Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Pragmatiskais diagnostiskās precizitātes pētījums× | Epidemioloģisks šķērsgriezuma pētījums× | |
|---|---|---|
| Nozare | Epidemioloģija | Epidemioloģija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 2000s–2010s (formalized alongside STARD reporting guidelines) | 1960s (formal codification); widely practiced since mid-20th century |
| Autors≠ | Evolved from STARD initiative (Bossuyt et al.) and pragmatic trial framework (Schwartz & Lellouch, 1967) | Classical epidemiology tradition; systematized by Brian MacMahon and Thomas Pugh (1960s) |
| Tips≠ | Observational diagnostic study design | Observational, descriptive/analytic epidemiological design |
| Pirmavots≠ | Bossuyt, P. M., et al. (2015). STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies. BMJ, 351, h5527. DOI ↗ | Kelsey, J. L., Whittemore, A. S., Evans, A. S., & Thompson, W. D. (1996). Methods in Observational Epidemiology (2nd ed.). Oxford University Press. ISBN: 978-0195080407 |
| Citi nosaukumi | real-world diagnostic accuracy study, pragmatic DAS, routine-care diagnostic study, pragmatic test evaluation | prevalence study, cross-sectional survey, transversal study, cross-sectional design |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | A pragmatic diagnostic accuracy study evaluates how well a diagnostic test performs under real-world clinical conditions — not in idealized, tightly controlled settings. Conducted within routine care workflows, it measures sensitivity, specificity, predictive values, and likelihood ratios for an index test against a reference standard, yielding accuracy estimates directly applicable to clinical practice rather than laboratory benchmarks. | A cross-sectional epidemiological study measures the exposure(s) and outcome(s) of interest simultaneously in a defined population at a single point in time (or over a short period). Because there is no follow-up, it is the most efficient observational design for estimating disease prevalence and for generating hypotheses about associations between risk factors and health outcomes. |
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