What is the biggest challenge that labs face with sweat chloride testing?
The sweat test involves transdermal administration of pilocarpine by iontophoresis to stimulate sweat gland secretion, followed by collection and quantitation of sweat onto gauze, filter paper, or into a Macroduct coil and analysis of chloride concentration. Appropriate performance of the sweat test is crucial for accurately diagnosing cystic fibrosis.
The Cystic Fibrosis Foundation requires laboratories to maintain an annual quantity not sufficient (QNS) rate for this test of 5% or less for children older than 3 months and an annual QNS rate of 10% or less for infants 6 weeks to 3 months. This requirement aims to prevent repeat testing triggered by insufficient sample volume, which in turn increases the wait time for a definitive diagnosis, delays initiation of therapy, and reduces sweat testing’s overall cost-effectiveness. However, attaining sufficient sample volume remains a major challenge with sweat chloride testing.
When should labs perform sweat testing in newborns to avoid QNS situations?
In asymptomatic newborns with a positive newborn screening result or positive prenatal genetic test for cystic fibrosis, labs should evaluate sweat chloride when the infant is at least 10 days old, greater than 36 weeks gestation, and weighs >2 kg. In symptomatic newborns (for example, those with meconium ileus), labs can evaluate sweat chloride as early as 48 hours after birth if they are able to collect an adequate sweat volume.
Prior to testing, labs or clinicians should also provide parents of patients with a verbal explanation of the testing procedure as well as a written take-home explanation. This helps to ensure that infants are well hydrated prior to testing (and should be done in the case of adult patients as well).
What else can labs do to minimize QNS for sweat chloride testing?
First and foremost, labs should validate the sensitivity of their chloride detection method before putting it in place. Essential validation procedures include studies of accuracy, precision, and upper/lower limits of the analytic measurement range. In particular, the method should accurately detect sweat chloride at the lower end of the normal range (10 mmol/L).
Next, labs should specially train select staff members to collect and analyze samples, making sure to assess these individuals’ competency before they start working with patients. I recommend limiting the number of staff who do sweat chloride collection/testing so that the lab can easily monitor performance. Labs should do a weekly review of QNS rate per person so that they can deal with deficiencies in training promptly. Establishing monthly meetings between laboratory staff and cystic fibrosis clinical team members can also improve sweat testing by increasing communication about pain points. If QNS rates are very high, labs should call in consultants to regularly review the sweat test procedure for areas that need attention.
Throughout sweat collection, transport, and analysis, lab staff need to take every precaution to minimize evaporation, contamination, and condensation of the sample. Steps that can help with this include avoiding the use of electrolyte-containing solutions during the testing process; following proper procedure for the filter paper/gauze or Macroduct coil; and limiting collection time to 30 minutes, as going beyond this can lead to sample evaporation. Ideally, labs should process the sample immediately, but if this isn’t possible, it should be stored appropriately. Experts also suggest bilateral testing to ensure that at least one adequate sweat sample is obtained.
Of course, even if labs implement all of these recommendations, a low rate of QNS situations will still inevitably happen. Whenever insufficient samples occur, labs should make sure not to analyze them and should never pool them for analysis.
Shiefa Joan Sequeira, PhD, SC(ASCPi)CM, CPHQ, is a clinical scientist and point-of-care testing coordinator at Al Jalila Children’s Specialty Hospital in Dubai, United Arab Emirates. +Email: firstname.lastname@example.org