Resting and Post Bronchial Challenge Testing Carbon Dioxide Partial Pressure in Individuals with and without Asthma

Objective: There is conflicting evidence about resting carbon dioxide levels in asthmatic individuals. We wanted to determine if transcutaneously measured carbon dioxide levels prior and during bronchial provocation testing differ according to asthma status reflecting dysfunctional breathing. Methods: We investigated active firefighters and policemen by means of a validated questionnaire on respiratory symptoms, spirometry, bronchial challenge testing with methacholine (MCT) and measurement of transcutaneous blood carbon dioxide partial pressure (PtcCO 2) at rest prior performing spirometry, one minute and five minutes after termination of MCT. A respiratory physician blinded to the PtcCO2 results assigned a diagnosis of asthma after reviewing the available study data and the files of the workers medical screening program. Results: The study sample consisted of 128 male and 10 female individuals. Fifteen individuals (11%) had physiciandiagnosed asthma. There was no clinically important difference in median PtcCO 2 at rest, one and five minutes after recovery from MCT in asthmatics compared to non-asthmatics (35.6 vs 35.7 mmHg, p = 0.466; 34.7 vs 33.4 mmHg, p = 0.245 and 37.4 vs 36.4 mmHg, p = 0.732). The median drop in PtcCO2 during MCT and the increase after MCT was lower in asthmatics compared to non-asthmatics (0.1 vs 3.2 mmHg, p = 0.014 and 1.9 vs 2.9 mmHg, p = 0.025). Conclusions: PtcCO2 levels at rest prior and during recovery after MCT do not differ in individuals with or without physicia

Stratifying patients with peripheral neuropathic pain based on sensory profiles : algorithm and sample size recommendations

In a recent cluster analysis, it has been shown that patients with peripheral neuropathic pain can be grouped into 3 sensory phenotypes based on quantitative sensory testing profiles, which are mainly characterized by either sensory loss, intact sensory function and mild thermal hyperalgesia and/or allodynia, or loss of thermal detection and mild mechanical hyperalgesia and/or allodynia. Here, we present an algorithm for allocation of individual patients to these subgroups. The algorithm is nondeterministic-ie, a patient can be sorted to more than one phenotype-and can separate patients with neuropathic pain from healthy subjects (sensitivity: 78%, specificity: 94%). We evaluated the frequency of each phenotype in a population of patients with painful diabetic polyneuropathy (n = 151), painful peripheral nerve injury (n = 335), and postherpetic neuralgia (n = 97) and propose sample sizes of study populations that need to be screened to reach a subpopulation large enough to conduct a phenotype-stratified study. The most common phenotype in diabetic polyneuropathy was sensory loss (83%), followed by mechanical hyperalgesia (75%) and thermal hyperalgesia (34%, note that percentages are overlapping and not additive). In peripheral nerve injury, frequencies were 37%, 59%, and 50%, and in postherpetic neuralgia, frequencies were 31%, 63%, and 46%. For parallel study design, either the estimated effect size of the treatment needs to be high (> 0.7) or only phenotypes that are frequent in the clinical entity under study can realistically be performed. For crossover design, populations under 200 patients screened are sufficient for all phenotypes and clinical entities with a minimum estimated treatment effect size of 0.5.Peer reviewe