The Well-being Model: A New Drug Interaction Model for Positive and Negative Effects

Background: Drugs are routinely combined in anesthesia and pain management to obtain an enhancement of the desired effects. However, a parallel enhancement of the undesired effects might take place as well, resulting in a limited therapeutic usefulness. Therefore, when addressing the question of optimal drug combinations, side effects must be taken into account.

Methods: By extension of a previously published interaction model, the authors propose a method to study drug interactions considering also their side effects. A general outcome parameter identified as patient's well-being is defined by superposition of positive and negative effects. Well-being response surfaces are computed and analyzed for varying drugs pharmacodynamics and interaction types. In particular, the existence of multiple maxima and of optimal drug combinations is investigated for the combination of two drugs.

Results: Both drug pharmacodynamics and interaction type affect the well-being surface and the deriving optimal combinations. The effect of the interaction parameters can be explained in terms of synergy and antagonism and remains unchanged for varying pharmacodynamics. For all simulations performed for the combination of two drugs, the presence of more than one maximum was never observed.     

Differential effects of glycogen synthase kinase 3 (GSK3) inhibition by lithium or selective inhibitors in the central nervous system

Glycogen synthase kinase (GSK3) is a constitutively active serine-threonine kinase associated to neurological and psychiatric disorders. GSK3 inhibition is considered a mediator of the efficacy of the mood-stabiliser lithium. This study aimed at comparing the central nervous system effect of lithium with the selective GSK3 inhibitors AZ1080 and compound A in biochemical, cellular, and behavioural tests. Collapsin response mediator protein 2 is a neuron-specific GSK3 substrate. Lithium, AZ1080, and compound A inhibited its phosphorylation in rat primary neurons with different pIC₅₀. After systemic treatments with lithium or GSK3 inhibitors to assess specific functional responses, phosphorylation was unchanged in adult rat brain, while it was strongly inhibited by GSK3 inhibitors in pups, differently from lithium. Lithium may exert neurotrophic effect by increasing brain-derived neurotrophic factor (BDNF) levels: in the present experimental conditions, lithium exerted opposite effects on plasma BDNF levels compared to GSK3 inhibitors, suggesting this effect might not be necessarily mediated by GSK3 inhibition alone. While plasma thyroid-stimulating hormone and luteinising hormone were not affected by lithium, they were decreased by selective inhibitors. GH and prolactin displayed similar responses towards reduction. Follicle-stimulating hormone levels were not altered by treatments, whereas melatonin was specifically increased by AZ1080. Lithium impaired mouse spontaneous locomotion and decreased amphetamine-induced hyper-locomotion. AZ1080 had no effects on locomotion, while compound A reduced spontaneous locomotor activity without effects on amphetamine-induced hyper-locomotion. The present results indicate that a broad correlation between the effects of lithium and selective GSK3 inhibitors could not be devised, suggesting alternative mechanisms, whereas overlapping results could be obtained in specific assays.     

Model-free quantification of dynamic PET data using nonparametric deconvolution

Dynamic positron emission tomography (PET) data are usually quantified using compartment models (CMs) or derived graphical approaches. Often, however, CMs either do not properly describe the tracer kinetics, or are not identifiable, leading to nonphysiologic estimates of the tracer binding. The PET data are modeled as the convolution of the metabolite-corrected input function and the tracer impulse response function (IRF) in the tissue. Using nonparametric deconvolution methods, it is possible to obtain model-free estimates of the IRF, from which functionals related to tracer volume of distribution and binding may be computed, but this approach has rarely been applied in PET. Here, we apply nonparametric deconvolution using singular value decomposition to simulated and test–retest clinical PET data with four reversible tracers well characterized by CMs ([¹¹C]CUMI-101, [¹¹C]DASB, [¹¹C]PE2I, and [¹¹C]WAY-100635), and systematically compare reproducibility, reliability, and identifiability of various IRF-derived functionals with that of traditional CMs outcomes. Results show that nonparametric deconvolution, completely free of any model assumptions, allows for estimates of tracer volume of distribution and binding that are very close to the estimates obtained with CMs and, in some cases, show better test–retest performance than CMs outcomes.     

Sensors & Algorithms for Continuous Glucose Monitoring: Glucose Prediction Algorithms from Continuous Monitoring Data: Assessment of Accuracy via Continuous Glucose Error-Grid Analysis

Aim

The aim of this article was to use continuous glucose error-grid analysis (CG-EGA) to assess the accuracy of two time-series modeling methodologies recently developed to predict glucose levels ahead of time using continuous glucose monitoring (CGM) data.

Methods

We considered subcutaneous time series of glucose concentration monitored every 3 minutes for 48 hours by the minimally invasive CGM sensor Glucoday® (Menarini Diagnostics, Florence, Italy) in 28 type 1 diabetic volunteers. Two prediction algorithms, based on first-order polynomial and autoregressive (AR) models, respectively, were considered with prediction horizons of 30 and 45 minutes and forgetting factors (ff) of 0.2, 0.5, and 0.8. CG-EGA was used on the predicted profiles to assess their point and dynamic accuracies using original CGM profiles as reference.

Results

Continuous glucose error-grid analysis showed that the accuracy of both prediction algorithms is overall very good and that their performance is similar from a clinical point of view. However, the AR model seems preferable for hypoglycemia prevention. CG-EGA also suggests that, irrespective of the time-series model, the use of ff = 0.8 yields the highest accurate readings in all glucose ranges.

Conclusions

For the first time, CG-EGA is proposed as a tool to assess clinically relevant performance of a prediction method separately at hypoglycemia, euglycemia, and hyperglycemia. In particular, we have shown that CG-EGA can be helpful in comparing different prediction algorithms, as well as in optimizing their parameters.     

Does aspirin have a role in improving pregnancy outcome for women with the antiphospholipid syndrome? A randomized controlled trial

OBJECTIVE: This pilot investigation was undertaken to assess the efficacy of low-dose aspirin therapy for the treatment of women with antiphospholipid antibodies when recurrent miscarriage is the only sequela. STUDY DESIGN: A double-blind, randomized, placebo-controlled trial was conducted in the setting of the recurrent miscarriage clinic of a tertiary referral obstetric hospital. The participants were 50 women with a history of recurrent miscarriages (>/=3) and antiphospholipid antibodies. Women with systemic lupus erythematosus or a history of thrombosis were excluded. Women were recruited after full investigative screening at the recurrent miscarriage clinic. Women with >/=3 fetal losses and persistently positive results for antiphospholipid antibodies were randomly allocated to receive either aspirin (75 mg daily) or placebo. Investigators, clinicians, and patients were blinded to the treatment. Rates of live births, antenatal complications, and delivery and neonatal outcomes were recorded prospectively. Data were compared by chi(2) analysis with Yates' correction, the Fisher exact test, or the Student t test as appropriate. RESULTS: There were 10 exclusions after random assignment because of inappropriate inclusion. Eighty-five percent of the placebo (17/20) group and 80% of the aspirin-treated group (16/20) were delivered of live infants. This difference was not significant. There were no significant differences in antenatal complications or neonatal morbidity between the groups. CONCLUSIONS: This preliminary study suggests that low-dose aspirin has no additional benefit when added to supportive care for women for whom recurrent early fetal loss is the only sequela of the antiphospholipid syndrome. This live birth rate with supportive care alone exceeds the published live birth rates for women with antiphospholipid antibody-mediated recurrent fetal loss who were treated with heparin or corticosteroids. This trial, like all other trials in this field, is small, but its results bring into question the need for pharmacologic intervention for women with antiphospholipid syndrome for whom recurrent fetal loss is the only sequela. Our results highlight the need for a large randomized controlled trial to identify the optimal treatment for this group of women and justify the inclusion of a placebo arm in any such trial.     

Recurrent Miscarriage - Outcome After Supportive Care in Early Pregnancy

One hundred and thirty three couples were investigated at a recurrent miscarriage clinic. In their next pregnancy 42 women (Group 1) with unexplained recurrent miscarriage were managed with a programme of formal emotional support and close supervision at an early pregnancy clinic. Two women were seen in 2 pregnancies (44 supervised pregnancies); 86% (38 of 44) of these pregnancies were successful. Four of the 6 miscarriages had an identifiable causal factor. Nine women (Group 2), also with unexplained recurrent miscarriage, acted as a control group. After initial investigation they were reassured and returned to the care of their family practitioner and did not receive formal supportive care in their subsequent pregnancy; 33% (3 of 9) of these pregnancies were successful (p = 0.005; Fishers Exact Test). Whilst acknowledging that there is a significant spontaneous cure rate in this condition, emotional support seems to be important in the prevention of unexplained recurrent miscarriage, giving results as good as any currently accepted therapy.     

Quantification of Positron Emission Tomography Data Using Simultaneous Estimation of the Input Function: Validation with Venous Blood and Replication of Clinical Studies

Molecular Imaging and Biology - To determine if one venous blood sample can substitute full arterial sampling in quantitative modeling for multiple positron emission tomography (PET) radiotracers...     

Combinations of Bupivacaine, Fentanyl, and Clonidine for Lumbar Epidural Postoperative Analgesia: A Novel Optimization Procedure

Background: The authors developed and applied a method to optimize the combination of bupivacaine, fentanyl, and clonidine for continuous postoperative lumbar epidural analgesia.

Methods: One hundred eighteen patients undergoing knee or hip surgery participated in the study. Postoperative epidural analgesia during 48 h after surgery was optimized under restrictions dictated by side effects. Initially, eight combinations of bupivacaine, fentanyl, and clonidine (expressed as drug concentration in the solution administered) were empirically chosen and investigated. To determine subsequent combinations, an optimization model was applied until three consecutive steps showed no decrease in pain score. For the first time in a clinical investigation, a regression model was applied when the optimization procedure led to combinations associated with unacceptable side effects.

Results: The authors analyzed 12 combinations with an allowed bupivacaine concentration range of 0-2.5 mg/ml, a fentanyl concentration range of 0-5 [mu]g/ml, and a clonidine concentration range of 0-5 [mu]g/ml. The best combinations of bupivacaine, fentanyl, and clonidine concentrations were 1.0 mg/ml-1.4 [mu]g/ml-0.5 [mu]g/ml, 0.9 mg/ml-3.0 [mu]g/ml-0.3 [mu]g/ml, 0.6 mg/ml-2.5 [mu]g/ml-0.8 [mu]g/ml, and 1.0 mg/ml-2.4 [mu]g/ml-1.0 [mu]g/ml, respectively, all producing a similarly low pain score. The incidence of side effects was low. The application of the regression model to combinations associated with high incidence of motor block successfully directed the optimization procedure to combinations within the therapeutic range.     

Brain 5-HT1A Receptor PET Binding,Cortisol Responses to Stress,and the Familial Transmission of Suicidal Behavior

BackgroundThe serotonin 1A (5-HT_1A) receptor has been implicated in depression and suicidal behavior. Lower resting cortisol levels are associated with higher 5-HT_1A receptor binding, and both differentiate suicide attempters with depression. However, it is not clear whether 5-HT_1A receptor binding and cortisol responses to stress are related to familial risk and resilience for suicidal behavior.Methods[¹¹C]CUMI-101 positron emission tomography imaging to quantify regional brain 5-HT_1A receptor binding was conducted in individuals considered to be at high risk for mood disorder or suicidal behavior on the basis of having a first- or second-degree relative(s) with an early onset mood disorder and history of suicidal behavior. These high-risk individuals were subdivided into the following groups: high risk resilient having no mood disorder or suicidal behavior (n = 29); high risk with mood disorder and no suicidal behavior history (n = 31); and high risk with mood disorder and suicidal behavior (n = 25). Groups were compared with healthy volunteers without a family history of mood disorder or suicidal behavior (n = 34). Participants underwent the Trier Social Stress Task (TSST). All participants were free from psychotropic medications at the time of the TSST and PET scanning.ResultsWe observed no group differences in 5-HT_1A receptor binding considering all regions simultaneously, nor did we observe heterogeneity of the effect of group across regions. These results were similar across outcome measures (BP_ND for all participants and BP_p in a subset of the sample) and definitions of regions of interest (ROIs; standard or serotonin system-specific ROIs). We also found no group differences on TSST outcomes. Within the high risk with mood disorder and suicidal behavior group, lower BP_p binding (β = −0.084, SE = 0.038, P = .048) and higher cortisol reactivity to stress (β = 9.25, 95% CI [3.27,15.23], P = .004) were associated with higher lethality attempts. There were no significant relationships between 5-HT_1A binding and cortisol outcomes.Conclusions5-HT_1A receptor binding in ROIs was not linked to familial risk or resilience protecting against suicidal behavior or mood disorder although it may be related to lethality of suicide attempt. Future studies are needed to better understand the biological mechanisms implicated in familial risk for suicidal behavior and how hypothalamic-pituitary-adrenal axis function influences such risk.