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Posted: August 20th, 2023

Tampons and Toxic Shock Syndrome: Epidemiological Case Study

Population Health, Epidemiology, & Statistical Problems
DNP, FNP, PMH

Tampons and Toxic Shock Syndrome: Epidemiological Case Study

Question 1: Why might the case-fatality rate in Wisconsin be lower than the national case-fatality rate?

Several factors could contribute to the lower case-fatality rate for Toxic Shock Syndrome (TSS) in Wisconsin compared to the national rate:

Early detection and active surveillance: Wisconsin quickly established a TSS surveillance system in response to initial case reports. This early implementation of disease surveillance could facilitate prompt detection and treatment of TSS cases, potentially reducing the case-fatality rate (World Health Organization, 2021).

Comprehensive case reporting and data collection: Efficient data collection systems can influence the accuracy of reported case-fatality rates. Given Wisconsin’s active surveillance, more TSS cases, including milder ones, might have been identified and reported, leading to a lower case-fatality rate (M’ikanatha et al., 2018).

Healthcare quality and access: Differences in healthcare provision and access between regions could be a factor. Wisconsin may have had better healthcare resources or more experienced healthcare professionals in handling TSS cases, leading to a lower case-fatality rate (Smith et al., 2019).

Reporting bias: The surveillance system in Wisconsin may have led to a reporting bias, with more mild or moderate cases being reported, whereas in other regions, more severe cases, which are inherently more likely to be fatal, may have been predominantly reported (Baker et al., 2019).

Question 2: Does it appear that TSS is associated with tampon use? Do you consider the Utah study consistent with the other two studies?

Based on the presented data in Tables 1, 2, and 3, there is a potential association between tampon use and Toxic Shock Syndrome (TSS). The higher number of cases among tampon users compared to non-users in the CDC-1 and Wisconsin studies suggests this association. However, it is important to note that the use of 2×2 tables shows a consistently strong positive association (Bland & Altman, 2000).

In the CDC-1 study, 50 tampon users were among the cases, compared to 0 non-users. Similarly, the Wisconsin study reported 30 tampon users and only 1 non-user among the cases. Both studies also reported statistically significant p-values (p = 0.02 and p = 0.014, respectively), indicating a strong likelihood of the association not being due to random chance.

The Utah study, on the other hand, showed a different pattern. It included 12 tampon users and 0 non-users among the cases, but the association was not statistically significant (p = 0.20). This suggests that while tampon use was common among cases, the observed pattern could have occurred by chance or due to other variables not included in the analysis, such as sample size limitations (Greenland & Morgenstern, 2001).

In this context, the Utah study could be seen as inconsistent with the CDC-1 and Wisconsin studies. However, it’s important to note that inconsistencies between studies can result from many factors, including differences in study design, sample size, population characteristics, or measurement of variables. Therefore, while the Utah study does not support the same conclusion as the CDC-1 and Wisconsin studies, it does not necessarily invalidate those findings (American Public Health Association, 2019). More comprehensive research would be needed to confirm the association and understand any potential differences across populations or geographical locations.

Question 3: What is the main difference between Table 4 and the previous tables?

The main difference between Table 4 and the previous tables is that Table 4 focuses specifically on continual tampon use during the index menstrual period. It does not consider sporadic tampon use, non-tampon menstrual products, or non-menstrual cases and their controls. Additionally, Table 4 provides information on both the exposed and unexposed groups, allowing for the calculation of an odds ratio and a chi-square statistic. This table is in a matched-pair format, whereas the previous tables are in an unmatched format. The matched-pair format is important when analyzing cases in different types of studies to determine if there is an association between exposure and disease or health outcomes (Rothman et al., 2012).

Question 4a: How many cases used tampons continually?

To answer this question, we need to create a 2×2 table that shows the matched pairs.

markdown
Copy code
Cases Controls Totals
Tampon users ? ? ?
Non-users ? ? ?
N/A Total Total 104

Question 4b: How many cases did not use tampons continually?

Based on the information provided, 16 cases did not use tampons continually.

Question 4c: How many controls used tampons continually?

Based on the information provided, 1 control used tampons continually.

Question 4d: How many controls did not use tampons continually?

Based on the information provided, 2 controls did not use tampons continually.

Question 5: What is the odds ratio and chi-square statistic for the matched pairs in Table 4?

The odds ratio (OR) is calculated as f/g, which is 16/1, resulting in an odds ratio of 16.

The chi-square (χ^2) statistic is calculated as (f – g)^2 / (f + g), which is (16 – 1)^2 / (16 + 1), resulting in a chi-square value of 15.

Question 6: What are the 95% confidence limits for the odds ratio?

To calculate the 95% confidence limits, we use the formula: OR / exp(1.96√χ), where OR is the odds ratio, and χ is the square root of the chi-square statistic. The Z value for a 95% confidence interval is 1.96.

From Question 5, we calculated that the odds ratio (OR) was 16, and the chi-square statistic was 15. So, the square root of chi-square, √χ, is approximately 3.87.

The lower 95% limit is calculated as OR / exp(1.96√χ), which is 16 / exp(1.96/3.87), resulting in approximately 9.57.

The upper 95% limit is calculated as OR * exp(1.96√χ), which is 16 * exp(1.96/3.87), resulting in approximately 25.85.

Therefore, the 95% confidence interval for the odds ratio is approximately (9.57, 25.85), indicating that we can be 95% confident that the true odds ratio lies within this interval.

Question 7: What do the results indicate about the association between continual tampon use and TSS?

The results indicate a strong association between the continual use of tampons and the occurrence of Toxic Shock Syndrome (TSS). With an odds ratio of 16, it appears that those who continually used tampons were 16 times more likely to develop TSS compared to those who did not use tampons continually. The 95% confidence interval (9.57, 25.85) does not contain 1, further strengthening the evidence for a true association (Centers for Disease Control and Prevention, 2023).

Question 8: What should be considered when interpreting the association between tampon use and TSS?

While the results suggest a strong association, it is crucial to remember that association does not imply causation. Other confounding factors may also be contributing to the observed association. Confounding refers to factors that are related to both the exposure (tampon use) and the outcome (TSS) and can distort the association between them. Therefore, it is important to conduct more comprehensive and controlled studies to validate these findings and to further investigate the potential causality (American Statistical Association, 2022).

Question 9: Why is the matched-pair format appropriate for Table 4?

The matched-pair format used in Table 4 is appropriate for this matched-pair case-control study because it allows for a clear delineation of cases and controls, along with exposure (continual tampon use) and non-exposure. This format enables an easy calculation of the odds ratio and other association measures, helping to understand the strength and direction of the observed association between tampon use and TSS. It is particularly useful in studies where matching is done to control for potential confounders and to increase the comparability between cases and controls (Bland & Altman, 2000).

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