[Early-onset familial Alzheimer's disease with spastic paraparesis associated with PSEN1 gene]. / Rannyaya semeinaya bolezn' Al'tsgeimera so spasticheskim paraparezom, svyazannaya s genom PSEN1.

A familial case of a rare autosomal dominant Alzheimer's disease (AD), related to PSEN1 gene (AD3, OMIM 607822), differing from common multifactorial form by earlier onset and, in part of cases, by accompanying neurological signs, spastic paraparesis particularly, is presented. The first sign in a female proband and in her son was paraparesis manifested at the age of 29 and 21 years, respectively. Cognitive disturbances developed soon; the former diagnosis was hereditary spastic paraplegia with cognitive impairment, In the proband examined in 2008 at 33 years old the diagnosis was not established. In the son examined in 2022 at 27 years old whole-exome sequencing detected a novel PSEN1 missense mutation p.Thr421Ala. The mutation was confirmed by Sanger sequencing in him, found out in the proband (who was severely disabled by that time) and excluded in her unaffected mother. Except for different age of onset, AD3 in two patients was similar, though in whole it is variable, also in relatives. The variability and rareness of the disease hampers clinical diagnostics. Massive parallel sequencing is a most reliable diagnostic method.

Childhood adversities and risk of posttraumatic stress disorder and major depression following a motor vehicle collision in adulthood.

AIMS: Childhood adversities (CAs) predict heightened risks of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) among people exposed to adult traumatic events. Identifying which CAs put individuals at greatest risk for these adverse posttraumatic neuropsychiatric sequelae (APNS) is important for targeting prevention interventions. METHODS: Data came from n = 999 patients ages 18-75 presenting to 29 U.S. emergency departments after a motor vehicle collision (MVC) and followed for 3 months, the amount of time traditionally used to define chronic PTSD, in the Advancing Understanding of Recovery After Trauma (AURORA) study. Six CA types were self-reported at baseline: physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect and bullying. Both dichotomous measures of ever experiencing each CA type and numeric measures of exposure frequency were included in the analysis. Risk ratios (RRs) of these CA measures as well as complex interactions among these measures were examined as predictors of APNS 3 months post-MVC. APNS was defined as meeting self-reported criteria for either PTSD based on the PTSD Checklist for DSM-5 and/or MDE based on the PROMIS Depression Short-Form 8b. We controlled for pre-MVC lifetime histories of PTSD and MDE. We also examined mediating effects through peritraumatic symptoms assessed in the emergency department and PTSD and MDE assessed in 2-week and 8-week follow-up surveys. Analyses were carried out with robust Poisson regression models. RESULTS: Most participants (90.9%) reported at least rarely having experienced some CA. Ever experiencing each CA other than emotional neglect was univariably associated with 3-month APNS (RRs = 1.31-1.60). Each CA frequency was also univariably associated with 3-month APNS (RRs = 1.65-2.45). In multivariable models, joint associations of CAs with 3-month APNS were additive, with frequency of emotional abuse (RR = 2.03; 95% CI = 1.43-2.87) and bullying (RR = 1.44; 95% CI = 0.99-2.10) being the strongest predictors. Control variable analyses found that these associations were largely explained by pre-MVC histories of PTSD and MDE. CONCLUSIONS: Although individuals who experience frequent emotional abuse and bullying in childhood have a heightened risk of experiencing APNS after an adult MVC, these associations are largely mediated by prior histories of PTSD and MDE.

Recovery from DSM-IV post-traumatic stress disorder in the WHO World Mental Health surveys.

BACKGROUND: Research on post-traumatic stress disorder (PTSD) course finds a substantial proportion of cases remit within 6 months, a majority within 2 years, and a substantial minority persists for many years. Results are inconsistent about pre-trauma predictors. METHODS: The WHO World Mental Health surveys assessed lifetime DSM-IV PTSD presence-course after one randomly-selected trauma, allowing retrospective estimates of PTSD duration. Prior traumas, childhood adversities (CAs), and other lifetime DSM-IV mental disorders were examined as predictors using discrete-time person-month survival analysis among the 1575 respondents with lifetime PTSD. RESULTS: 20%, 27%, and 50% of cases recovered within 3, 6, and 24 months and 77% within 10 years (the longest duration allowing stable estimates). Time-related recall bias was found largely for recoveries after 24 months. Recovery was weakly related to most trauma types other than very low [odds-ratio (OR) 0.2-0.3] early-recovery (within 24 months) associated with purposefully injuring/torturing/killing and witnessing atrocities and very low later-recovery (25+ months) associated with being kidnapped. The significant ORs for prior traumas, CAs, and mental disorders were generally inconsistent between early- and later-recovery models. Cross-validated versions of final models nonetheless discriminated significantly between the 50% of respondents with highest and lowest predicted probabilities of both early-recovery (66-55% v. 43%) and later-recovery (75-68% v. 39%). CONCLUSIONS: We found PTSD recovery trajectories similar to those in previous studies. The weak associations of pre-trauma factors with recovery, also consistent with previous studies, presumably are due to stronger influences of post-trauma factors.

The associations of earlier trauma exposures and history of mental disorders with PTSD after subsequent traumas.

Although earlier trauma exposure is known to predict posttraumatic stress disorder (PTSD) after subsequent traumas, it is unclear whether this association is limited to cases where the earlier trauma led to PTSD. Resolution of this uncertainty has important implications for research on pretrauma vulnerability to PTSD. We examined this issue in the World Health Organization (WHO) World Mental Health (WMH) Surveys with 34 676 respondents who reported lifetime trauma exposure. One lifetime trauma was selected randomly for each respondent. DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, 4th Edition) PTSD due to that trauma was assessed. We reported in a previous paper that four earlier traumas involving interpersonal violence significantly predicted PTSD after subsequent random traumas (odds ratio (OR)=1.3-2.5). We also assessed 14 lifetime DSM-IV mood, anxiety, disruptive behavior and substance disorders before random traumas. We show in the current report that only prior anxiety disorders significantly predicted PTSD in a multivariate model (OR=1.5-4.3) and that these disorders interacted significantly with three of the earlier traumas (witnessing atrocities, physical violence victimization and rape). History of witnessing atrocities significantly predicted PTSD after subsequent random traumas only among respondents with prior PTSD (OR=5.6). Histories of physical violence victimization (OR=1.5) and rape after age 17 years (OR=17.6) significantly predicted only among respondents with no history of prior anxiety disorders. Although only preliminary due to reliance on retrospective reports, these results suggest that history of anxiety disorders and history of a limited number of earlier traumas might usefully be targeted in future prospective studies as distinct foci of research on individual differences in vulnerability to PTSD after subsequent traumas.

Post-traumatic stress disorder associated with sexual assault among women in the WHO World Mental Health Surveys.

BACKGROUND: Sexual assault is a global concern with post-traumatic stress disorder (PTSD), one of the common sequelae. Early intervention can help prevent PTSD, making identification of those at high risk for the disorder a priority. Lack of representative sampling of both sexual assault survivors and sexual assaults in prior studies might have reduced the ability to develop accurate prediction models for early identification of high-risk sexual assault survivors. METHODS: Data come from 12 face-to-face, cross-sectional surveys of community-dwelling adults conducted in 11 countries. Analysis was based on the data from the 411 women from these surveys for whom sexual assault was the randomly selected lifetime traumatic event (TE). Seven classes of predictors were assessed: socio-demographics, characteristics of the assault, the respondent's retrospective perception that she could have prevented the assault, other prior lifetime TEs, exposure to childhood family adversities and prior mental disorders. RESULTS: Prevalence of Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV) PTSD associated with randomly selected sexual assaults was 20.2%. PTSD was more common for repeated than single-occurrence victimization and positively associated with prior TEs and childhood adversities. Respondent's perception that she could have prevented the assault interacted with history of mental disorder such that it reduced odds of PTSD, but only among women without prior disorders (odds ratio 0.2, 95% confidence interval 0.1-0.9). The final model estimated that 40.3% of women with PTSD would be found among the 10% with the highest predicted risk. CONCLUSIONS: Whether counterfactual preventability cognitions are adaptive may depend on mental health history. Predictive modelling may be useful in targeting high-risk women for preventive interventions.

Using self-report surveys at the beginning of service to develop multi-outcome risk models for new soldiers in the U.S. Army.

BACKGROUND: The U.S. Army uses universal preventives interventions for several negative outcomes (e.g. suicide, violence, sexual assault) with especially high risks in the early years of service. More intensive interventions exist, but would be cost-effective only if targeted at high-risk soldiers. We report results of efforts to develop models for such targeting from self-report surveys administered at the beginning of Army service. METHODS: 21 832 new soldiers completed a self-administered questionnaire (SAQ) in 2011-2012 and consented to link administrative data to SAQ responses. Penalized regression models were developed for 12 administratively-recorded outcomes occurring by December 2013: suicide attempt, mental hospitalization, positive drug test, traumatic brain injury (TBI), other severe injury, several types of violence perpetration and victimization, demotion, and attrition. RESULTS: The best-performing models were for TBI (AUC = 0.80), major physical violence perpetration (AUC = 0.78), sexual assault perpetration (AUC = 0.78), and suicide attempt (AUC = 0.74). Although predicted risk scores were significantly correlated across outcomes, prediction was not improved by including risk scores for other outcomes in models. Of particular note: 40.5% of suicide attempts occurred among the 10% of new soldiers with highest predicted risk, 57.2% of male sexual assault perpetrations among the 15% with highest predicted risk, and 35.5% of female sexual assault victimizations among the 10% with highest predicted risk. CONCLUSIONS: Data collected at the beginning of service in self-report surveys could be used to develop risk models that define small proportions of new soldiers accounting for high proportions of negative outcomes over the first few years of service.

Posttraumatic stress disorder in the World Mental Health Surveys.

BACKGROUND: Traumatic events are common globally; however, comprehensive population-based cross-national data on the epidemiology of posttraumatic stress disorder (PTSD), the paradigmatic trauma-related mental disorder, are lacking. METHODS: Data were analyzed from 26 population surveys in the World Health Organization World Mental Health Surveys. A total of 71 083 respondents ages 18+ participated. The Composite International Diagnostic Interview assessed exposure to traumatic events as well as 30-day, 12-month, and lifetime PTSD. Respondents were also assessed for treatment in the 12 months preceding the survey. Age of onset distributions were examined by country income level. Associations of PTSD were examined with country income, world region, and respondent demographics. RESULTS: The cross-national lifetime prevalence of PTSD was 3.9% in the total sample and 5.6% among the trauma exposed. Half of respondents with PTSD reported persistent symptoms. Treatment seeking in high-income countries (53.5%) was roughly double that in low-lower middle income (22.8%) and upper-middle income (28.7%) countries. Social disadvantage, including younger age, female sex, being unmarried, being less educated, having lower household income, and being unemployed, was associated with increased risk of lifetime PTSD among the trauma exposed. CONCLUSIONS: PTSD is prevalent cross-nationally, with half of all global cases being persistent. Only half of those with severe PTSD report receiving any treatment and only a minority receive specialty mental health care. Striking disparities in PTSD treatment exist by country income level. Increasing access to effective treatment, especially in low- and middle-income countries, remains critical for reducing the population burden of PTSD.

Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

The 2013 US Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are not known to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male nondeployed Regular US Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naive Bayes, random forests, support vector regression and elastic net penalized regression) were explored. Of the Army suicides in 2004-2009, 41.5% occurred among 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100 000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded.

Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports.

Heterogeneity of major depressive disorder (MDD) illness course complicates clinical decision-making. Although efforts to use symptom profiles or biomarkers to develop clinically useful prognostic subtypes have had limited success, a recent report showed that machine-learning (ML) models developed from self-reports about incident episode characteristics and comorbidities among respondents with lifetime MDD in the World Health Organization World Mental Health (WMH) Surveys predicted MDD persistence, chronicity and severity with good accuracy. We report results of model validation in an independent prospective national household sample of 1056 respondents with lifetime MDD at baseline. The WMH ML models were applied to these baseline data to generate predicted outcome scores that were compared with observed scores assessed 10-12 years after baseline. ML model prediction accuracy was also compared with that of conventional logistic regression models. Area under the receiver operating characteristic curve based on ML (0.63 for high chronicity and 0.71-0.76 for the other prospective outcomes) was consistently higher than for the logistic models (0.62-0.70) despite the latter models including more predictors. A total of 34.6-38.1% of respondents with subsequent high persistence chronicity and 40.8-55.8% with the severity indicators were in the top 20% of the baseline ML-predicted risk distribution, while only 0.9% of respondents with subsequent hospitalizations and 1.5% with suicide attempts were in the lowest 20% of the ML-predicted risk distribution. These results confirm that clinically useful MDD risk-stratification models can be generated from baseline patient self-reports and that ML methods improve on conventional methods in developing such models.

Predicting non-familial major physical violent crime perpetration in the US Army from administrative data.

BACKGROUND: Although interventions exist to reduce violent crime, optimal implementation requires accurate targeting. We report the results of an attempt to develop an actuarial model using machine learning methods to predict future violent crimes among US Army soldiers. METHOD: A consolidated administrative database for all 975 057 soldiers in the US Army in 2004-2009 was created in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). Of these soldiers, 5771 committed a first founded major physical violent crime (murder-manslaughter, kidnapping, aggravated arson, aggravated assault, robbery) over that time period. Temporally prior administrative records measuring socio-demographic, Army career, criminal justice, medical/pharmacy, and contextual variables were used to build an actuarial model for these crimes separately among men and women using machine learning methods (cross-validated stepwise regression, random forests, penalized regressions). The model was then validated in an independent 2011-2013 sample. RESULTS: Key predictors were indicators of disadvantaged social/socioeconomic status, early career stage, prior crime, and mental disorder treatment. Area under the receiver-operating characteristic curve was 0.80-0.82 in 2004-2009 and 0.77 in the 2011-2013 validation sample. Of all administratively recorded crimes, 36.2-33.1% (male-female) were committed by the 5% of soldiers having the highest predicted risk in 2004-2009 and an even higher proportion (50.5%) in the 2011-2013 validation sample. CONCLUSIONS: Although these results suggest that the models could be used to target soldiers at high risk of violent crime perpetration for preventive interventions, final implementation decisions would require further validation and weighing of predicted effectiveness against intervention costs and competing risks.

The epidemiology of traumatic event exposure worldwide: results from the World Mental Health Survey Consortium.

BACKGROUND: Considerable research has documented that exposure to traumatic events has negative effects on physical and mental health. Much less research has examined the predictors of traumatic event exposure. Increased understanding of risk factors for exposure to traumatic events could be of considerable value in targeting preventive interventions and anticipating service needs. METHOD: General population surveys in 24 countries with a combined sample of 68 894 adult respondents across six continents assessed exposure to 29 traumatic event types. Differences in prevalence were examined with cross-tabulations. Exploratory factor analysis was conducted to determine whether traumatic event types clustered into interpretable factors. Survival analysis was carried out to examine associations of sociodemographic characteristics and prior traumatic events with subsequent exposure. RESULTS: Over 70% of respondents reported a traumatic event; 30.5% were exposed to four or more. Five types - witnessing death or serious injury, the unexpected death of a loved one, being mugged, being in a life-threatening automobile accident, and experiencing a life-threatening illness or injury - accounted for over half of all exposures. Exposure varied by country, sociodemographics and history of prior traumatic events. Being married was the most consistent protective factor. Exposure to interpersonal violence had the strongest associations with subsequent traumatic events. CONCLUSIONS: Given the near ubiquity of exposure, limited resources may best be dedicated to those that are more likely to be further exposed such as victims of interpersonal violence. Identifying mechanisms that account for the associations of prior interpersonal violence with subsequent trauma is critical to develop interventions to prevent revictimization.

Occupational differences in US Army suicide rates.

BACKGROUND: Civilian suicide rates vary by occupation in ways related to occupational stress exposure. Comparable military research finds suicide rates elevated in combat arms occupations. However, no research has evaluated variation in this pattern by deployment history, the indicator of occupation stress widely considered responsible for the recent rise in the military suicide rate. METHOD: The joint associations of Army occupation and deployment history in predicting suicides were analysed in an administrative dataset for the 729 337 male enlisted Regular Army soldiers in the US Army between 2004 and 2009. RESULTS: There were 496 suicides over the study period (22.4/100 000 person-years). Only two occupational categories, both in combat arms, had significantly elevated suicide rates: infantrymen (37.2/100 000 person-years) and combat engineers (38.2/100 000 person-years). However, the suicide rates in these two categories were significantly lower when currently deployed (30.6/100 000 person-years) than never deployed or previously deployed (41.2-39.1/100 000 person-years), whereas the suicide rate of other soldiers was significantly higher when currently deployed and previously deployed (20.2-22.4/100 000 person-years) than never deployed (14.5/100 000 person-years), resulting in the adjusted suicide rate of infantrymen and combat engineers being most elevated when never deployed [odds ratio (OR) 2.9, 95% confidence interval (CI) 2.1-4.1], less so when previously deployed (OR 1.6, 95% CI 1.1-2.1), and not at all when currently deployed (OR 1.2, 95% CI 0.8-1.8). Adjustment for a differential 'healthy warrior effect' cannot explain this variation in the relative suicide rates of never-deployed infantrymen and combat engineers by deployment status. CONCLUSIONS: Efforts are needed to elucidate the causal mechanisms underlying this interaction to guide preventive interventions for soldiers at high suicide risk.

The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity.

BACKGROUND: Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question. METHOD: Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes. RESULTS: Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6-72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors. CONCLUSIONS: Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.

Sociodemographic and career history predictors of suicide mortality in the United States Army 2004-2009.

BACKGROUND: The US Army suicide rate has increased sharply in recent years. Identifying significant predictors of Army suicides in Army and Department of Defense (DoD) administrative records might help focus prevention efforts and guide intervention content. Previous studies of administrative data, although documenting significant predictors, were based on limited samples and models. A career history perspective is used here to develop more textured models. METHOD: The analysis was carried out as part of the Historical Administrative Data Study (HADS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). De-identified data were combined across numerous Army and DoD administrative data systems for all Regular Army soldiers on active duty in 2004-2009. Multivariate associations of sociodemographics and Army career variables with suicide were examined in subgroups defined by time in service, rank and deployment history. RESULTS: Several novel results were found that could have intervention implications. The most notable of these were significantly elevated suicide rates (69.6-80.0 suicides per 100 000 person-years compared with 18.5 suicides per 100 000 person-years in the total Army) among enlisted soldiers deployed either during their first year of service or with less than expected (based on time in service) junior enlisted rank; a substantially greater rise in suicide among women than men during deployment; and a protective effect of marriage against suicide only during deployment. CONCLUSIONS: A career history approach produces several actionable insights missed in less textured analyses of administrative data predictors. Expansion of analyses to a richer set of predictors might help refine understanding of intervention implications.

The importance of secondary trauma exposure for post-disaster mental disorder.

BACKGROUND: Interventions to treat mental disorders after natural disasters are important both for humanitarian reasons and also for successful post-disaster physical reconstruction that depends on the psychological functioning of the affected population. A major difficulty in developing such interventions, however, is that large between-disaster variation exists in the prevalence of post-disaster mental disorders, making it difficult to estimate need for services in designing interventions without carrying out a post-disaster mental health needs assessment survey. One of the daunting methodological challenges in implementing such surveys is that secondary stressors unique to the disaster often need to be discovered to understand the magnitude, type, and population segments most affected by post-disaster mental disorders. METHODS: This problem is examined in the current commentary by analyzing data from the WHO World Mental Health (WMH) Surveys. We analyze the extent to which people exposed to natural disasters throughout the world also experienced secondary stressors and the extent to which the mental disorders associated with disasters were more proximally due to these secondary stressors than to the disasters themselves. RESULTS. Lifetime exposure to natural disasters was found to be high across countries (4.4-7.5%). 10.7-11.4% of those exposed to natural disasters reported the occurrence of other related stressors (e.g. death of a loved one and destruction of property). A monotonic relationship was found between the number of additional stressors and the subsequent onset of mental disorders CONCLUSIONS. These results document the importance of secondary stressors in accounting for the effects of natural disasters on mental disorders. Implications for intervention planning are discussed.

Lifetime co-morbidity of DSM-IV disorders in the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A).

BACKGROUND: Research on the structure of co-morbidity among common mental disorders has largely focused on current prevalence rather than on the development of co-morbidity. This report presents preliminary results of the latter type of analysis based on the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A). METHOD: A national survey was carried out of adolescent mental disorders. DSM-IV diagnoses were based on the Composite International Diagnostic Interview (CIDI) administered to adolescents and questionnaires self-administered to parents. Factor analysis examined co-morbidity among 15 lifetime DSM-IV disorders. Discrete-time survival analysis was used to predict first onset of each disorder from information about prior history of the other 14 disorders. RESULTS: Factor analysis found four factors representing fear, distress, behavior and substance disorders. Associations of temporally primary disorders with the subsequent onset of other disorders, dated using retrospective age-of-onset (AOO) reports, were almost entirely positive. Within-class associations (e.g. distress disorders predicting subsequent onset of other distress disorders) were more consistently significant (63.2%) than between-class associations (33.0%). Strength of associations decreased as co-morbidity among disorders increased. The percentage of lifetime disorders explained (in a predictive rather than a causal sense) by temporally prior disorders was in the range 3.7-6.9% for earliest-onset disorders [specific phobia and attention deficit hyperactivity disorder (ADHD)] and much higher (23.1-64.3%) for later-onset disorders. Fear disorders were the strongest predictors of most other subsequent disorders. CONCLUSIONS: Adolescent mental disorders are highly co-morbid. The strong associations of temporally primary fear disorders with many other later-onset disorders suggest that fear disorders might be promising targets for early interventions.

Days out of role due to common physical and mental conditions: results from the WHO World Mental Health surveys.

Days out of role because of health problems are a major source of lost human capital. We examined the relative importance of commonly occurring physical and mental disorders in accounting for days out of role in 24 countries that participated in the World Health Organization (WHO) World Mental Health (WMH) surveys. Face-to-face interviews were carried out with 62 971 respondents (72.0% pooled response rate). Presence of ten chronic physical disorders and nine mental disorders was assessed for each respondent along with information about the number of days in the past month each respondent reported being totally unable to work or carry out their other normal daily activities because of problems with either physical or mental health. Multiple regression analysis was used to estimate associations of specific conditions and comorbidities with days out of role, controlling by basic socio-demographics (age, gender, employment status and country). Overall, 12.8% of respondents had some day totally out of role, with a median of 51.1 a year. The strongest individual-level effects (days out of role per year) were associated with neurological disorders (17.4), bipolar disorder (17.3) and post-traumatic stress disorder (15.2). The strongest population-level effect was associated with pain conditions, which accounted for 21.5% of all days out of role (population attributable risk proportion). The 19 conditions accounted for 62.2% of all days out of role. Common health conditions, including mental disorders, make up a large proportion of the number of days out of role across a wide range of countries and should be addressed to substantially increase overall productivity.

[Ultrasound diagnosis of extrahepatic portal hypertension in chronic pancreatitis].

AIM: To evaluate the potential of the color duplex scanning in revealing of the portal hypertension in patients with chronic pancreatitis. MATERIALS AND METHODS: 94 patients with chronic pancreatitis were investigated. In 61 patients (65%) pancreatitis was complicated by extrahepatic portal hypertension (EHPH) and 31 patients (35%) were without signs of rising of the portal pressure. RESULTS: Investigations in B-regime have shown that in patients with EHPH chronic calculous pancreatitis was revealed in 48%, development of pancreatic hypertension in 75%, increase of the pancreas head up to more than 40 mm in 58% of patients. We did not reveal statistically significant differences in pseudo-cysts in pancreas, extension of extrahepatic and intrahepatic ducts and infiltrative changes in parapancreatic cellular tissue in patients with and without EHPH. A development of EHPH in 31 (51%) patients was preconditioned by an extravasal compression of veins of portal system, combination of extravasal compression with thrombosis was found in 11 (18%) patients, in 12 (20%) patients thrombosis of the magistral veins of portal system was revealed and in 7 (11%) patients hemodynamics was not changed. Resections were found to be preferable operations for recovery of portal circulation. Increase and normalization of portal circulation found after transversal section of pancreas (Beger operation, pancreo-duodenal resection, distal resection of pancreas). A tendency to normalization of the blood flow was observed after the Frey operation.

[The distal pancreatic resection with spleen preservation: which collaterals can we rely on?].

The spleen preservation by distal pancreatic resection can be performed either with spleen vessels preservation or with the ligation of the least. The experiment evolved ligation of all gastric arteries but the short gastric arteries in 20 cadaveric organocomplexes, followed by ink perfusion through the left gastric and left gastro-epiploic arteries. The study was amplified with the intraoperative dopplerography of portal arteries of the spleen after crossclamping of the left gastro-epiploic and short gastric arteries. Ten patients after distal pancreatic resection with spleen preservation and splenic vessels ligation had the CT-angiography before and after the surgery. All the conducted studies demonstrated the incapability of short gastric arteries to supply the satisfactory spleen perfusion. The left gastro-epiploic artery proved to be the main source of splenic blood supply after splenic vessels ligation.

Bipolar disorder with frequent mood episodes in the national comorbidity survey replication (NCS-R).

Virtually nothing is known about the epidemiology of rapid cycling bipolar disorder (BPD) in community samples. Nationally representative data are reported here for the prevalence and correlates of a surrogate measure of DSM-IV rapid cycling BPD from the National Comorbidity survey Replication (NCS-R), a national survey of the US household population. DSM-IV disorders were assessed in the NCS-R with the WHO Composite International Diagnostic Interview (CIDI). Although the CIDI did not assess rapid cycling, it did assess the broader category of 12-month BPD with frequent mood episodes (FMEs), having at least four episodes of mania/hypomania or major depression in the 12 months before interview. Roughly one-third of NCS-R respondents with lifetime DSM-IV BPD and half with 12-month BPD met criteria for FME. FME was associated with younger age-of-onset (of BP-I, but not BP-II) and higher annual persistence (73% of the years since first onset of illness with an episode) than non-FME BPD. No substantial associations of FME vs non-FME BPD were found with socio-demographics, childhood risk factors (parental mental disorders, other childhood adversities) or comorbid DSM-IV disorders. However, FME manic episodes had greater clinical severity than non-FME episodes (assessed with a fully structured version of the Young Mania Rating Scale) and FME hypomanic episodes had greater role impairment than non-FME episodes (assessed with the Sheehan Disability Scales). Whether these indicators of severity merely reflect attenuated effects of rapid cycling or independent effects of sub-threshold rapid cycling warrants further study given the high proportion of lifetime cases who met criteria for FME.