Salīdzināt metodes

	Pragmatiska gadījumu sērija	Sērija prospective gadījumu
Nozare	Epidemioloģija	Epidemioloģija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	Pragmatic framing formalized 1967; case series practice predates 20th century	Late 19th century onward; formalized in modern clinical epidemiology by the 1970s–1980s
Autors	Pragmatic framework: Schwartz & Lellouch (1967); case series design: longstanding clinical tradition	Evolved from clinical case reporting traditions in 19th–20th century medicine
Tips	Observational descriptive study	Observational study design
Pirmavots	Schwartz, D., & Lellouch, J. (1967). Explanatory and pragmatic attitudes in therapeutical trials. Journal of Chronic Diseases, 20(8), 637–648.	Meinert, C. L. (1996). Clinical Trials: Design, Conduct, and Analysis. Oxford University Press. ISBN: 978-0195035681
Citi nosaukumi	real-world case series, pragmatic observational case series, practice-based case series	prospective case series study, forward-looking case series, prospective uncontrolled study, prospective observational case series
Saistītās	5	5
Kopsavilkums	A pragmatic case series is an observational study that documents consecutive or purposively selected patients receiving a clinical intervention or presenting with a condition under routine, real-world practice conditions — without randomization, a control group, or the highly controlled eligibility criteria characteristic of explanatory trials. It is used to describe treatment patterns, outcomes, and adverse events as they occur in everyday clinical settings.	A prospective case series is an observational study design in which a group of patients with a particular condition, exposure, or intervention is identified in advance and followed forward in time according to a pre-specified protocol. Data on outcomes, adverse events, and clinical course are collected as they occur, yielding higher data quality and temporal clarity than retrospective designs. No control group is included, so causal inference is limited, but the design is valuable for characterizing natural disease history, early safety signals, and feasibility of new interventions.