Transcutaneous carbon dioxide profile during sleep reveals metabolic risk factors in post-menopausal females.

The risks of metabolic syndrome and sleep-disordered breathing increase around the time of the menopause. We have previously shown that features of the nocturnal transcutaneous carbon dioxide (TcCO2) profile are associated with metabolic variables such as cholesterol, glycosylated haemoglobin A1C (GHbA1C) and blood pressure in patients with sleep apnoea. In the present study, we investigated whether these metabolic variables can be predicted using noninvasive TcCO2 measurements during sleep in generally healthy post-menopausal females. 22 post-menopausal females underwent an overnight polygraphic sleep study that involved the continuous monitoring of arterial oxygen saturation (S(a,O2)) and TcCO2. Body composition, GHbA1C, plasma cholesterol and blood pressure were measured prior to the sleep study. Nocturnal TcCO2 features were the most important predictors of lipoprotein cholesterols, triglycerides and blood pressure levels. A longer sleep period and higher TcCO2 levels were linked with lower GHbA1C, and fragmented sleep with lower high-density lipoprotein cholesterol. Neither nocturnal S(a,O2) indices nor the apnoea/hypopnoea index had a predictive power. The results suggest that nocturnal TcCO2 events revealed metabolic risk factors already present in healthy post-menopausal females.

Parameter estimation of a respiratory control model from noninvasive carbon dioxide measurements during sleep.

A new method for estimating the parameters of a human gas exchange model is presented. Sensitivity analysis is used both to inspect the relative importance of the model parameters and to speed up the par-ameter estimation process. Multistart optimization is used to compensate for the effects of partial and noisy measurements. The validity of the method is first investigated with a test problem for which par-ameter identifiability is shown. The method is then applied to the estimation of sleep-related changes in the respiratory control system from the end-tidal and transcutaneous carbon dioxide measurements on human subjects. The results show that it is possible to gain insight into the behaviour of the rather complex physiological system using only a few noninvasive measurements and tractable computations.

Model-based analysis of mechanisms responsible for sleep-induced carbon dioxide differences.

This work describes a comprehensive mathematical model of the human respiratory control system which incorporates the central mechanisms for predicting sleep-induced changes in chemical regulation of ventilation. The model integrates four individual compartments for gas storage and exchange, namely alveolar air, pulmonary blood, tissue capillary blood, body tissues, and gas transport between them. An essential mechanism in the carbon dioxide transport is its dissociation into bicarbonate and acid, where a buffering mechanism through hemoglobin is used to prevent harmfully low pH levels. In the current model, we assume high oxygen levels and consider intracellular hydrogen ion concentration as the principal respiratory control variable. The resulting system of delayed differential equations is solved numerically. With an appropriate choice of key parameters, such as velocity of blood flow and gain of a non-linear controller function, the model provides steady-state results consistent with our experimental observations measured in subjects across sleep onset. Dynamic predictions from the model give new insights into the behaviour of the system in subjects with different buffering capacities and suggest novel hypotheses for future experimental and clinical studies.