In-hospital malnutrition: indications of postoperative evolution

BACKGROUND: The question of the minimum number of Papanicolaou (Pap) smear slides that must be rescreened to draw statistically valid conclusions regarding the accuracy of screening often is raised. No method for generating answers in varying laboratory circumstances has achieved widespread application; standard statistical sample size calculations may represent such a resource. METHODS: A series of tables was constructed to display minimum required numbers of rescreens, with each table representing differing hypothetical laboratory circumstances. To use each table, assumptions must be specified in advance as to prevalence of abnormality, definition of error, baseline false-negative proportions (FNPs) of performance, and a degree of increase in FNPs that is considered a departure from baseline warranting concern, among others. RESULTS: The authors constructed four sample tables displaying minimum numbers of slides that must be rescreened in differing specified laboratory scenarios. Depending on assumed conditions and predetermined levels of satisfactory and unsatisfactory accuracy, the range of numbers is very broad (38-10,000). One example representing likely conditions indicates that 1040 slides must be reexamined; in another scenario, a sample size of 300 is sufficient. CONCLUSIONS: The minimum number of rescreened slides needed to draw statistically valid conclusions regarding Pap smear screening accuracy can be calculated using standard statistical methods. However, a number of assumptions must be detailed in advance. The authors offer this as a practical guide and a continuation of a general inquiry regarding Pap smear error rate measurement and display. The use of these tables raises at least as many questions as it answers, but still may represent a significant advance. Future efforts at further numeric characterization of aspects of Pap smear screening performance are warranted to enable rational decision making when performance is examined in the course of quality assurance, and during quality control and regulatory activities. [See editorial on pages 127-9, this issue.]