Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process

for the ANZICS Centre for Outcome and Resource Evaluation (CORE) of the Australian and New Zealand Intensive Care Society (ANZICS)BACKGROUND Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. METHODS Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. RESULTS The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag ₄₀ and 35% had autocorrelation through to lag ₄₀; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. CONCLUSIONS The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.John L Moran, Patricia J Solomo

Production of benzylisoquinoline alkaloids in Saccharomyces cerevisiae

The benzylisoquinoline alkaloids (BIAs) are a diverse class of metabolites that exhibit a broad range of pharmacological activities and are synthesized through plant biosynthetic pathways comprised of complex enzyme activities and regulatory strategies. We have engineered yeast to produce the key intermediate reticuline and downstream BIA metabolites from a commercially available substrate. An enzyme tuning strategy was implemented that identified activity differences between variants from different plants and determined optimal expression levels. By synthesizing both stereoisomer forms of reticuline and integrating enzyme activities from three plant sources and humans, we demonstrated the synthesis of metabolites in the sanguinarine/berberine and morphinan branches. We also demonstrated that a human P450 enzyme exhibits a novel activity in the conversion of (R)-reticuline to the morphinan alkaloid salutaridine. Our engineered microbial hosts offer access to a rich group of BIA molecules and associated activities that will be further expanded through synthetic chemistry and biology approaches

Effect of Chronic Escitalopram versus Placebo on Personality Traits in Healthy First-Degree Relatives of Patients with Depression: A Randomized Trial

The serotonergic neurotransmitter system is closely linked to depression and personality traits. It is not known if selective serotonin reuptake inhibitors (SSRI) have an effect on neuroticism that is independent of their effect on depression. Healthy individuals with a genetic liability for depression represent a group of particular interest when investigating if intervention with SSRIs affects personality. The present trial is the first to test the hypothesis that escitalopram may reduce neuroticism in healthy first-degree relatives of patients with major depressive disorder (MD).The trial used a randomized, blinded, placebo-controlled parallel-group design. We examined the effect of four weeks escitalopram 10 mg daily versus matching placebo on personality in 80 people who had a biological parent or sibling with a history of MD. The outcome measure on personality traits was change in self-reported neuroticism scores on the Revised Neuroticism-Extroversion-Openness-Personality Inventory (NEO-PI-R) and the Eysenck Personality Inventory (EPQ) from entry until end of four weeks of intervention.When compared with placebo, escitalopram did not significantly affect self-reported NEO-PI-R and EPQ neuroticism and extroversion, EPQ psychoticism, NEO-PI-R openness, or NEO-PI-R conscientiousness (p all above 0.05). However, escitalopram increased NEO-PI-R agreeableness scores significantly compared with placebo (mean; SD) (2.38; 8.09) versus (-1.32; 7.94), p = 0.046), but not following correction for multiplicity. A trend was shown for increased conscientiousness (p = 0.07). There was no significant effect on subclinical depressive symptoms (p = 0.6).In healthy first-degree relatives of patients with MD, there is no effect of escitalopram on neuroticism, but it is possible that escitalopram may increase the personality traits of agreeableness and conscientiousness.Clinicaltrials.gov NCT00386841

Neuroendocrine–immune disequilibrium and endometriosis: an interdisciplinary approach

Endometriosis, a chronic disease characterized by endometrial tissue located outside the uterine cavity, affects one fourth of young women and is associated with chronic pelvic pain and infertility. However, an in-depth understanding of the pathophysiology and effective treatment strategies of endometriosis is still largely elusive. Inadequate immune and neuroendocrine responses are significantly involved in the pathophysiology of endometriosis, and key findings are summarized in the present review. We discuss here the role of different immune mechanisms particularly adhesion molecules, protein–glycan interactions, and pro-angiogenic mediators in the development and progression of the disease. Finally, we introduce the concept of endometrial dissemination as result of a neuroendocrine-immune disequilibrium in response to high levels of perceived stress caused by cardinal clinical symptoms of endometriosis