reference values were statistically derived from a sample of 1328 healthy never-smokers （672 males, 656 females）, age 56-84 years. As expected, age and height were the main predictors for all lung function parameters. Using the two spirometric definitions, the number of pulmonary function test results interpreted as obstructed varied markedly in the elderly population for both genders （males： X2=19.59, P 〈0.01; females： X2=5.67, P=0.017）. Conclusions The Global Initiative for Chronic Obstructive Lung Disease （GOLD） criterion probably leads to over- diagnosis in asymptomatic elderly never-smokers. Our study suggests that the predicted LLN values will reduce the misclassification risk instead. However, cohort studies are urgently needed for clinical validation.