Arho Virkki

24-hour serum levels of growth hormone, prolactin, and cortisol in pre- and postmenopausal women: the effect of combined estrogen and progestin treatment.

OBJECTIVEnOur objective was to study the 24-h profiles of GH, prolactin (PRL), and cortisol concentrations in older postmenopausal and middle-aged premenopausal women, before and after estrogen-progestin treatment (EPT).nnnDESIGNnThe study was a randomized, placebo-controlled, double-blind trial. GH, PRL, and cortisol were sampled every 20 min for 24 h in 18 postmenopausal (aged 58-70 yr) and 17 premenopausal (aged 45-51 yr) women before and after 6 months of EPT.nnnRESULTSnThe mean 24-h GH (1.0 vs. 1.8 mU/liter, P = 0.033) and PRL (6.8 vs. 10.0 ng/ml, P = 0.009) concentrations were lower in postmenopausal than in premenopausal women. After EPT, the postmenopausal GH and PRL did not differ from premenopausal baseline levels. Postmenopausal mean 24-h GH (P < 0.001) and PRL (P = 0.002), daytime GH (P < 0.001) and nighttime PRL (P = 0.004) were higher during EPT compared with placebo. Cortisol levels did not differ. Premenopausal mean nighttime PRL (P = 0.026) and cortisol (P = 0.018) were higher during EPT compared with placebo. Postmenopausal PRL and premenopausal GH and PRL concentrations were higher at night than during the day. EPT did not alter this pattern.nnnCONCLUSIONSnMenopause was associated with decreased 24-h levels of GH and PRL, which were reversible with EPT. In contrast, cortisol levels were not affected by menopause or EPT. In middle-aged premenopausal women, the studied effects of EPT were limited to nighttime increases of PRL and cortisol.

Overnight variability in transcutaneous carbon dioxide predicts vascular impairment in women

While there are a number of studies demonstrating association between arterial oxyhaemoglobin saturation events during sleep and markers of vascular impairment, the contribution of peripheral carbon dioxide to the development of atherosclerosis is poorly understood. We used ultrasound imaging to measure carotid artery intima–media thickness (IMT), as well as flow‐mediated dilatation (FMD) and nitroglycerin‐mediated dilatation (NMD) of brachial artery, in 103 generally healthy 46‐year‐old (±2 years) women. Characteristic event patterns were extracted from their overnight recordings of arterial oxyhaemoglobin saturation , end‐tidal partial pressure of carbon dioxide and transcutaneous partial pressure of carbon dioxide . Importance of the event patterns was evaluated through predictive modelling of classes of the ultrasound measurements while controlling for potential confounders. Prediction accuracy was assessed with cross‐validation and reported as the area under the receiver operating characteristic curve (AUC). Overnight patterns predicted each of the ultrasound measurements with high accuracy (IMT, AUC = 0.70; FMD, AUC = 0.75; and NMD, AUC = 0.81; all with P < 0.001). Adding the or patterns into the models did not significantly increase their predictive powers (AUC = 0.72, AUC = 0.77 and AUC = 0.83, respectively). The most important patterns reflected overnight variability in . These results suggest a novel link between overnight carbon dioxide events and early signs of vascular impairment in middle‐aged women. Non‐invasive measurements combined with non‐linear modelling techniques could be used to reveal potential markers of vascular impairment present in relatively healthy subjects.

Overnight features of transcutaneous carbon dioxide measurement as predictors of metabolic status

OBJECTIVEnTo systematically investigate whether overnight features in transcutaneous carbon dioxide (P(TcCO(2)) measurements can predict metabolic variables in subject with suspected sleep-disordered breathing.nnnMETHODSnThe features extracted from the P(TcCO(2)) signal included the number of abrupt descents per hour and attributes that characterize the recovery after such an event. For each outcome variable, the subgroup of the 108 study subjects with the particular variable present was divided into two representative classes, and the optimal features that can predict the classes were learned. Overfitting was avoided by evaluating the classification algorithms using 10-fold cross-validation.nnnRESULTSn(P(TcCO(2)) signal has a key role in determining the classes of high-density lipoprotein cholesterol and thyroid-stimulating hormone concentrations, and it improves the classification accuracy of glycosylated hemoglobin A1c and fasting plasma glucose values.nnnCONCLUSIONSnThe features learned from the (P(TcCO(2)) signal reflected the state of the selected metabolic variables in a subtle, but systematic, way. These findings provide a step towards understanding how metabolic disturbances are connected to carbon dioxide exchange during sleep.

Non-invasive respiratory monitoring during wakefulness and sleep in pre- and postmenopausal women

Menopause and aging cause hormonal changes with respiratory consequences. The aim of the present study was to investigate the physiological changes in respiration during wakefulness and sleep across menopause in non-patient population using non-invasive measurements of blood and tissue gases. The arterial oxyhemoglobin saturation (SaO2), heart rate, end-tidal partial carbon dioxide tension (EtCO2) and transcutaneous partial carbon dioxide tension (TcCO2) were measured during wakefulness and sleep in thirteen pairs of BMI-matched pre- and postmenopausal women. Postmenopausal women had lower SaO2 during sleep than during wakefulness, whereas premenopausal women maintained their wakefulness SaO2 levels also during sleep. EtCO2 levels did not change either between wakefulness and sleep or between premenopausal and postmenopausal groups. TcCO2 levels increased from wakefulness to sleep in both groups and the increase was greater in the postmenopausal group. The impact of sleep on the non-invasive measurements of blood and tissue gases is stronger in postmenopausal women.

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 (Sa,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 Sa,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.

Understanding sleep-disordered breathing through mathematical modelling

Recent studies have uncovered high prevalence of undiagnosed sleep-disordered breathing, and its linkage to metabolic or cardiovascular disorders which represent increasing health hazard. However, the mechanistic links behind these disorders as well as their contribution to the experimental observations and treatment responses remain poorly understood. Therefore, the screening of clinical measurements still relies upon relatively simple diagnostic features, such as signal averages or event frequencies, which may represent suboptimal or surrogate markers of the underlying abnormality. Consequently, most patients are being treated with general therapies regardless of the cause of their key dysfunction. Combining experimental measurements with mathematical modelling has the potential to provide mechanistic insights into the individual factors underlying the disease progression, which may finally enable tailored treatment alternatives for each patient. This review depicts a number of modelling approaches to elucidate sleep-related dysfunctions of the human respiratory system, and how these models are being used to translate the measurements first into new ideas and then into testable hypotheses. Such model-based investigations can provide systematic strategies towards better understanding, predicting or even preventing these dysfunctions. Along with the brief description of the modelling approaches, we discuss their relative merits and potential implications especially for clinical research.

The temporal relationship between growth hormone and slow wave sleep is weaker after menopause

OBJECTIVEnTo study the temporal association between growth hormone (GH) and slow wave sleep (SWS) in middle-aged women.nnnMETHODSnSeventeen premenopausal and 18 postmenopausal women were studied using all-night polygraphic sleep recordings and blood sampling at 20-min intervals. The postmenopausal women were re-studied after six months on hormone therapy (HT) according to a randomized, double-blind, placebo-controlled protocol.nnnRESULTSnThe total sleep time (premenopausal 361.9±81.5 min, postmenopausal 358±67.7 min) and the percentages of the sleep stages did not differ between pre- and postmenopausal women. In postmenopausal women the first GH peak after sleep onset occurred later and with a more variable time interval compared to premenopausal women. The percentage of SWS was highest 40-20 min prior to the first GH peak after sleep onset in both groups with a higher SWS proportion in premenopausal women (p=0.048), although the total SWS percent for night did not differ. HT did not affect the distribution of SWS in postmenopausal women.nnnCONCLUSIONSnThe temporal relationship between GH and SWS in premenopausal women is less robust after menopause and is not improved with HT.

Optimization of multi-photon event discrimination levels using Poisson statistics

In applications where random multi-photon events must be distinguishable from the background, detection of the signals must be based on either analog current measurement or photon counting and multi-level discrimination of single and multi-photon events. In this paper a novel method for optimizing photomultiplier (PMT) pulse discrimination levels in single- and multi-photon counting is demonstrated. This calibration method is based on detection of photon events in coincidence to short laser pulses. The procedure takes advantage of Poisson statistics of single- and mult-iphoton signals and it is applicable to automatic calibration of photon counting devices on production line. Results obtained with a channel photomultiplier (CPM) are shown. By use of three parallel discriminators and setting the discriminator levels according to the described method resulted in a linear response over wide range of random single- and multi-photon signals.

ePCR: an R-package for survival and time-to-event prediction in advanced prostate cancer, applied to real-world patient cohorts

Motivation Prognostic models are widely used in clinical decision‐making, such as risk stratification and tailoring treatment strategies, with the aim to improve patient outcomes while reducing overall healthcare costs. While prognostic models have been adopted into clinical use, benchmarking their performance has been difficult due to lack of open clinical datasets. The recent DREAM 9.5 Prostate Cancer Challenge carried out an extensive benchmarking of prognostic models for metastatic Castration‐Resistant Prostate Cancer (mCRPC), based on multiple cohorts of open clinical trial data. Results We make available an open‐source implementation of the top‐performing model, ePCR, along with an extended toolbox for its further re‐use and development, and demonstrate how to best apply the implemented model to real‐world data cohorts of advanced prostate cancer patients. Availability and implementation The open‐source R‐package ePCR and its reference documentation are available at the Central R Archive Network (CRAN): https://CRAN.R‐project.org/package=ePCR. R‐vignette provides step‐by‐step examples for the ePCR usage. Supplementary information Supplementary data are available at Bioinformatics online.