I totally knew that *cough cough*
These are the current gold standards for testing for pertussis
dedicated PCR and respiratory panel PCR
The aim of the study is
To assess whether panel PCR can reliably detect Bordetella pertussis infection compared with a dedicated pertussis PCR assay and to determine how often panel PCR testing may miss true pertussis cases or attribute symptoms to other respiratory pathogens.
This type of study is used in the article
retrospective cohort study
The differences between types of validity
Internal: does it test what it's supposed to test?
External: can these results from the sample population be applied to the intended population?
These are the main findings of the article
- Panel testing was only positive 56% of the time and also included other positives which can lead to misdiagnosis.
-Approximately 42% of pertussis-positive samples also contained other respiratory pathogens (most commonly rhinovirus/enterovirus).
-Samples with lower cycle threshold (Ct) values (reflecting higher B. pertussis DNA concentration) were significantly more likely to test positive on RPP, highlighting its lower analytical sensitivity compared with the dedicated assay.
Paired t-test is used to
Check if there’s a significant difference between two related measurements.
When to use it (examples): a) same item, different conditions, b) before and after an intervention
In short: It's for comparing related things to see if a change or difference is real, not just by chance.
These are other pathogens that are typically tested for on multiplex respiratory panels
Adenovirus, coronavirus, rhino/enterovirus, influenza, human metapneumovirus, parainfluenza, RSV, chlamydophila pneumoniae, Mycoplasma pneumoniae
The Inclusion/Exclusion Criteria & Primary/Secondary Outcomes are
Inclusion Criteria: Archived nasopharyngeal specimens that had previously tested positive for Bordetella pertussis by the Focus Diagnostics PCR assay between March 2015 and October 2017 and were stored at –80 °C for retesting.
Exclusion Criteria: Duplicate, mislabeled, indeterminate, or PCR-inhibited samples were excluded to ensure validity of comparative analysis.
Primary Outcome: The proportion of B. pertussis–positive cases detected by the multiplex respiratory pathogen panel (RPP) compared with the dedicated pertussis PCR assay.
Secondary Outcome: The frequency of coinfection with other respiratory pathogens on RPP and the association between B. pertussis PCR cycle-threshold values and RPP detection rates.
Interquartile ranges are typically used to identify
variability or spread spread of data and to identify outliers
The interquartile range (IQR) tells you the spread or variability of the middle 50% of your data, showing how clustered or spread out the central data points are, while ignoring extreme outliers at the ends. It's the difference between the third quartile (Q3, 75th percentile) and the first quartile (Q1, 25th percentile) (IQR = Q3 - Q1). A large IQR means the middle data is spread out, while a small IQR means it's tightly clustered around the median.
This appraisal tool can be used on diagnostic studies
CEBM
Limitations of this paper include
- Retrospective design
- Selection bias
- Using frozen, banked specimens
- Detailed clinical information was unavailable for roughly half of the patients, limiting assessment of symptom correlation, disease stage, and outcomes.
- Risk of false positives: IS481 insertion sequence
- The study was conducted in a single academic health system using specific assays (Focus Diagnostics PCR and FilmArray RPP), so findings may not generalize to other institutions.
Chi-square testing is used to assess this
Used w/ categorical data to compare observed vs expected data to determine any significant relationships