Retrospective Cohort
Retrospective Cohort - Related Videos
03:05
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2025
This protocol details the acupuncture procedures for patients with overweight complicated by hyperlipidemia and certifies the influence of emotional factors on therapeutic efficacy based on metrics including BMI, cholesterol, and triglyceride levels.
08:53
Preparation of Single-cohort Colonies and Hormone Treatment of Worker Honeybees to Analyze Physiology Associated with Role and/or Endocrine System
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Cited by 5 •
2016
Here we describe our detailed protocol for the preparation of single-cohort honeybee colonies – a useful tool for analyzing the role-associated worker physiology. We also describe detailed protocols for treating workers with juvenile hormone and ecdysone to evaluate the involvement of these hormones in the regulation of worker behavior and/or physiology.
09:36
Standardization of Basket Use in Sialendoscopy: A Ten-Year Retrospective Study
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2025
We present the standardization of the basket use in sialendoscopy for obstructive sialolithiasis in a consecutive ten-year series of patients with obstructive salivary gland, describing localization, stone evaluation, size estimation, choosing basket type, and choosing approach technique (Frontal, Side-to-Side, Back-to-Forward) to achieve a high success rate in its removal.
05:32
Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
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Cited by 2 •
2025
We provide a comprehensive description of the intrinsic retrospective cardiac gating method of the CrumpCAT, a prototype small-animal X-ray computed tomography (CT) scanner designed and constructed at our research institution.
05:53
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Cited by 2 •
2018
Identification of genetic variants contributing to complex human disease allows us to identify novel mechanisms. Here, we demonstrate a multiplex genotyping approach to candidate genes or gene pathway analysis that maximizes the coverage at low cost and is amenable to cohort-based studies.
FAQs
The exposure or characteristic must be identified from records that precede the outcome assessment. This ordering allows researchers to examine whether later outcomes differ between groups defined by the earlier condition, treatment, or risk factor. Although temporality supports interpretation of an association, it does not by itself establish causation because the study remains observational and may contain confounding or selection bias.
Confounding can make an observed outcome difference reflect another factor associated with both the exposure and the outcome. Statistical analysis therefore needs careful control of relevant differences between exposed and unexposed cohorts. Without that control, incidence, risk ratios, or hazard ratios may describe a mixture of the exposure association and the effects of other characteristics recorded in the historical data.
Incomplete or inaccurate historical records can affect exposure classification, cohort eligibility, outcome measurement, or follow-up status. These problems may reduce the reliability of comparisons and can distort estimated associations when information is missing differently across groups. Reviewing data quality and acknowledging limitations are therefore essential when interpreting results from a retrospective cohort.
Incidence summarizes how outcomes occur during the defined follow-up period, while risk ratios compare outcome risk between the exposed and unexposed cohorts. Hazard ratios are another way to compare outcome occurrence over follow-up. Together, these measures quantify associations, but their meaning depends on accurate group classification, suitable follow-up information, and consideration of confounding.
Researchers first establish eligibility from historical records, define the exposure-based cohorts, and specify the outcome and follow-up period. They then assess outcomes in each group and calculate an appropriate comparative measure, such as incidence, a risk ratio, or a hazard ratio. Finally, they examine potential confounding, selection bias, and missing data before interpreting the association.
This approach is useful when relevant records already exist and the outcomes of interest have occurred over a long period. It can evaluate associations involving treatments, risk factors, and disease without waiting for future outcomes to develop. Its efficiency is particularly valuable when a prospective study would require extended follow-up, provided the historical data are sufficiently complete and accurate.
An association indicates that outcome occurrence differed between groups defined by the past exposure or characteristic during the selected follow-up period. Interpretation should also consider the quality of the records, how participants entered the cohorts, missing information, and uncontrolled confounding. These limitations determine how confidently the statistical result can be connected to the exposure rather than to other differences between groups.