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Screening and Diagnostic Tests
Published in Marcello Pagano, Kimberlee Gauvreau, Heather Mattie, Principles of Biostatistics, 2022
Marcello Pagano, Kimberlee Gauvreau, Heather Mattie
Recall that the odds of an event are defined as , the probability of the event divided by 1 minus the probability of the event. Bayes' theorem allows us to calculate the probability of disease given a positive test result, and 1 minus this probability is
Critical appraisal of studies on diagnostic tests
Published in O. Ajetunmobi, Making Sense of Critical Appraisal, 2021
The ‘odds’ of an event happening are defined as the probability that the event will occur compared with the probability that the event will not occur: Odds = probability/(1 — probability).(Note: Probability = odds/(odds + 1.)Likelihood ratios are also used with multi-category or continuous results.
Death and related issues
Published in David Sales, Medical IELTS, 2020
It is helpful to be able to explain such concepts in terms that the patient may understand, for example, a mortality rate could be explained as the chance of dying from a particular condition. It’s often difficult for a patient to work out their individual risk from statistical odds and some doctors will resort to illustrative terms that attempt to put a risk in perspective such as being as rare as hens’ teeth (which don’t exist) would mean that the chance is so small that they could (virtually) ignore it.
Homogeneity test of relative risk ratios for stratified bilateral data under different algorithms
Published in Journal of Applied Statistics, 2023
Ke-Yi Mou, Chang-Xing Ma, Zhi-Ming Li
In medical clinical studies, observations from patients' paired parts (e.g. eyes, ears, and arms) are usually collected as paired data. The paired outcomes for each patient will be no, unilateral or bilateral response(s). Data from all patients can be summarized in a contingency table. The correlation between responses from paired parts should be taken into account to avoid biased or misleading results. In clinical practice, research subjects often can be distinguished by some control variables (e.g. age, gender), which contribute to stratified data. Although the questions involving treatment-by-stratum interaction are often secondary in most multi-center trials, they are still important as preparatory work for the overall and subgroup analyses. For a stratified bilateral design with two groups, the interaction can be tested by comparing different ratios across strata. If the ratios are not significantly different, the effect of stratum is negligible. Relative risk ratio, odds ratio and risk difference are often used to quantify the strength of the association. Generally, relative risk ratio is more visual than odds ratio. Walter [22] pointed out the population risks of some diseases were rather small such that risk differences between groups were less dramatic. Thus, risk relative ratio can be effectively used to study the homogeneity test in stratified bilateral data.
Rapid systematic review of respiratory rate as a vital sign of clinical deterioration in COVID-19
Published in Expert Review of Respiratory Medicine, 2022
John Tredinnick-Rowe, Rehan Symonds
Odds ratios (OR) give an indication of the likelihood of an event occurring, expressed as a proportion. It is calculated by dividing the probability of an event by the probability of the opposite, specified nonevent. In clinical trials, the nonevent would be a control group; in our paper, this represents the people that did not have an escalation in their COVID-19 severity. Depending on the paper, the event itself could be COVID-19 mortality or admission to an ICU. If the OR is greater than 1, it indicates the greater likelihood of an event happening. Whereas if the OR is negative, there is an increased odds that the events not associated with the relationship will occur, I.e. it is more likely that RR is not predictive of severe COVID-19. The Odds Ratios (and confidence intervals) for both the papers that measured RR and SpO2 as vital signs to predict COVID-19 status are presented below in Figures 4 and 5 as forest plots.
Rates and types of urine drug screen false negative results compared with confirmatory toxicology testing in major trauma patients
Published in Clinical Toxicology, 2022
Stephanie T. Weiss, Laura J. Veach, William McGill, Jeffrey Brent
Limitations of this study include the inability to correct our odds ratios for all potentially confounding variables. UDS testing batteries are variable, limiting the generalizability of these results. We used a commercial UDS that was not tailored to the specific drugs prevalent in our local community, resulting in tests for some analytes like phencyclidine and barbiturates that were low yield. While our testing was comprehensive, it is possible that a more extensive battery might have detected additional FN. In some cases, we were unable to definitively determine whether certain drugs such as fentanyl were given iatrogenically. We also could not determine the role of detected substances in the etiology of our patients’ traumas given that the window for drug detection in urine typically exceeds the duration of drug effect.