Association between prehospital end-tidal carbon dioxide levels and mortality in patients with suspected severe traumatic brain injury

Purpose: Severe traumatic brain injury is a leading cause of mortality and morbidity, and these patients are frequently intubated in the prehospital setting. Cerebral perfusion and intracranial pressure are influenced by the arterial partial pressure of CO2 and derangements might induce further brain damage. We investigated which lower and upper limits of prehospital end-tidal CO2 levels are associated with increased mortality in patients with severe traumatic brain injury. Methods: The BRAIN-PROTECT study is an observational multicenter study. Patients with severe traumatic brain injury, treated by Dutch Helicopter Emergency Medical Services between February 2012 and December 2017, were included. Follow-up continued for 1 year after inclusion. End-tidal CO2 levels were measured during prehospital care and their association with 30-day mortality was analyzed with multivariable logistic regression. Results: A total of 1776 patients were eligible for analysis. An L-shaped association between end-tidal CO2 levels and 30-day mortality was observed (p = 0.01), with a sharp increase in mortality with values below 35 mmHg. End-tidal CO2 values between 35 and 45 mmHg were associated with better survival rates compared to &lt; 35 mmHg. No association between hypercapnia and mortality was observed. The odds ratio for the association between hypocapnia (&lt; 35 mmHg) and mortality was 1.89 (95% CI 1.53–2.34, p &lt; 0.001) and for hypercapnia (≥ 45 mmHg) 0.83 (0.62–1.11, p = 0.212). Conclusion: A safe zone of 35–45 mmHg for end-tidal CO2 guidance seems reasonable during prehospital care. Particularly, end-tidal partial pressures of less than 35 mmHg were associated with a significantly increased mortality.</p

Proposals for a Practical System of Significance Evaluation in Archaeological Heritage Management

World Heritage & Archaeological Resource Managemen

Efficacy and safety of on-demand use of 2 treatments designed for different etiologies of female sexual interest/arousal disorder:3 Randomized Clinical Trials

Background In women, low sexual desire and/or sexual arousal can lead to sexual dissatisfaction and emotional distress, collectively defined as female sexual interest/arousal disorder (FSIAD). Few pharmaceutical treatment options are currently available. Aim To investigate the efficacy and safety of 2 novel on-demand pharmacologic treatments that have been designed to treat 2 FSIAD subgroups (women with low sensitivity for sexual cues and women with dysfunctional over-activation of sexual inhibition) using a personalized medicine approach using an allocation formula based on genetic, hormonal, and psychological variables developed to predict drug efficacy in the subgroups. Methods 497 women (21–70 years old) with FSIAD were randomized to 1 of 12 8-week treatment regimens in 3 double-blinded, randomized, placebo-controlled, dose-finding studies conducted at 16 research sites in the United States. Efficacy and safety of the following on-demand treatments was tested: placebo, testosterone (T; 0.5 mg), sildenafil (S; 50 mg), buspirone (B; 10 mg) and combination therapies (T 0.25 mg + S 25 mg, T 0.25 mg + S 50 mg, T 0.5 mg + S 25 mg, T 0.5 mg + S 50 mg, and T 0.25 mg + B 5 mg, T 0.25 mg + B 10 mg, T 0.5 mg + B 5 mg, T 0.5 mg + B 10 mg). Outcomes The primary efficacy measure was the change in satisfying sexual events (SSEs) from the 4-week baseline to the 4-week average of the 8-week active treatment period after medication intake. For the primary end points, the combination treatments were compared with placebo and the respective monotherapies on this measure. Results In women with low sensitivity for sexual cues, 0.5 mg T + 50 mg S increased the number of SSEs from baseline compared with placebo (difference in change [Δ] = 1.70, 95% CI = 0.57–2.84, P =.004) and monotherapies (S: Δ = 1.95, 95% CI = 0.44–3.45, P =.012; T: Δ = 1.69, 95% CI = 0.58–2.80, P =.003). In women with overactive inhibition, 0.5 mg T + 10 mg B increased the number of SSEs from baseline compared with placebo (Δ = 0.99, 95% CI = 0.17–1.82, P =.019) and monotherapies (B: Δ = 1.52, 95% CI = 0.57–2.46, P =.002; T: Δ = 0.98, 95% CI = 0.17–1.78, P =.018). Secondary end points followed this pattern of results. The most common drug-related side effects were flushing (T + S treatment, 3%; T + B treatment, 2%), headache (placebo treatment, 2%; T + S treatment, 9%), dizziness (T + B treatment, 3%), and nausea (T + S treatment, 3%; T + B treatment, 2%). Clinical Implications T + S and T + B are promising treatments for women with FSIAD. Strengths and Limitations The data were collected in 3 well-designed randomized clinical trials that tested multiple doses in a substantial number of women. The influence of T + S and T + B on distress and the potentially sustained improvements after medication cessation were not investigated. Conclusions T + S and T + B are well tolerated and safe and significantly increase the number of SSEs in different FSIAD subgroups. Tuiten A, van Rooij K, Bloemers J, et al. Efficacy and Safety of On-Demand Use of 2 Treatments Designed for Different Etiologies of Female Sexual Interest/Arousal Disorder: 3 Randomized Clinical Trials. J Sex Med 2018;15:201–216

Multilevel analyses of on-demand medication data, with an application to the treatment of Female Sexual Interest/Arousal Disorder

Data from clinical trials investigating on-demand medication often consist of an intentionally varying number of measurements per patient. These measurements are often observations of discrete events of when the medication was taken, including for example data on symptom severity. In addition to the varying number of observations between patients, the data have another important feature: they are characterized by a hierarchical structure in which the events are nested within patients. Traditionally, the observed events of patients are aggregated into means and subsequently analyzed using, for example, a repeated measures ANOVA. This procedure has drawbacks. One drawback is that these patient means have different standard errors, first, because the variance of the underlying events differs between patients and second, because the number of events per patient differs. In this paper, we argue that such data should be analyzed by applying a multilevel analysis using the individual observed events as separate nested observations. Such a multilevel approach handles this drawback and it also enables the examination of varying drug effects across patients by estimating random effects. We show how multilevel analyses can be applied to on-demand medication data from a clinical trial investigating the efficacy of a drug for women with low sexual desire. We also explore linear and quadratic time effects that can only be performed when the individual events are considered as separate observations and we discuss several important statistical topics relevant for multilevel modeling. Taken together, the use of a multilevel approach considering events as nested observations in these types of data is advocated as it is more valid and provides more information than other (traditional) methods

A multilevel structural equation model for assessing a drug effect on a patient‐reported outcome measure in on‐demand medication data

We analyze data from a clinical trial investigating the effect of an on-demand drug for women with low sexual desire. These data consist of a varying number of measurements/events across patients of when the drug was taken, including data on a patient-reported outcome consisting of five items measuring an unobserved construct (latent variable). Traditionally, these data are aggregated prior to analysis by composing one sum score per event and averaging this sum score over all observed events. In this paper, we explain the drawbacks of this aggregating approach. One drawback is that these averages have different standard errors because the variance of the underlying events differs between patients and because the number of events per patient differs. Another drawback is the implicit assumption that all items have equal weight in relation to the latent variable being measured. We propose a multilevel structural equation model, treating the events (level 1) as nested observations within patients (level 2), as alternative analysis method to overcome these drawbacks. The model we apply includes a factor model measuring a latent variable at the level of the event and at the level of the patient. Then, in the same model, the latent variables are regressed on covariates to assess the drug effect. We discuss the inferences obtained about the efficacy of the on-demand drug using our proposed model. We further illustrate how to test for measurement invariance across grouping covariates and levels using the same model.</p

Two novel combined drug treatments for women with hypoactive sexual desire disorder

Low sexual desire is the most common sexual complaint in women. As a result, many women suffer from sexual dissatisfaction which often negatively interferes with their quality of life. These complaints have been classified as the condition Hypoactive Sexual Desire Disorder (HSDD), and have recently been merged with the condition Female Sexual Arousal Disorder (FSAD) into the diagnosis Female Sexual Interest/Arousal Disorder (FSIAD) in the DSM-5. To date, no drug treatment approved by the U.S. Food & Drug Administration (FDA)/European Medicines Agency (EMA) is available to treat women with HSDD/FSIAD. As a result, there is an unmet need for a drug treatment for HSDD/FSIAD. In our search for an adequate treatment we followed a different approach compared to other pharmaceutical companies. Based on a personalized sexual medicine approach we proposed that different mechanisms cause low sexual desire in women, namely an insensitive system for sexual cues or dysfunctional activation of sexual inhibitory mechanisms. Subsequently we developed two new on-demand drug treatments for women with HSDD/FSIAD based on these different causal mechanisms. One treatment (testosterone combined with a phosphodiesterase type 5 inhibitor) has been developed for women with HSDD/FSIAD due to a relatively insensitive system for sexual cues, while the second treatment (testosterone combined with a 5-HT₁A receptor agonist) has been developed for women with HSDD/FSIAD due to dysfunctional activation of sexual inhibitory mechanisms

Multilevel analyses of on-demand medication data, with an application to the treatment of Female Sexual Interest/Arousal Disorder

Data from clinical trials investigating on-demand medication often consist of an intentionally varying number of measurements per patient. These measurements are often observations of discrete events of when the medication was taken, including for example data on symptom severity. In addition to the varying number of observations between patients, the data have another important feature: they are characterized by a hierarchical structure in which the events are nested within patients. Traditionally, the observed events of patients are aggregated into means and subsequently analyzed using, for example, a repeated measures ANOVA. This procedure has drawbacks. One drawback is that these patient means have different standard errors, first, because the variance of the underlying events differs between patients and second, because the number of events per patient differs. In this paper, we argue that such data should be analyzed by applying a multilevel analysis using the individual observed events as separate nested observations. Such a multilevel approach handles this drawback and it also enables the examination of varying drug effects acrosspatients by estimating random effects. We show how multilevel analyses can be applied to on-demand medication data from a clinical trial investigating the efficacy of a drug for women with low sexual desire. We also explore linear and quadratic time effects that can only be performed when the individual events are considered as separate observations and we discuss several important statistical topics relevant for multilevel modeling. Taken together, the use of a multilevel approach considering events as nested observations in these types of data is advocated as it is more valid and provides more information than other(traditional) methods

The Effect of Food on the Pharmacokinetics of Sildenafil after Single Administration of a Sublingual Testosterone and Oral Sildenafil Combination Tablet in Healthy Female Subjects

Introduction: Female sexual interest/arousal disorder (FSIAD) affects many women worldwide, but pharmacological treatment options are scarce. A new medicine being developed for FSIAD is an on-demand, dual-route, dual-release drug combination product containing 0.5 mg testosterone (T) and 50 mg sildenafil (S), referred to here as T+S. Aim: The aim of this study was to compare the effect of a fed and a fasted state on the pharmacokinetics of sildenafil following administration of T+S. Methods: Eighteen healthy women were administered T+S under fed and fasted conditions during 2 separate overnight visits in this randomized, open-label, balanced, 2-period, 2-treatment, 2-sequence crossover study. Main Outcome Measures: The pharmacokinetics of sildenafil and its active metabolite N-desmethyl sildenafil were determined over a 24-hour period. Total testosterone was assessed only at a limited number of time points for quality purposes, as sublingual uptake is not expected to be affected by food intake. Results: The observed geometric mean ratios (GMRs) and 90% confidence intervals of sildenafil were not all contained within the prespecified bounds (0.80, 1.25). The GMR (90% CI) for plasma AUC0–last was 1.2753 (0.9706–1.6755); for AUC0–14h, it was 1.7521 (1.0819–2.8374); and for Cmax, it was 1.5591 (0.8634–2.8153). Only lower limits of the CIs fell within the bounds. For N-desmethyl sildenafil, the GMR (90% CI) for AUC0–last was 0.8437 (0.6738–1.0564); for AUC0–10h, it was 1.0847 (0.7648–1.5383); and for Cmax, it was 1.0083 (0.6638–1.5318). Only the GMRs were contained within bounds. No differences were observed between plasma testosterone Cmax and Tmax under fed and fasted conditions, which is in line with expectations for a sublingual administration. Clinical Implications: The T+S combination tablet ruptures too late when taken in a fasted state and should therefore not be taken on an empty stomach. Strengths &amp; Limitations: This is a well-controlled study that provides important insights into the performance characteristics of the delayed-release coating of the combination tablet. The higher variability of the pharmacokinetic parameters in the fasted state was caused by severely delayed rupture in one-third of the women. A reason for this is proposed but the present data do not explain this phenomenon. Conclusion: The pharmacokinetics of sildenafil from this modified-release tablet are more robust under fed conditions as compared to the artificial fasted condition where no food is consumed 10 hours prior to and 4 hours after dosing. The dosing situation under the tested fasting condition does not represent the expected common use of this product. Patients should, however, be instructed not to take the tablet on an empty stomach. Bloemers J, Gerritsen J, van Rooij K, et al. The Effect of Food on the Pharmacokinetics of Sildenafil After Single Administration of a Sublingual Testosterone and Oral Sildenafil Combination Tablet in Healthy Female Subjects. J Sex Med 2019; 19:1433–1443.</p