Biomaterial Database

[Predictive value of ventilatory indices in elderly subjects]. 1990

W Jedrychowski, and E Flak, and E Mróz, and J Cecek, and S Sek

Zakładau Epidemiologii Instytutu Med. Społ. AM w Krakowie.

Epidemiological studies of Kraków citizens enabled to calculate spirometric predictive values of elderly subjects. The study group was composed of 341 males and 843 females, aged 65-89 years. In every subject anthropomorphic and spirometric (FVC, FEV1.0, FEV0.5) calculations were carried out. Using the multiple regression analysis predictive indices of normal spirometric values were calculated. Monograms were also made, allowing easy access to normal values.

UI	MeSH Term	Description	Entries
D008297	Male		Males
D011044	Poland	A country in central Europe, east of Germany. The capital is Warsaw.	Polish People's Republic,Republic of Poland
D011237	Predictive Value of Tests	In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.	Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D012016	Reference Values	The range or frequency distribution of a measurement in a population (of organisms, organs or things) that has not been selected for the presence of disease or abnormality.	Normal Range,Normal Values,Reference Ranges,Normal Ranges,Normal Value,Range, Normal,Range, Reference,Ranges, Normal,Ranges, Reference,Reference Range,Reference Value,Value, Normal,Value, Reference,Values, Normal,Values, Reference
D012044	Regression Analysis	Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.	Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D012129	Respiratory Function Tests	Measurement of the various processes involved in the act of respiration: inspiration, expiration, oxygen and carbon dioxide exchange, lung volume and compliance, etc.	Lung Function Tests,Pulmonary Function Tests,Function Test, Pulmonary,Function Tests, Pulmonary,Pulmonary Function Test,Test, Pulmonary Function,Tests, Pulmonary Function,Function Test, Lung,Function Test, Respiratory,Function Tests, Lung,Function Tests, Respiratory,Lung Function Test,Respiratory Function Test,Test, Lung Function,Test, Respiratory Function,Tests, Lung Function,Tests, Respiratory Function
D005260	Female		Females
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000368	Aged	A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available.	Elderly
D000369	Aged, 80 and over	Persons 80 years of age and older.	Oldest Old