Predictive factors influencing pregnancy rates after intrauterine insemination with frozen donor semen: a prospective cohort study.

The extent to which certain parameters can influence pregnancy rates after intrauterine insemination with frozen donor semen was examined prospectively. Between July 2011 and September 2015, 402 women received 1264 IUI cycles with frozen donor semen in a tertiary referral infertility centre. A case report form was used to collect data prospectively. The primary outcome measure was clinical pregnancy rate (CPR), confirmed by detection of a gestational sac and fetal heartbeat using ultrasonography at 7-8 weeks of gestation. Statistical analysis was carried out using generalized estimating equations (GEE) to account for the correlation between observations from the same patient. Overall, CPR per cycle was 17.2%. Multivariate GEE analysis revealed the following parameters as predictive for a successful pregnancy outcome: female age (P = 0.0003), non-smoking or smoking fewer than 15 cigarettes a day (P = 0.0470 and P = 0.0235, respectively), secondary infertility (P = 0.0062), low progesterone levels at day zero of the cycle (P = 0.0164) and use of ovarian stimulation with HMG and recombinant FSH compared with clomiphene citrate and natural cycle (P = 0.0006 and P = 0.0004, respectively). These parameters were the most important factors influencing the success rate in a sperm donation programme.

Predictive value of different covariates influencing pregnancy rate following intrauterine insemination with homologous semen: a prospective cohort study.

The aim was to examine the value of different covariates in the prediction of intrauterine insemination (IUI) success. Between July 2011 and September 2015, data from 1401 IUI cycles with homologous semen in 556 couples were collected prospectively, by questionnaire, in a tertiary referral infertility centre. Statistical analysis was performed using generalized estimating equations (GEEs). GEEs were used instead of an ordinary logistic regression model to take into account the correlation between observations from the same person. The primary outcome parameter was clinical pregnancy rate (CPR), confirmed with a gestational sac and fetal heartbeat on ultrasonography at 7-8 weeks. An overall CPR of 9.5% per cycle was observed. Univariate statistical analysis revealed female and male age, male smoking, female body mass index, ovarian stimulation and inseminating motile count (IMC) as covariates significantly influencing CPR per cycle. Multivariate GEE analysis revealed that the only valuable prognostic covariates included female age, male smoking and infertility status (i.e. primary/secondary infertility). IMC showed a significant curvilinear relationship, with first an increase and then a decrease in pregnancy rate.

What is the value of regional cerebral saturation in post-cardiac arrest patients? A prospective observational study.

BACKGROUND: The aim of this study was to elucidate the possible role of cerebral saturation monitoring in the post-cardiac arrest setting. METHODS: Cerebral tissue saturation (SctO2) was measured in 107 successfully resuscitated out-of-hospital cardiac arrest patients for 48 hours between 2011 and 2015. All patients were treated with targeted temperature management, 24 hours at 33 °C and rewarming at 0.3 °C per hour. A threshold analysis was performed as well as a linear mixed models analysis for continuous SctO2 data to compare the relation between SctO2 and favorable (cerebral performance category (CPC) 1-2) and unfavorable outcome (CPC 3-4-5) at 180 days post-cardiac arrest in OHCA patients. RESULTS: Of the 107 patients, 50 (47 %) had a favorable neurological outcome at 180 days post-cardiac arrest. Mean SctO2 over 48 hours was 68 % ± 4 in patients with a favorable outcome compared to 66 % ± 5 for patients with an unfavorable outcome (p = 0.035). No reliable SctO2 threshold was able to predict favorable neurological outcome. A significant different course of SctO2 was observed, represented by a logarithmic and linear course of SctO2 in patients with favorable outcome and unfavorable outcome, respectively (p < 0.001). During the rewarming phase, significant higher SctO2 values were observed in patients with a favorable neurological outcome (p = 0.046). CONCLUSIONS: This study represents the largest post-resuscitation cohort evaluated using NIRS technology, including a sizeable cohort of balloon-assisted patients. Although a significant difference was observed in the overall course of SctO2 between OHCA patients with a favorable and unfavorable outcome, the margin was too small to likely represent functional outcome differentiation based on SctO2 alone. As such, these results given such methodology as performed in this study suggest that NIRS is insufficient by itself to serve in outcome prognostication, but there may remain benefit when incorporated into a multi-neuromonitoring bedside assessment algorithm.

A sensitivity analysis for shared-parameter models for incomplete longitudinal outcomes.

All models for incomplete data either explicitly make assumptions about aspects of the distribution of the unobserved outcomes, given the observed ones, or at least implicitly imply such. One consequence is that there routinely exist a whole class of models, coinciding in their description of the observed portion of the data but differing with respect to their "predictions" of what is unobserved. Within such a class, there always is a single model corresponding to so-called random missingness, in the sense that the mechanism governing missingness depends on covariates and observed outcomes, but given these not further on unobserved outcomes. We employ these results in the context of so-called shared-parameter models where outcome and missingness models are connected by means of common latent variables or random effects, to devise a sensitivity analysis framework. Precisely, the impact of varying unverifiable assumptions about unobserved measurements on parameters of interest is studied. Apart from analytic considerations, the proposed methodology is applied to assess treatment effect in data from a clinical trial in toenail dermatophyte onychomycosis. While our focus is on longitudinal outcomes with incomplete outcome data, the ideas developed in this paper are of use whenever a shared-parameter model could be considered.

Resource utilisation and direct costs in patients with recently diagnosed fibromyalgia who are offered one of three different interventions in a randomised pragmatic trial.

The purpose of this study is to understand the course of costs over a 2-year period in a cohort of recently diagnosed fibromyalgia (FM) patients receiving different treatment strategies. Following the diagnosis, patients were randomly assigned to a multidisciplinary programme (MD), aerobic exercise (AE) or usual care (UC) without being aware of alternative interventions. Time between diagnosis and start of treatment varied between patients. Resource utilisation, health care costs and costs for patients and families were collected through cost diaries. Mixed linear model analyses (MLM) examined the course of costs over time. Linear regression was used to explore predictors of health care costs in the post-intervention period. Two hundred three participants, 90 % women, mean (SD) age 41.7 (9.8) years, were included in the cohort. Intervention costs per patient varied from €864 to 1392 for MD and were €121 for AE. Health care costs (excluding intervention costs) decreased after diagnosis, but before the intervention in each group, and increased again afterwards to the level close to the diagnostic phase. In contrast, patient and family costs slightly increased over time in all groups without initial decrease immediately after diagnosis. Annualised health care costs post-intervention varied between €1872 and 2310 per patient and were predicted by worse functioning and high health care costs at diagnosis. In patients with FM, health care costs decreased following the diagnosis by a rheumatologist. Offering patients a specific intervention after diagnosis incurred substantial costs while having only marginal effects on costs.

Exercise training improves insulin release during glucose tolerance testing in stable chronic heart failure patients.

PURPOSE: Chronic heart failure (CHF) patients often present with (pre)diabetes, which negatively influences prognosis. Unlike the proven effect of exercise on glucose regulation in the general population, its effect in CHF is unclear. Therefore, this study aimed at investigating the effect of exercise training on glucose regulation in stable CHF patients. METHODS: Twenty-two CHF patients were randomized into training (EX, n = 15) and control (CON, n = 7) groups. Before and after a 12-week training intervention involving endurance and resistance training, glucose tolerance (2-hour oral glucose tolerance test), exercise tolerance (cardiopulmonary exercise test), muscle strength (isokinetic dynamometer), heart function (echocardiography), glycated hemoglobin, body composition (dual-energy x-ray absorptiometry), and quality of life (EQ5D) were assessed. RESULTS: At baseline, glucose levels 2 hours after glucose intake were elevated in both groups. Whereas area under the glucose curve did not change, area under the insulin curve decreased following training (EX, -13 ± 23% vs CON, +22 ± 33%; P < .05). Changes in the ratio of mitral peak velocity of early filling/early diastolic mitral annular velocity and waist-to-hip fat mass ratio were related to changes in the insulin curve. Exercise training resulted in improved oxygen uptake at the second ventilatory threshold (EX, +10 ± 5% vs CON, -8 ± 5%; P < .05) and isokinetic strength endurance of the upper leg (EX, +25 ± 9% vs CON, -6 ± 5%; P < 0.05). Lean body tissue was increased by 2.2 ± 0.5% in EX versus 0.2 ± 0.6% in CON (P < .05). CONCLUSION: Our data suggest that exercise training attenuates worsening of glucose regulation typically seen in a stable CHF population.

Mandatory oral glucose tolerance tests identify more diabetics in stable patients with chronic heart failure: a prospective observational study.

BACKGROUND: Many patients with chronic heart failure (CHF) are believed to have unrecognized diabetes, which is associated with a worse prognosis. This study aimed to describe glucose tolerance in a general stable CHF population and to identify determinants of glucose tolerance focusing on body composition and skeletal muscle strength. METHODS: A prospective observational study was set up. Inclusion criteria were diagnosis of CHF, stable condition and absence of glucose-lowering medication. Patients underwent a 2 h oral glucose tolerance test (OGTT), isometric strength testing of the upper leg and dual energy x-ray absorptiometry. Health-related quality of life and physical activity level were assessed by questionnaire. RESULTS: Data of 56 participants were analyzed. Despite near-normal fasting glucose values, 55% was classified as prediabetic, 14% as diabetic, and 20% as normal glucose tolerant. Of all newly diagnosed diabetic patients, 79% were diagnosed because of 2 h glucose values only and none because of HbA1c. Univariate mixed model analysis revealed ischaemic aetiology, daily physical activity, E/E', fat trunk/fat limbs and extension strength as possible explanatory variables for the glucose curve during the glucose tolerance test. When combined in one model, only fat trunk/fat limbs and E/E' remained significant predictors. Furthermore, fasting insulin was correlated with fat mass/height2 (r = 0.51, p < 0.0001), extension strength (r = -0.33, p < 0.01) and triglycerides (r = 0.39, p < 0.01). CONCLUSIONS: Our data confirm that a large majority of CHF patients have impaired glucose tolerance. This glucose intolerance is related to fat distribution and left ventricular end-diastolic pressure.