Predictive value of positional change in vital capacity to identify diaphragm dysfunction.

RATIONALE: Sitting-to-supine fall in vital capacity (ΔVC) can be used to help identify diaphragm dysfunction (DD), but its optimal predictive threshold value is uncertain. Our aim was to evaluate the diagnostic performance of ΔVC in identifying the presence of unilateral or bilateral DD. METHODS: Patients referred to the diaphragm dysfunction clinic of our center (2017-2018) were included. All subjects had lung function testing (including measurement of ΔVC) and an ultrasound assessment of diaphragm thickening fraction (TFdi). Unilateral DD was defined as a single hemidiaphragm with TFdi ≤30 % and bilateral DD as a mean TFdi value of both hemidiaphragms ≤30 %. Clinical and physiological characteristics were compared across groups, and sensitivity/specificity analyses of ΔVC to identify DD were performed. RESULTS: 84 patients were included (31 unilateral DD, 17 bilateral DD and 36 without significant DD). DD groups had similar age, gender and BMI (all p > 0.05), but patients with bilateral DD had lower FVC, FEV1, MIP, TLC, ΔVC and more frequent orthopnea than patients with unilateral DD (all p < 0.05). There was a significant correlation between TFdi and ΔVC (rho=-0.56, p < 0.001). The optimal ΔVC value to identify bilateral DD was ≤-15 % [AUC 0.97 (95 %CI 0.89-1.00), p < 0.001, with sensitivity and specificity of 100 % and 89 %, respectively]. No single threshold of ΔVC could accurately predict unilateral DD [AUC 0.58 (95 %CI 0.45-0.72), p = 0.24]. CONCLUSION: ΔVC performs poorly in identifying patients with unilateral DD. However, a ΔVC value ≤-15 % is strongly associated with the presence of bilateral DD. These findings should be taken into account when using ΔVC in the evaluation of patients with suspected DD.

Statin treatment and new-onset diabetes: a review of proposed mechanisms.

New-onset diabetes has been observed in clinical trials and meta-analyses involving statin therapy. To explain this association, three major mechanisms have been proposed and discussed in the literature. First, certain statins affect insulin secretion through direct, indirect or combined effects on calcium channels in pancreatic ß-cells. Second, reduced translocation of glucose transporter 4 in response to treatment results in hyperglycemia and hyperinsulinemia. Third, statin therapy decreases other important downstream products, such as coenzyme Q10, farnesyl pyrophosphate, geranylgeranyl pyrophosphate, and dolichol; their depletion leads to reduced intracellular signaling. Other possible mechanisms implicated in the effect of statins on new-onset diabetes are: statin interference with intracellular insulin signal transduction pathways via inhibition of necessary phosphorylation events and reduction of small GTPase action; inhibition of adipocyte differentiation leading to decreased peroxisome proliferator activated receptor gamma and CCAAT/enhancer-binding protein which are important pathways for glucose homeostasis; decreased leptin causing inhibition of ß-cells proliferation and insulin secretion; and diminished adiponectin levels. Given that the magnitude of the risk of new-onset diabetes following statin use remains to be fully clarified and the well-established beneficial effect of statins in reducing cardiovascular risk, statins remain the first-choice treatment for prevention of CVD. Elucidation of the mechanisms underlying the development of diabetes in association with statin use may help identify novel preventative or therapeutic approaches to this problem and/or help design a new generation statin without such side-effects.