E-health tools are a new mechanism to expand patient care, allowing supplemental resources to usual care, including enhanced patient-provider communication. These applications to smoking cessation have yet to be tested in a hospitalized patient sample. This project aims to evaluate the effectiveness and cost-effectiveness of a tailored web-based and e-message smoking cessation program for current smokers that, upon hospital discharge, transitions the patient to continue a quit attempt when home (Decide2Quit).A randomized two-arm follow-up design will test the effectiveness of an evidence- and theoretically-based smoking cessation program designed for post-hospitalization.A total of 1,488 patients aged 19 or older, who smoked cigarettes in the previous 30 days, are being recruited from 27 patient care areas of a large urban university hospital. Study-eligible hospitalized patients receiving usual tobacco cessation usual care are offered study referral. Trained hospital staff assist the 744 patients who are being randomized to the intervention arm with registration and orientation to the intervention website. This e-mail and web-based program offers tailored messages as well as education, self-assessment and planning aids, and social support to promote tobacco use cessation. Condition-blind study staff assess participants for tobacco use history and behaviors, tobacco use cost-related information, co-morbidities and psychosocial factors at 0, 3, 6, and 12 months. The primary outcome is self-reported 30-day tobacco abstinence at 6 months follow-up. Secondary outcomes include 7-day point prevalence quit rates at 3-, 6-, and 12-month follow-up, 30-day point prevalence quit rates at 3 and 12 months, biologically confirmed tobacco abstinence at 6-month follow-up, and multiple point-prevalence quit rates based on self-reported tobacco abstinence rates at each follow-up time period. Healthcare utilization and quality of life are assessed at baseline, and 6- and 12-month follow-up to measure program cost-effectiveness from the hospital, healthcare payer, patient, and societal perspectives.Given the impact of tobacco use on medical resources, establishing feasible, cost-effective methods for reducing tobacco use is imperative. Given the minimal hospital staff burden and the automated transition to a post-hospitalization tailored intervention, this program could be an easily disseminated approach.Current Intervention Trial NCT01277250 The health effects of smoking tobacco and their economic impact are well documented . AlabamaCrossing the Quality Chasm, the Institute of Medicine began to emphasize that care should not occur just within face-to-face visits but that ‘access to care should be provided over the internet’ to foster continuous healing relationships [In onships . Subsequonships -11 and oonships , includionships , have coonships , computeonships . InnovatSecure patient-provider e-messaging systems have been found to improve patient satisfaction and increase practice efficiency while maintaining HIPAA standards ,17. The In a meta-analysis, 17% of web- and computer-based smoking cessation out-patient interventions were found effective in doubling quit rates at 6 months among general population participants compared to controls . Also, tThis study uses a randomized controlled two-arm multiple follow-up design to: (1) test the effectiveness of the Decide2Quit intervention against usual smoking cessation care for hospitalized patients transitioning to outpatient care; and (2) determine the cost-effectiveness of each component of a smoking cessation intervention for hospitalized smokers . The primary outcome for effectiveness is self-reported 30-day point prevalence at 6 month post-hospitalization. Secondary outcomes are: biologically confirmed smoking cessation at 6 months; 30-day point prevalence at 3 and 12 months; and 7-day point prevalence at 3, 6, and 12 months. Consecutive abstinence will be assessed using the three 30-day point prevalence data. The cost-effectiveness of the intervention compared to usual care will be determined by considering costs of intervention implementation and costs of healthcare with effectiveness measured in terms of Quality Adjusted Life Years (QALYs).This study has obtained approval from The University of Alabama at Birmingham (UAB) Institutional Review Board for Human Use (IRB). All study personnel are IRB trained and Health Insurance Portability and Accountability Act (HIPAA) certified.The setting for this study is UAB Hospital, a 1,000 bed state-of-the-art academic center hospital with 43 patient care areas (PCAs). Of these, 27 PCAs serve patients potentially eligible for study participation. The 16 PCAs not included in this study, maternity and palliative care units and some intensive care and psychiatric units , are excluded due to the difficulty of obtaining informed consent and/or the unique smoking cessation needs among the patients served. As well, we will over-recruit smokers with pulmonary and cardiac diseases, as this population is of primary interest to the study collaborative. While UAB Hospital has a non-smoking policy, and patients are expected to abstain from tobacco use while hospitalized, non-adherence to this policy has been noted in patients sufficiently mobile to go outdoors.The UAB Lung Health Center staff receive a daily report of all current smokers admitted to UAB Hospital during the previous 24 h to provide or facilitate the provision of tobacco cessation usual care at bedside . Eligible patients are provided an overview of the study and a chance to ask questions prior to providing written informed consent. After completion of baseline assessments and listing on the electronic study roll by study staff, patients are randomized to study condition . Blocked randomization within each PCA is used to reduce selection and accidental bias and achieve balance in the allocation of participants to treatment arms. The study statistician generated random number lists for each PCA prior to study initiation. The Study Coordinator identifies the participants to randomize to study condition each day based on their order of listing on the study roll and the allocation indicated for the PCA in which they were recruited. As participants are allocated to the intervention arm, the Study Coordinator sends email alerts to designated hospital staff (Quit Staff) that newly randomized patients need to be registered to the intervention website, Decide2Quit. Figure The intervention includes tailored e-mail messages and an interactive website (Decide2Quit) designed for post-hospitalization smoking cessation which allows secure messaging with a certified Tobacco Treatment Specialist (TTS) (Quit Advisor) and both in- and post-hospital contact by the hospital Quit Staff. The Quit Staff visit patients assigned to the intervention arm at bedside to assist them with registration to Decide2Quit using secure laptops connected to the website via the hospital’s WiFi system. The Quit Staff then orient the participants to the website by displaying general content areas and available quit tools. Participants also receive a booklet illustrating how to access and navigate the website. In addition, this booklet features study contact information for technical problems, blank copies of the website ‘quit plan’ , and a letter for their primary healthcare provider. This letter contains study-related information and requests the healthcare provider’s verbal and pharmaceutical (as appropriate) support of their patient’s quit attempt.Some patients randomized to the intervention are discharged from the hospital before the Quit Staff can visit them to provide website registration and orientation. The print materials are mailed to these participants and Quit Staff provide telephone assistance with website registration and orientation. The Quit Staff make one follow-up telephone contact, at 7 to 14 days post-discharge, to encourage website use in the context of the primary area of health concern the participant identified at website registration.Two behavioral change theories are the basis for both the website content and e-mail messages: Social Cognitive Theory  and the The health concern messages, sent weekly for 12 weeks, are based on the primary area of health concern identified by the participant at website registration . E-mail messages provide general information related to the selected health concern, without specifying protected health information. Outcome expectations and other theoretical constructs provide the basis for the messages. For example, someone selecting ‘surgery or wound healing’ would receive the message ‘Quitting smoking allows more blood with oxygen to reach wounds to help them heal faster’ while someone selecting ‘heart disease or stroke’ would receive ‘In just one day of quitting, you will have started to lower your risk of having a heart attack. Every day you stay quit, you lower your risk of having a heart attack more.’ Those choosing ‘none of these’ receive general health messages. Each message ends with promoting website use by providing the link to ‘learn more about ____'. Table This intervention website is a modification and refinement of an existing version of Decide2Quit which is the product of two Investigators’ prior NIH-funded research efforts to develop web-delivered smoking cessation systems for patients  and provMeetings with various hospital staff groups led to the identification of respiratory therapists as the most appropriate hospital staff (Quit Staff) for this study given their professional role in lung health and their hospital-wide duties. When the respiratory therapists’ duties preclude assisting with patient registrations, a hospital-paid smoking cessation staff provides this service. Quit Staff provided input into the development of the administrative portal they use to track contact with intervention participants, as well as practical suggestions for how best to implement this intervention in UAB Hospital. Quit Staff training includes a didactic overview of the study, information on specific protocols  and the website, and a hands-on computer training for the website, from both the patient and administrative perspectives.Survey data collection takes place at the hospital bedside for baseline and via telephone interview for the 3- , 6- and 12-months follow-up. Additional biologic measures are collected at 6-month follow-up as described below. Tables et al. CHART Overview paper). A random sample of self-reported past-7-day tobacco users are asked to provide saliva samples in the same manner as non-smokers. For past-7-days smokers, study staff check a random selection list to determine if the participant is selected to provide a biologic specimen. We anticipate this sample to be about 10% of the past-7-days smokers. At the time of the telephone interview, those participants who are to provide in-person biologic measures are scheduled to come into the clinic within the following 2 weeks. If a participant misses two scheduled clinic appointments, a saliva kit is mailed with follow-up attempts the same as for all mailed kits.At 6-month follow-up, participants are contacted by telephone and asked about their past-7-days’ smoking status. Participants reporting not smoking in the past 7 days and living within a 40-min commute are asked to come to the clinic for in-person saliva collection, for cotinine testing, as well as a Carbon Monoxide (CO) measure. Those living farther away are mailed saliva collection kits as described in the CHART biochemical verification study  recruitment and retention; 2) intervention delivery and dose; and (3) staff productivity. Study investigators review reports monthly to monitor study activities and make recommendations for remediation as needed. Reports include the proportion of patients participating (or lost) at each level of screening and study activity  and the group with all other diagnoses (expected n = 488) will have sufficient power  to detect a difference in tobacco abstinence rates of 9.4% (two-sided), assuming the three-diagnoses comparison group has a 25% quit rate (two-sided). Note that, as the smoking cessation rate increases for the comparison group, a larger difference is necessary between groups to achieve a specific level of power, which is why a higher rate is used for power computation. The reverse of this is true as well: as the comparison group rate decreases, a smaller difference between groups achieves the same level of power.Power is estimated for the primary outcome: differences in self-reported smoking abstinence rates between the two treatment conditions at 6 months post-hospitalization based on 30-day point prevalence. Rates for smoking cessation reported in the literature for ‘usual’ post-hospitalization care are 5% to 15% at 6 months and 7% to 10% at 1 year . With 1,P ≤ 0.05 will be considered significant for all analyses, except where Bonferroni correction for multiple comparisons is necessary. Baseline characteristics of both groups will be compared to ensure that random assignment results in comparable groups. Any factors not found balanced across randomization groups will be adjusted for in subsequent models. Continuous variables will be compared using a two-sample t-test, while a chi-square test of association will be used to compare categorical variables.The study analyses will be conducted using the most up-to-date version of SAS  and The primary outcome for this study will be self-reported 30-day tobacco abstinence rates at 6-months follow-up. For missing outcome data at the 6- and 12- months follow-ups, we will impute missing data using a propensity-based multiple imputation method  that hasWe will also run a responders-only analysis for descriptive purposes. A two-sample test for the difference in proportions will be used to test whether the quit rates are different between the two treatment conditions (two-sided) and, if indicated, whether the Decide2Quit intervention is effective in promoting smoking cessation compared to the usual care group (one-sided). We will conduct this same statistical analysis for secondary outcomes.vs all other diagnostic groups. Secondary exploratory analyses are planned to investigate a range of broader issues related to smoking cessation. An analysis similar to the primary analysis will test potential differential effects of the Decide2Quit intervention among diagnostic groups by comparing those patients with AMI, CHF, and/or pneumonia to patients not having these diagnoses. A third set of tests of proportions will compare each of the three diagnostic groups of interest in the intervention condition to their matching group in the usual care condition . The relationship between dose and smoking cessation will be examined using logistic regression tests, as we expect dose will not be normally distributed.Several covariates may affect the relationship between the intervention effect and the quit rate. Potential covariates include age, tobacco dependence, major health issue, number of diagnostic codes assigned at hospital discharge, race, smoking history, alcohol use, depressive symptoms, social support, use of other smoking cessation programs, and self-efficacy. Because participants are randomized to treatment arm, these potential covariates will theoretically be balanced across the two arms. However, the strength of the association between each of these covariates and the quit rate will be assessed in a logistic regression model. This analysis will provide the variables that are predictive of smoking cessation among all smokers and can be repeated to test for predictors among the three diagnostic groups  The cost-effectiveness will be conducted from the perspectives of the hospital, health care payers, patients, and society. Analyses will be conducted for the short-term of the trial and for the lifetime of participants using modeling techniques and data from the literature, using the established cost-effectiveness analyses measures common to participating CHART projects. Effectiveness will be measured using Quality Adjusted Life Years (QALYs) which will be calculated using the EQ-5D-5L . See TabIn addition, a non-parametric bootstrap method -46 will There is considerable research on smoking cessation among outpatients and among inpatients with respiratory or cardiac disease. However, for general inpatient smokers, there is little information on programs that transition to post-hospitalization and most have follow-up limited to less than 6 months. Rates of smoking cessation immediately post-hospitalization are high, but relapse rates are also high . ConceptIdentifying appropriate hospital staff to register patients for a smoking cessation program was a challenge in the current healthcare system. A strong interest in tobacco cessation and access to and familiarity with all areas of the hospital are considered essential. As hospital resources, environments, and staffing vary, different hospital personnel may be identified as most appropriate. After discussions with personnel on many levels and areas of this hospital, respiratory therapists were identified as the best fit. Regardless, having committed champions among the hospital staff, or even better dedicated hospital staff, is imperative for successful implementation and the institutionalization that leads to program sustainability.Given the unknown validity of self-reported health behaviors and the expense and difficulty of collecting biological specimens, this study also aims to determine the validity of self-reported smoking status for both self-reported quitters and non-quitters post-hospitalization. Participants are not informed of their selection for biological confirmation until after their quit status is assessed via telephone. We anticipate these findings will provide an algorithm for estimating true rates of smoking status from self-reported rates in future studies, increasing confidence in findings while reducing costs and allowing more precise measures of cost-effectiveness.A limitation of this study is that the intervention is designed for the general medical or surgical patient. We are not involving adolescents, acute psychiatric patients, and maternity patients as these individuals have unique needs. Ideally, we would include all smokers hospitalized within our medical hospital complex, to be able to meet the needs of every patient in the hospital population; however, given resource and time constraints, it is not feasible for this study. In the future, this website intervention could be expanded, similar to how this study’s website is an expansion of one originally developed for outpatients, to include messages and web pages tailored to meet the needs of these groups. As well, it could be tailored to specialty hospital populations. Another limitation of this study is potential selection bias given that a large proportion of our potential participant pool does not have internet access, a requirement for study participation. Those on the other side of the ‘digital divide’ may vary from our study sample in terms of smoking habits, concomitant tobacco use or other salient attributes. This limits the generalizability of the findings to this study to the proportion of the hospitalized population with internet and e-mail capability.We have developed a tailored web-based program in an effort to apply these new e-health tools to facilitate the transition of the hospitalized smoker to the outpatient arena. This study will examine the effectiveness and cost-effectiveness of this smoking cessation program that is facilitated by hospital staff and links the discharged patient to a certified TTS and the intervention program for as long as needed. If this program proves to be effective and cost-effective, it will be an approach that could easily be adopted by other hospitals.This study began recruitment July 17, 2011 and will continue to enroll participants until May 2013.AMI: Acute Myocardial Infarction; Audit-C: Alcohol Use Disorders Identification Test; CHART: Consortium of Hospitals to Advance Research on Tobacco; CHF: Congestive Heart Failure; CO: Carbon Monoxide; HIPAA: Health Insurance Portability and Accountability Act; HSI: Heavy Smoking Index; ICERs: Incremental cost-effectiveness ratios; IRB: Institutional Review Board for Human Use; NIH: National Institutes of Health; OOP: Out of Pocket; PCA: Patient Care Area; PHQ-2: Patient Health Questionnaire-2; QALYs: Quality Adjusted Life Years; SAS: Statistical Analysis Software; SEQ12: Smoking Self-Efficacy Questionnaire; SF-12: Short Form Health Survey (12-item); TTS: Tobacco Treatment Specialist; UAB: University of Alabama at Birmingham.The authors have no competing interests, either financial or otherwise.TKH and RS designed the website, participated in the study design, and helped draft the intervention description section of this manuscript. MP designed and drafted the cost-effectiveness methods. BZ ran the power analyses and designed the primary analyses methods. JAM participated in the design of some study methods and helped draft the manuscript. KFH and WCB conceived the study, developed the design, and drafted sections of the manuscript. All authors read and approved the final manuscript.Dr Houston received previous NIH-funding (R01CA129091 and R01DA017971) to develop the original Decide2Quit website intervention described herein. His experience with these previous efforts and ongoing internet-based tobacco interventions are influential in the design of this current study’s Decide2Quit intervention website.This work is funded by the National Institute on Drug Abuse at the National Institutes of Health (NIH) through cooperative agreement number 1U01DA031515.


Emerging attempts have been made to reduce operative trauma and improve cosmetic results of laparoscopic cholecystectomy. There is a trend towards minimizing the number of incisions such as natural transluminal endoscopic surgery (NOTES) and single-port laparoscopic cholecystectomy (SPLC). Many retrospective case series propose excellent cosmesis and reduced pain in SPLC. As the latter has been confirmed in a randomized controlled trial, patient's satisfaction on cosmesis is still controversially debated.The SPOCC trial is a prospective, multi-center, double blinded, randomized controlled study comparing SPLC with 4-port conventional laparoscopic cholecystectomy (4PLC) in elective surgery. The hypothesis and primary objective is that patients undergoing SPLC will have a better outcome in cosmesis and body image 12 weeks after surgery. This primary endpoint is assessed using a validated 8-item multiple choice type questionnaire on cosmesis and body image. The secondary endpoint has three entities: the quality of life 12 weeks after surgery assessed by the validated Short-Form-36 Health Survey questionnaire, postoperative pain assessed by a visual analogue scale and the use of analgesics. Operative time, surgeon's experience with SPLC and 4PLC, use of additional ports, conversion to 4PLC or open cholecystectomy, length of stay, costs, time of work as well as intra- and postoperative complications are further aspects of the secondary endpoint. Patients are randomly assigned either to SPLC or to 4PLC. Patients as well as treating physicians, nurses and assessors are blinded until the 7th postoperative day. Sample size calculation performed by estimating a difference of cosmesis of 20%  resulted in a number of 55 randomized patients per arm.The SPOCC-trial is a prospective, multi-center, double-blind, randomized controlled study to assess cosmesis and body image after SPLC.NCT 01278472:  Since the first laparoscopic cholecystectomy in 1985, the laparoscopic approach has emerged as the treatment of choice for symptomatic gallstone disease . AdvantaTraditionally laparoscopic cholecystectomy is performed with four ports. In an attempt to further reduce operative trauma and improve cosmetic results following laparoscopic cholecystectomy, there has been a trend toward minimizing the number of incisions and ports required. These new operative techniques are called natural orifice transluminal endoscopic surgery (NOTES) ,4 or sinA MEDLINE  search  using the keywords 'cholecystectomy' and 'single port', 'single incision', 'single site' or 'single provided 334 articles. However, there were only two randomized controlled studies which were published. These included a low number of patients and focused on postoperative pain ,8. CurreSPLC is regarded to provide excellent results in cosmesis with almost no visible scar ,13. Yet,Since the available devices for SPLC have been designed to enable an almost scarless procedure the hypothesis of cosmesis improvement has to be proven. No previously published RCT on this topic was designed with the focus on cosmesis. We therefore designed a double-blinded randomized controlled trial on SPLC versus 4PLC  evaluating cosmesis and body image as a primary endpoint.The SPOCC trial is a prospective, multi-center, double blinded, randomized controlled study comparing Single-Port laparoscopic cholecystectomy with 4-port conventional laparoscopic cholecystectomy in elective surgery for symptomatic cholecystolithiasis. Patients with an indication for an elective cholecystectomy are randomized for either (A) single-port laparoscopic cholecystectomy (SPLC) or (B) conventional 4-port laparoscopic cholecystectomy (4PLC). The hypothesis of this trial is that patients undergoing SPLC will have a better outcome in cosmesis and body image 12 weeks after surgery.The primary endpoint of the study concerns patient's satisfaction with cosmesis and body image 12 weeks after surgery. This endpoint is assessed using a validated cosmesis and body image score (CBIS) that was previously used in surgery for Crohn's disease  and in dThe secondary endpoint is a combination of several variables: the quality of life 12 weeks after surgery assessed by the validated Short-Form-36 Health Survey questionnaire , postopeA clinically relevant improvement of the cosmesis and body image score (CBIS)  is definInclusion criteria are- elective cholecystectomy- 18 years of age- ability to understand the study purpose (German language)- written informed consentExclusion criteria are- pregnant women- proven or suspected liver cirrhosis- coagulopathy (platelet count below 50'000/μl)- double medication on platelet antagonists - international normalized ratio (INR) below 1.4- Non-German speakers- patients who are unable to understand the study purpose.- family members of study investigators or employees of the participating centresTo prevent surgeon bias, the requirements to qualify as a surgeon are equal in both arms. Since the present study represents a so-called pragmatic randomised control trial , the stuParticipating centres are the Division of Visceral and Transplantation Surgery of the University Hospital Zurich and the Department of Surgery of the Cantonal Hospital in Winterthur, Switzerland.http://www.randomizer.at[Patients have to sign an informed consent in the outpatient clinic. Randomization is performed online .This study is conducted in accordance with the principles of the Declaration of Helsinki and 'good clinical practice' guidelines. The principal investigator has completed a course in 'good clinical practice' certified by the Swiss Agency for Therapeutic Products (Swissmedic). The independent medical ethics committee of canton Zurich  has approved the study protocol. This trial was registered at clinicaltrial.gov on January 14, 2011  on the left of the patient, the second assistant (facultative) on the right, the nurse near the right hand of the surgeon, and the monitor shoulder level to the patient. The endoscopic equipment in terms of optic, monitor, gas supply, suction device, graspers, monopolar hook and endobag are equal in both groups. For surgical disinfection of the skin iodopovidone is used.th congress of the Swiss Society of Surgery [A transumbilical straight 20 to 25 mm skin and fascia incision is performed  is introduced. The pneumoperitoneum is maintained at 10-12 mmHg. A 10 mm 45° long scope  is introduced. Now additional 5 mm trocars are placed under optical control subxyphoidal on the left side of the falciforme ligament and in the right lateral upper abdomen. These trocars are used as endograspers to retain the fundus and the infundibulum of the gallbladder. A further 10 mm reusable trocar is placed in the left middle abdomen. This trocar is used as dissection instruments, swabs and the endobag Figure . OptimalThe prevalence of diagnosed cholecystolithiasis is high: 14.4% in men and 25.3% in women. About half of these patients are symptomatic and therefore candidates for cholecystectomy [While many retrospective case series on SPLC are available ,10, onlyNCT01348620, NCT01094379). The majority of trials focus on postoperative pain or costs. One trial with the most extensive sample size (600-patients) investigates differences in morbidity .Currently 9 RCTs are registered in the international trial database  Table . Two triNCT00904865) while another study focuses on a combined primary endpoint consisting of quality of life assessed by SF-36, cosmesis and pain  (Table Cosmesis and body image (after 1 month) as a primary endpoint is considered in only one registered trial (NCT0133935-trial (The present SPOCC-trial has two specific advantages, such as the time point of cosmesis assessment 3 months after surgery, which represents a reasonable follow-up time point, using a validated questionnaire and scoring system . The secThe authors declare that they have no competing interests.DCS and SB drafted the manuscript. DCS, GL, CEO and SB designed the protocol and co-authored the writing of the manuscript. DAR contributed to the design of the protocol and calculation of the power of the study. All other authors participated in the design of the study and are local investigators in the participating centers. All authors were involved in editing the manuscript and approved the final text of the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2482/11/24/prepub


Although community pharmacists in the United Kingdom are expected to assess elderly patients' needs for additional support in managing their medicines, there is limited data on potentially useful assessment tools. We sought to evaluate a 13-item assessment instrument among community dwelling elderly patients, 65 years and above. The instrument is composed of a cognitive risk sub-scale of 6 items and a physical risk sub-scale of 7 items.The instrument was administered to elderly patients in a survey performed in a community to the west of Glasgow, Scotland. The survey recruited 37 participants, 31 from 4 community pharmacies and 6 patients whose medication management tasks were managed by the West Glasgow Community Health and Care Partnership (managed patients). Community pharmacists independently rated 29 of the 37 participants' comprehension of, and dexterity in handling their medicines. We assessed scale reliability, convergent validity and criterion validity. In sub-analyses, we assessed differences in scores between the managed patients and those recruited from the community pharmacies, and between multi-compartment compliance aid users and non-users. The instrument showed satisfactory internal consistency . There was significant strong negative correlation between the cognitive risk sub-scores and community pharmacists' assessment of comprehension ; and physical risk sub-scores and community pharmacists' assessment of dexterity . The Area Under the Receiver Operator Characteristic Curve  showed that the instrument had good discriminatory capacity . The best cut-off  was ≥4 . In the sub-analyses, managed patients had significantly higher cognitive risk sub-scores  compared to non-managed patients. There was a significant difference in total risk score  and cognitive risk sub-score  between users and non-users of multi-compartment compliance aids.This instrument shows potential for use in identifying elderly patients who may have problems managing their own medicines in the community setting. However, more robust validity and reliability assessments are needed prior to introduction of the tool into routine practice. Older people may have problems with self-management of their medicines and exhibit unintentional noncompliance, which may be caused by several risk factors such as a higher prevalence of chronic conditions, consumption of complex drug regimens, and age-associated physical, visual, and cognitive impairment . And whiThe United Kingdom National Health Service Community Pharmacy Contractual Framework and the Disability Discrimination Act require community pharmacists to support self-care, provide a medicines assessment and compliance service and to support aspects of social care home services in medication management for the elderly and those with disabilities -10. As sAn evaluation of the Community Pharmacy Contractual Framework in England and Wales found that only 29% of pharmacies were providing medicines assessment and compliance service and 21% provided support to social care home services . A recenA brief task-based Risk Assessment Tool (RAT) was developed at the Department of Pharmaceutical Sciences, University of Strathclyde in Glasgow, Scotland. It was a 19-item instrument developed as a hospital pharmacy-based pre-discharge assessment for elderly patients and those recovering from stroke ,14; Kusu; Kusu14;The present paper reports on further development of this instrument for use among elderly patients (65 years old and above) in community settings. We evaluated a modified version of the instrument with the aim of determining whether it is at least as good as an experienced community pharmacist, with knowledge of the patient, in assessing older patients' ability to manage their own medicines. Our primary objectives were to determine scale reliability and validate the instrument against community pharmacists' assessment of patients' ability to manage their medicines. Secondarily, we sought to compare RAT scores between patients receiving home care support with management of their medicines and other community dwelling elderly patients and between users and non-users of multi-compartment compliance aids.Administration of Medicines' scheme of the West Glasgow Community Health and Care Partnership. These were patients who had been assessed as unable to manage their own medicines and a social worker assumed responsibility for the medicines management tasks. Their medicines are dispensed in original packs with a Medication Administration Record chart that is completed daily by the carer after assisting the patient with his/her medicines.We performed a 4-week survey in July and August 2008. We included participants who were at least 65 years old and taking at least 4 different medications daily and were either receiving social care support for administration of their medication, or using multi-compartment compliance aids, or both. These are important risk factors for non-compliance and problems with self-management of medications, and therefore represented an attractive group in which to test the RAT. Patients who did not consent to participate in the survey were excluded. We conveniently selected 4 community pharmacies in the west of Glasgow, Scotland from which participants were sampled. We also purposively selected participants whose medication tasks were managed (managed patients) by the '®) filled with sweets. The labels were printed in Arial font, in 3 different sizes: 8, 10, and 12.We used a modified 13-item instrument with two sub-scales: 1) a cognitive risk sub-scale consisting of three comprehension questions, two motivation questions and one label-reading task and 2) a physical risk sub-scale consisting of six dexterity questions and one coordination question  involved in rating our participants were experienced community pharmacists, each with at least 15 years of community pharmacy practice experience, and were the regular pharmacists in charge of the pharmacies from which our patients were recruited.For criterion standards, participants were grouped into three "able" and "unable" categories defined as follows: 1) "able overall" (community pharmacists' score of 4 in both comprehension and dexterity assessments) and "unable overall" (score of less than 4 in either comprehension or dexterity assessments); 2) "able physically" (score of 4 in the dexterity assessment) and "unable physically" (score of less than 4 in the dexterity assessment); and 3) "able cognitively" (score of 4 in the comprehension assessment) and "unable cognitively" (score of less than 4 in the comprehension assessment). We opted to use the community pharmacists' assessment as our criterion standard because there was no alternative validated assessment tool in routine use in the participating community pharmacies.The data was entered into a database in Microsoft Excel 2007 and exported to STATA 10.0  for analysis. Participant characteristics were summarised, continuous data as medians and Inter-quartile Ranges (IQR) and nominal data as percentages. Bivarite analyses were conducted to compare characteristics between managed participants and those whose medicine taking was not managed (non-managed) and between multi-compartment compliance aid users and non-users, focussing on the non-managed participants.We used a Kruskal-Wallis test to determine whether there was a difference across ratings of participants' comprehension and dexterity by pharmacist. For scale reliability, Cronbach's alpha was computed for the total 13-item scale, physical risk and cognitive risk sub-scales. To investigate convergent validity, we used Spearman's correlation to determine the relationship between cognitive and physical risk sub-scores and community pharmacists' comprehension and dexterity scores respectively. Criterion validity was assessed by constructing Receiver Operator Characteristic (ROC) curves for the 13-item scale, and its component physical and cognitive risk sub-scales (against the respective criterion standards). We computed the Area Under the Curve ± Standard Error (AUC ± SE) and best cut-offs including sensitivity and specificity. The best cut-offs were defined as scores that produced the largest number of correctly classified participants.Bivariate analyses were conducted to compare total risk score, cognitive and physical risk sub-scores between managed patients and non-managed participants and between multi-compartment compliance aid users and non-users. Bivariate analyses were performed using the two-sample Wilcoxon Rank Sum test for continuous data and the Pearson chi-squared test or Fisher exact test for categorical data.All participants provided written informed consent. The Ethics Committee of the Department of Pharmaceutical Sciences, Strathclyde Institute of Pharmacy and Biomedical Sciences approved the study protocol. All procedures complied with the Declaration of Helsinki.Thirty-seven participants met the inclusion criteria and completed the interview. Of these, 8 were interviewed at home: the 6 managed patients and 2 others by preference. Of the 29 patients interviewed from the pharmacies, 6 (20.7%) were interviewed from the first two pharmacies each, 4 13.8%) from the third pharmacy and 13 (44.8%) from the fourth. Overall, the median (IQR) age was 76  years and number of medicines taken was 8 . About half (51.4%) of the participants were male. Twenty-two (59.4%) lived alone and of these 12 (54.5%) received routine social care support at their homes. The majority (70.3%) managed their medicines by themselves. Eighteen (48.6%) participants used multi-compartment compliance aids. Table 3.8% fromOverall, total risk score, cognitive risk sub-score and physical risk sub-score ranged from 0-15, 0-9 and 0-7 respectively. Participants had a median (IQR) total risk score of 4.0 , cognitive risk sub-score of 3.0  and physical risk sub-score of 0 .Cronbach's alphas were 0.792, 0.679 and 0.813 for the 13-item, cognitive risk, and the physical risk sub-scales respectively. Dexterity items "Can open 48 ml amber plastic with screw cap" and "Can open 100 ml glass bottle with normal cap" were constant in our analysis sample and were therefore dropped from the analysis  and dexterity  by pharmacist. 15 (51.7%) participants were classified as "able cognitively", 16 (55.2%) as "able physically" and 9 (31%) as "able overall". There was a significant negative correlation between cognitive risk sub-score and the community pharmacists' assessment of comprehension  and the physical risk sub-score and community pharmacists' assessment of dexterity .We obtained community pharmacists' assessments for the 29 (78.4%) participants who were interviewed in the pharmacies. There was no statistically significant difference in pharmacist ratings of participants' comprehension (χAUC ± SE (95% CI) were 0.71 ± 0.10 0.53, 0.87) for the cognitive risk sub-scale Figure  and 0.86, 0.87 foAlthough managed participants had worse scores compared to the other community dwelling patients, only the cognitive risk sub-score difference was statistically significant Table . The difTypical scores for the participants in our study were better than those in the prior studies that employed the instrument in elderly hospitalised patients (with or without stroke) and those with rheumatoid arthritis -15; Kusu; Kusu15;Internal consistency was used as a measure of scale reliability. The Cronbach's alphas obtained for the 13-item scale and the physical risk sub-scale were above the indicative value of 0.70 for acceptable internal consistency . If usedAs with one previous study , a strong negative correlation between the instrument scores and the community pharmacists' assessment shows that there is agreement between the community pharmacists' assessments and the instrument. The ROC analysis (the AUC and 95% CI obtained) indicates that the full 13-item scale has good discriminatory capability. However, the wide 95% CI for the AUC for sub-scales with the lower bounds tending towards 0.5 imply that in some patients, the sub-scales used alone may not have good discriminatory capability. We found that a cut-off  total risk score of ≥4  would be the best value for screening purposes. The cut-offs obtained in our study were much lower than those in earlier studies among hospitalised elderly patients  and thosDifferences in scores between managed patients and other patients only resulted from the cognitive risk sub-scale. Managed participants had good physical risk scores, similar to other community dwelling elderly patients, implying that they are able to manage administration tasks just as well. Inability to self-manage medicines appears to have been the result of cognitive impairment (such as forgetfulness), which has been associated with unintentional non-adherence in the elderly ,19. Our Only total risk score and cognitive risk sub-score were significantly worse for multi-compartment compliance aid users compared to non-users, suggesting that multi-compartment compliance aids should be considered in elderly patients with cognitive impairment, as a memory prompt, on condition that they are physically capable of self-administration. In this way, a patient who scores poorly on both physical and cognitive sub-scales would not be considered a candidate for multi-compartment compliance aid use and alternative means of medication support would be sought. However a patient who has poor scores on the cognitive sub-scale and good scores on the physical sub-scale would benefit from multi-compartment compliance aid use.There are strengths inherent in the use of this instrument. It is a multidimensional instrument, covering several factors associated with the inability of patients to self-manage their medicines. The short time (15 to 20 minutes) it takes to conduct the assessment should be a welcome positive for practitioners as well as patients. Item 1, in the cognitive domain is based on a validated measure of cognitive function, the Abbreviated Mental Test . The phyOur study was limited by a small sample size, which could have compromised our ability to make definitive statements on the psychometric properties of the instrument. In addition, the comparison of scores between managed and non-managed patients is limited by the fact that there were only 6 managed patients. Community pharmacists set up opportunist interviews and appointments. As such we did not gather the data how many they approached to make the 31 community participants; and we could only trace 6 managed participants through the WGCHCP records. And because we neither used a pre-validated instrument for the community pharmacists' assessments, nor conducted inter-rater reliability across pharmacists, further studies are needed to validate this tool against more robust instruments. We used a conservative definition of polypharmacotherapy (4 or more medicines). Our results showed that the median (IQR) number of medicines used by our patients was much higher, 8 (6-10), ranging from 4-21. Our study therefore might have been biased by lower risk patients in terms of the number of medicines taken. Although our study demonstrated an association between cognitive risk sub-scores and both multi-compartment compliance aid use and social care support with medicines management, there are no differences between patients in the physical risk domain of the tool. Therefore we are unable to determine, using the tool, exactly which patients would be candidates for either social care support or multi-compartment compliance aids. In spite of this, we found that typical scores in "managed" participants are worse than those who use multi-compartment compliance aids (6.5 versus 4.0). We can therefore discern that patients with much worse scores may be considered for social care support, as opposed to multi-compartment compliance aids.There are limitations inherent in the tool itself. The questions concerning motivation  rely on the participant providing an honest answer. The question "what medications do you take at the moment?" assesses people's knowledge of their medicines. There are various dimensions to a patient's knowledge of their medicines, and the evidence linking knowledge of medicines to adherence and ability to self-manage medicines is at best conflicting .The instrument shows potential for use in identifying the limitations that older patients in the community may have with managing their medicines. With further modifications such as removal of items without discriminatory capacity, validation with a larger sample size and against more robust self-medication management assessment instruments, and determination of optimal cut-offs to distinguish between patients requiring home care medication management support or compliance aids, the tool could be considered for introduction into routine community practice.The authors declare that they have no competing interests.SJL participated in designing the study, collecting data, performing statistical analysis and drafting the manuscript. IM conceived the study, participated in designing the study, collecting data and revising the manuscript. JBB participated in performing statistical analysis and revising the manuscript. All authors read and approved the final manuscript.13-item self-medication Risk Assessment Tool.Click here for file


The aims of the present study were to investigate clinically relevant patient and environment-related predictive factors for threats and violent incidents the first three days in a PICU population based on evaluations done at admittance.In 2000 and 2001 all 118 consecutive patients were assessed at admittance to a Psychiatric Intensive Care Unit (PICU). Patient-related conditions as actuarial data from present admission, global clinical evaluations by physician at admittance and clinical nurses first day, a single rating with an observer rated scale scoring behaviours that predict short-term violence in psychiatric inpatients (The Brøset Violence Checklist (BVC)) at admittance, and environment-related conditions as use of segregation or not were related to the outcome measure Staff Observation Aggression Scale-Revised (SOAS-R). A multiple logistic regression analysis with SOAS-R as outcome variable was performed.The global clinical evaluations and the BVC were effective and more suitable than actuarial data in predicting short-term aggression. The use of segregation reduced the number of SOAS-R incidents.In a naturalistic group of patients in a PICU segregation of patients lowers the number of aggressive and threatening incidents. Prediction should be based on clinical global judgment, and instruments designed to predict short-term aggression in psychiatric inpatients.NCT00184119/NCT00184132 Threatening and violent behaviour by psychiatric inpatients are major concerns in psychiatric practice ,2. AggreIn Psychiatric Intensive Care Units (PICUs) and emergency services violent incidents are frequent and short-term predictions of violence important . PatientDifferences in methods, designs, outcome measures and settings make it difficult to compare studies of short-term prediction of violence. The weaknesses in most designs are underreporting of incidents, lack of correction for therapeutic interventions, and a disregard of the influence from the treatment environment ,9. EnvirRating scales specifically developed to measure frequency and severity of violent or threatening incidents, a prospective research design, and control of environment-related conditions and treatment factors are believed to minimize the problems in research methods.The frequency of threatening and violent incidents differs with the stages of psychiatric disorders . The higThe aims of the present prospective study were to investigate clinically relevant patient and environment-related predictive factors for threatening and violent incidents the first three days in a psychiatric acute emergency population based on evaluations at admittance. These patient-related conditions are actuarial data , assessments of symptoms, function and behaviour, therapeutic interventions the first day, global clinical impression assessed by physician on duty, global clinical impression assessed by treating nurses, and predictive properties from a single BVC rating at admittance; while the environment-related condition is the use of the PICU as a segregation area or not.The psychiatric department at St. Olavs University Hospital, Trondheim, Norway has a catchment area of 140.000 inhabitants. About 700 patients above 18 years with acute psychiatric conditions are admitted each year. Norwegian acute psychiatric emergency services are publicly funded and available to everyone. All the patients in the catchment area are admitted to this department. Acute admissions to other psychiatric hospitals occur only if inhabitants temporarily reside outside the catchment area when the need for acute admittance arises.The acute department consists of two ordinary closed emergency wards each with a PICU area with 4 beds. The patients were admitted to the acute ward with most free capacity. One ward was used for the study, and the patients excluded from the study were admitted to the other ward.The physician on duty evaluated all the patients acutely admitted to the ward. Patients assessed to be in need of PICU were admitted to the PICU area and included in the study except those with dementia, mental retardation or autism to a severe degree, and patients not speaking Norwegian or English. They were excluded at evaluation before entering the PICU area and admitted to the other ward.2) and a PICU area (190 m2). The main entrance leads to the ordinary area of the ward. In the end of the corridor a locked door separates the PICU area from the ordinary area. The PICU area consists of two wings with two single patient rooms in each. The patients stay mostly in the wings together with nurses, and contact with other patients is limited. The PICU area thus provides segregation from other persons. A sketch of the ward is published previously [The study ward consists of an ordinary closed acute ward area  for schizophrenia  with timViolent or threatening incidents were recorded with the Staff Observation Scale-Revised (SOAS-R) ,24. The Therapeutic- and control steps taken and nurses' observations were coded on a 23-item checklist. These therapeutic steps and observations included for instance "frequency of testing out and pushing limits", "intensity of testing out and pushing limits", "need to set limits", all prescribed medication, side effects, formal restrictions (restrictions regarding visits and telephone), staff contact time, use of newspapers, and visits from relatives. Depending on the type of item each were scored on scales 0-4  or 0-1 . Specially trained unit nurses did all the ratings. The first rating with the items "frequency of testing out and pushing limits", "intensity of testing out and pushing limits", and "need to set limits" was used as a possible predictor after an initial, short observation of the patient's behaviour at admittance and right after entrance to the PICU in order to evaluate whether the experienced staff's assessments of the patients' immediate behaviour could predict SOAS-R incidents for the rest of the study period.At admittance the physician on duty evaluated the patients' need for PICU on a scale with scorings 1-4 (1 representing no need to 4 representing absolute need). Four categories of reasons for admittance to PICU were noted . If more than one reason was present, the physician indicated the dominating category. "Physician's prediction" is an index defined by giving the patients with category 4 reason for admittance the scorings on "patients' need" of PICU, and the rest of the patients value 0. "Physicians prediction" therefore has scorings 0-4 with increasing value indicating increasing assumed probability for violent or threatening incidents.The patients were systematically examined for substance use at admittance, at evaluation with ward psychiatrist the first weekday after admittance, and at discharge from PICU. In the first period (November 13 2000 to March 25 2001) (n = 56), urine samples were analysed on clinical suspicion of substance use. In the second period (October 1 2001 to March 21 2002) (n = 62), all admitted patients had urine- and blood samples taken within a few hours after admission.Diagnoses according to ICD-10 Diagnostic criteria for research  were setAll data were analysed using the Statistical Package for the Social Sciences (version 11.0). Demographic and clinical variables were described using means and frequencies. Independent t-tests were used to compare differences between groups. Multiple logistic regression forced-entries were performed to examine the extent of the predictor variables' associations with SOAS-R incidents. The variable SOAS-R was categorised as incidents and non-incidents. Relative risk (RR) was calculated with Fischer's exact test and a generalized mixed model with Poisson distribution of SOAS-R incidents. The missing values were replaced with the mean score for each item. Statistical significance was defined as a two-tailed p < 0.05.The study was approved by "The Regional Medical Research Ethics Committee, Central Norway."In the two inclusion periods 56 and 62 patients were included. Mean length of stay in the PICU was 5.6 days (SD 0.6). One patient was excluded due to senile dementia. The number of males/females was 66/52 with mean age 36.3 years (SD 14.7). Fifty-seven (48.3%) were involuntarily admitted. The number of patients in each category of reasons for admittance to PICU were: Patient's own wish 3 (2.5%); Need of close observation from diagnostic or medical reasons 51 (43.2%); Reduction of stimuli 23 (19.5%); and Control of behaviour 40 (33.9%). The patients admitted to PICU due to "control of behaviour" had a mean need for stay = 3 . The first three days a total of 3 (inclusion 1) (the PICU-condition with complete segregation) and 19 (inclusion 2) (the PICU-condition without complete segregation) , 95% CI: 1.69-19.33) violent or threatening incidents were recorded among 3 (inclusion 1) (complete segregation) and 10 (inclusion 2) patients (11%)  (Fischer's exact test), 95% CI: 0.81-20.10). The effect for segregation indicates that patients who were not segregated were 3.0 times more likely to engage in a violent incident than those who were segregated.The mean SOAS-R severity score for these incidents was 10.1 (SD 14.7). The distribution of scores of SOAS-R -incidents and no SOAS-R-incidents, were found to have a mean of 0.11 (SD = .031). The number of serious incidents defined as SOAS-R severity score ≥ 9 was 16. The incidents with severity scores <9 were all verbal threats directed towards staff. Mechanical restraints (belts) were used twice in each inclusion period.The main diagnoses were F 00-09  6, F 10-19 (substance abuse) 24, F 20-29 (schizophrenia) 45, F 30-39 (mood disorders) 22 and F 40+  21. Nine patients (coded F 20-29) fulfilled criteria for both schizophrenia and substance abuse diagnoses. The prevalence of different substances used by the patients in the present department is published previously .Due to the limitations in the number of variables in the multiple regression analysis, the individual variables of possible interest were analysed for possible contribution to SOAS-R incidents with chi square tests for categorical and Student's T-tests for continuous data. PANSS total, PANSS subscales, GAF-S, medication, side effects, "frequency of testing out and pushing limits", "intensity of testing out and pushing limits", "need to set limits", gender and age did not contribute significantly. The items BVC, "Segregation" and "Physicians prediction" items were selected for subsequent multiple logistic regression forced-entry analyses Table . A furth2 (58%) indicates that the model contributes powerfully to the prediction of the SOAS-R incidents or non-incidents. The variables BVC, "Physicians prediction", and "Segregation" contribute significantly to predict SOAS-R incidents. The equation did not find statistically significant associations between SOAS-R (incidents or non-incidents) and a diagnosis of schizophrenia or substance abuse. The Hosmer-Lemeshow test was non-significant indicating that the fit of the model was good (p = 0.55).A multiple logistic regression forced-entry analysis was performed on SOAS-R as outcome variable and the five predictors: BVC, "Physicians prediction", "Segregation", and diagnosis of schizophrenia or substance abuse. The results are given in Table The present study gives evidence for a positive effect of segregation quantitatively determined in relation to other variables. We are not aware of the presence of such evidence so far. This finding is highly relevant for both clinical practice and the design of psychiatric wards. Effects of ward space and architecture are sparsely studied. Palmstierna et al found that patients with schizophrenia were more likely to be aggressive in a crowded ward . In a seOur data predicting short-term violent and aggressive incidents in a PICU are in accordance with previous studies from acute wards. Generally the predictive values from actuarial data are limited. The global clinical evaluation "Physicians prediction" from physician on duty, and the observer-rated scale scoring behaviours predicting imminent violence in psychiatric inpatients (BVC), were more suitable for predicting short-term violent and threatening incidents in the PICU setting. Since BVC is based on observer rated scorings of behaviour, the present study demonstrates that experienced staff members in acute settings are able to globally predict short-term violence in their patient populations.We found no association between SOAS-R ratings and psychopathology measured by PANSS total, PANSS subscales, and GAF-S. This finding is similar to Swett et al's . SteinerThe observer rated instrument BVC is based on reports of the most frequent behaviours observed prior to violent incidents, and it assesses the presence or absence of the six behavioural states confusion, irritability, boisterous behaviour, verbal threatening, physical threatening, and attacking objects . It has Involuntary admission status did not predict SOAS-R incidents in the present study. This finding is contrary to Nijman et al.'s who found a history of involuntary admission to be a predictor of aggressive behaviour . This maDiagnoses of substance use or schizophrenia are reported to be predictive factors for aggressive incidents ,28-30. TSeveral studies with different interventions have been conducted to assess the effects of preventive measures on aggressive incidents . ConclusThis study has weaknesses. "Physicians prediction" is an index composed of the physician on duty's global impression of the patients need and reason for admittance to PICU. This is not a validated instrument, but reflects the main outcome of what goes on in the mind of the experienced clinician. The nurse-rated 23-item checklist "Therapeutic- and control steps taken and nurses' observations" has similar shortcomings. The SOAS-R incidents are few, but comparable to other studies. The mean severity score of the incidents is moderate.The study sample is a consecutive, highly-selected sample of acutely admitted patients assessed in a PICU. The methods and facilities used for emergency psychiatry differ between countries . This spSegregation of patients raises ethical and legal questions. During the last years there have emerged new legislations, recommendations, court cases and professional guidelines to control the use of coercive measures in psychiatry. The recurring message in all of these guidelines is the need to practice caution when applying segregation in the form of seclusion . The preThe strengths of the study are numerous. First of all this is a prospective design in a naturalistic patient population from a defined catchment area. We have used robust validated instruments assessing symptoms, general psychopathology, function, behaviours and end-point measure. The routine screening for substance abuse was comprehensive. Therapeutic and control steps taken the first day were assessed. The degree of potential under-reporting of aggressive or threatening incidents is limited due to the prospective design and daily prompting for registrations. Finally the influence of the physical environment is incorporated in evaluation.In the psychiatric emergency setting the procedure of segregation of single patients predicts lowered numbers of short-term aggressive incidents. Predictions at admittance should further be based on a global clinical evaluation from the physician at admittance, or rating with instruments designed to predict short-term aggression in psychiatric in-patients like the Brøset Violence Checklist.The authors declare that they have no competing interests.AEV, VCI, GM, JCF and OML conceived and designed the study. VCI and AEV coordinated the study including the inclusion of patients. TP analyzed and interpreted the data. All authors helped to draft the manuscript, and all authors read and approved the final version.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/11/44/prepub


Individuals II-1 and II-6 from family 1 presented in the mid-1980s to the University of Utah Medical Center. These boys had a striking similarity to each other, with a range of shared clinical manifestations, but the disease they presented with was not a recognized syndrome. Both boys subsequently died in infancy. X-linked inheritance was confirmed in the next generation, when individuals III-4 and III-7 presented with the same disease. Their aged appearance was the most striking part of the disease.We describe two parallel genetic research efforts that converged on the same gene variant. Exon capture was carried out on samples from two families, using a commercially available in-solution method (Agilent’s SureSelect Human X Chromosome kit) as per the manufacturer’s guidelines with minor modifications to generate sequencing libraries (Illumina). We also used a recently developed tool, the Variant Annotation, Analysis and Selection Tool (VAAST), which identifies disease-causing variants, to analyze the exon capture data from family 1. Our analysis applied a disease model that did not require complete penetrance or locus homogeneity. We restricted the expected allele frequency of putative disease-causing variants within the control genomes to 0.1% or lower. The background file used in the analysis is composed of variants from dbSNP (version 130), 189 genomes from the 1000 Genomes Project, the 10Gen Data Set, 184 Danish exomes and 40 whole genomes from the Complete Genomics Diversity Panel. VAAST candidate gene prioritization analysis was performed using the likelihood ratio test under the dominant inheritance model, assuming an expected allele frequency of 0.1% or lower for the causal variant in the general population. After masking out loci of potentially low variant quality, single nucleotide variations in each gene were scored as a group. The significance level was assessed using individual permutation tests.NAA10, which encodes the catalytic subunit of the major human amino-terminal acetyltransferase . More recently, we became aware that a parallel effort on a second unrelated family converged on the same variant. The absence of this variant in controls, the amino acid conservation of this region of the protein, the predicted disruptive change and the co-occurrence in two unrelated families with the same rare disorder suggest that this is the pathogenic mutation. We confirmed this by demonstrating that the mutant hNaa10p had significantly impaired biochemical activity, and we therefore conclude that a reduction in acetylation by hNaa10p causes this disease.We identified a family with a previously undescribed lethal X-linked disorder of infancy comprising a distinct combination of an aged appearance, craniofacial anomalies, hypotonia, global developmental delays, cryptorchidism, cardiac arrhythmia and cardiomyopathy. We used X-chromosome exon sequencing and a recently developed probabilistic disease-gene discovery algorithm to identify a missense variant in This is one of the first uses of next-generation sequencing to identify the genetic basis of a previously unrecognized X-linked syndrome. It is also the first evidence of a human genetic disorder resulting from direct impairment of amino-terminal acetylation, one of the most common protein modifications in humans. We have also demonstrated that a probabilistic disease-gene discovery algorithm (VAAST) can readily identify and characterize the genetic basis of this syndrome.


The multiplexing becomes the major limitation of the next-generation sequencing (NGS) in application to low complexity samples. Physical space segregation allows limited multiplexing, while the existing barcode approach only permits simultaneously analysis of up to several dozen samples.Here we introduce pair-barcode sequencing (PBS), an economic and flexible barcoding technique that permits parallel analysis of large-scale multiplexed samples. In two pilot runs using SOLiD sequencer (Applied Biosystems Inc.), 32 independent pair-barcoded miRNA libraries were simultaneously discovered by the combination of 4 unique forward barcodes and 8 unique reverse barcodes. Over 174,000,000 reads were generated and about 64% of them are assigned to both of the barcodes. After mapping all reads to pre-miRNAs in miRBase, different miRNA expression patterns are captured from the two clinical groups. The strong correlation using different barcode pairs and the high consistency of miRNA expression in two independent runs demonstrates that PBS approach is valid.By employing PBS approach in NGS, large-scale multiplexed pooled samples could be practically analyzed in parallel so that high-throughput sequencing economically meets the requirements of samples which are low sequencing throughput demand. Next-generation sequencing (NGS) technologies which are widely employed in life science research, are transforming the biology. In one In order to relieve the mismatch between the high throughput of NGS technologies and the low throughput requirement of the low complex samples, most NGS technologies provide physically segregated sequencing mediums. But the physical segregation allows accommodation of limited independent samples, and obscures available sequencing space in some NGS technologies. BarcodeMicroRNAs (miRNAs) are an evolutionarily conserved class of small, approximately 22-nucleotide (nt) non-coding RNAs that regulate global gene expression patterns,14 and pIn our method, a pair of molecular barcodes of 6nt in length is designed at the two sides of the target sequences and is introduced to the libraries by adaptor ligation and PCR. We demonstrate the power of PBS by sequencing a pool of 32 human miRNA libraries on the SOLiD V2 platform (Applied Biosystems Inc.). 26 of these libraries were derived from human breast cancer cancerous tissues (BC) and 6 were derived from human breast noncancerous tissues (BO). Four unique forward barcodes (F-barcode) and eight unique reverse barcodes (R-barcode) were used to code the 32 samples. Additionally, we evaluate the correlation of different barcode pairs by performing technical replicates of the same sample with 16 different barcode pairs, and verified the reproducibility of the method by operating two independent sequencing run of the same pool of samples. After decoding and mapping, about 64% of the reads mapped to both of the two barcodes uniquely and 15.3% of decoded reads were identified to non coding RNAs on average. The peak read length of the reads recognized as miRNAs located at 21-22nt, indicating that the mature miRNAs were enriched in the samples and well sequenced. A total of 22 miRNAs were differentially expressed between the BC libraries and BO libraries. To the best of our knowledge, this is the first study to discover miRNAs from large-scale multiplexed samples using a pair of barcodes in NGS.In order to substantially enhance the scope and capacity of multiplexed high-throughput sequencing, a pair of barcodes for 6nt each was designed in two sides of miRNAs. The F-barcodes were devised at the 5' end of the F-adaptors, and were introduced to the libraries by ligating the F-adaptors to miRNAs Figure . The R-bAs one mismatch is tolerated in barcode mapping, it is impossible to get uniquely mapped reads if all permutations of 6 nucleotides are allowed to be barcodes. In order to get uniquely mapped reads, each barcode should be different with each other in at least three positions. Moreover, because the mapping of SOLiD reads is operated in the color space, the barcodes are designed to be different with each other in at least two positions in the color space, not in the nucleotide space.After the sequencing reactions, 89175789 barcoded sequences were obtained in the sequencing run I, while 85344522 barcoded sequences were obtained in the sequencing run II. 71.3% and 70.4% of the obtained barcoded sequences were mapped to the 4 F-barcodes used in the libraries generation, respectively. And 89.7% and 91.4% of the F-barcode mappable sequences were mapped to the 8 R-barcodes introduced in the PCR reactions, separately. In total, 64.0% and 64.4% of the obtained sequences were mapped to a used F-barcodes and a used R-barcodes at the same time. The reads mapped to each combination of F-barcodes and R-barcodes are counted and exhibited in Table Composition of each library was determined by filtering all decoded reads to human genome. MiRNAs were identified by mapping reads to pre-miRNAs in miRBase and quantified by mapping reads to mature miRNA in miRBase. About 46% of the decoded sequences were mappable using SOLiD system small RNA analysis pipeline tool   were shown in Additional file We also analyzed miRNAs previously reported to be differentially expressed in BC, including oncogenic miRNAs, miR-155, miR-21,19, miR-t-test  is at the same level of other work . The reaQuantile-quantile normalization was used to normalize raw read counts to remove potential bias in miRNA expression across the datasets. The quantile-quantile normalization has been used to normalize the raw read counts of NGS and shown to be superior to scaling to a given constant . We firsWe then analyzed miRNAs that previously associate to breast cancer. MiR-155, which was discovered to be upregulated in breast cancer -19, is ap-values. We compared the expression patterns of the 10 differentially expressed miRNAs with published results  and 6 human breast noncancerous tissues (C1-C6) and kept in TRIzol  before RNA isolation. MiRNAs were extracted from each sample using mirVana miRNA isolation kit . MiRNA quantity and quality were checked by spectrophotometer, Nanodrop ND-1000 . The clinical data of patients are shown in Additional file F-adaptors and R-adaptors were ligated to miRNA samples consequently with a size-selection by polyacrylamide gel electrophoresis to purify the library after each ligation. Each F-adaptor contains a unique F-barcode for 6-nt in length. The RT-primers were added to carry out reverse transcription. The libraries were then amplified by PCR reactions, in which the R-barcodes for 6-nt in length were introduced by the R-primers. One more size-selection by polyacrylamide gel electrophoresis was done after the PCR reactions. The 32 samples were mixed in a pool at the same concentration to operate emulsion PCR (ePCR). Template bead preparation, ePCR and deposition were performed according to the standard protocol, and slides were analyzed on a SOLiD system V2  according to the multiplexing protocol. The sequences of oligos used in this paper are shown in Additional file SOLiD reads were decoded by the F-barcodes and R-barcodes consequently allowing one mismatch in each 6nt coding region. The reads which match an F-barcode and an R-barcode uniquely and simultaneously were used for mapping  and miRBase (Release 14.0).Click here for fileMiRNA read length distribution. Exhibit the miRNA read length distribution of each patient.Click here for fileMiRNA read counts of two independent runs. Scatter plots of miRNA expressions of all 32 barcode pairs of two independent runs.Click here for fileMiRNA read counts of different barcode pairs. Scatter plots of miRNA read counts of the same sample without barcode to with different barcode pairs.Click here for fileHighly expressed miRNAs. Highly expressed miRNAs in all 25 datasets.Click here for fileMapping and normalization. The detailed progression of mapping and normalization.Click here for fileDifferent expressed miRNAs. The 22 miRNAs which were differentially expressed between breast malignant and breast carcinoid based on a t-test.Click here for fileClinical data. Clinical data of the patients included in this study.Click here for fileEncoding and decoding. Details of the encoding and decoding progress.Click here for file


Neuroscience is increasingly focusing on developmental factors related to human structural and functional connectivity. Unfortunately, to date, diffusion-based imaging approaches have only contributed modestly to these broad objectives, despite the promise of diffusion-based tractography. Here, we report a novel data-driven approach to detect similarities and differences among white matter tracts with respect to their developmental trajectories, using 64-direction diffusion tensor imaging. Specifically, using a cross-sectional sample comprising 144 healthy individuals (7 to 48 years old), we applied k-means cluster analysis to separate white matter voxels based on their age-related trajectories of fractional anisotropy. Optimal solutions included 5-, 9- and 14-clusters. Our results recapitulate well-established tracts  and subdivisions within tracts . For all but one tract identified, age-related trajectories were curvilinear , with age-related increases during childhood and adolescence followed by decreases in middle adulthood. Identification of peaks in the trajectories suggests that age-related losses in fractional anisotropy occur as early as 23 years of age, with mean onset at 30 years of age. Our findings demonstrate that data-driven analytic techniques may be fruitfully applied to extant diffusion tensor imaging datasets in normative and neuropsychiatric samples. Many initial efforts to characterize white matter maturation have assumed linear age effects, an assumption that is not necessarily justified and can lead to false negatives as a result of inadequate fitting a priori information. Specifically, we used k-means cluster analysis Here, in a cross-sectional sample composed of 144 individuals (7 to 48 years old), we demonstrate an alternative approach for exploring differential developmental trajectories across white matter tracts and their subdivisions that requires no This study is based on DTI data obtained from 144 healthy individuals aged 7–48 years . All participants were free from psychiatric disorders, as confirmed by semi-structured psychiatric interviews. Specifically, absence of DSM-IV axis-I psychiatric disorders was established per the Schedule for Affective Disorders and Schizophrenia for School-Age Children – Present and Lifetime Version (KSADS-PL) 2; 1 image with no diffusion weighting). Bandwidth was 3720 Hz/pixel. A gradient echo field map  was also acquired with the same slice positioning and resolution as the diffusion-weighted data.Imaging data were acquired using a Siemens Allegra 3T (NYU Center for Brain Imaging). A T1-weighted image , and two DTI scans were acquired from each participant using a twice-refocused diffusion-weighted EPI sequence  datasets for each participant were concatenated. Motion correction was performed by applying 9 degrees of freedom linear registration to a warped template, derived from the field map. Local magnetic field inhomogeneities were accounted for by field map reconstruction a priori expectations with respect to the number of clusters, we repeated the algorithm varying the number of clusters from 2 to 16.Prior to cluster analysis, differences among participants related to registration to standard space were removed from the data by regressing out the mean squared difference between each participant's FA map and the FMRIB58_FA template A classic challenge for data-driven approaches such as cluster analysis is the determination of an “optimal solution”. A common way to address this challenge is to calculate a measure of cost for each cluster solution, and identify those solutions with local minima in the cost measure as optimal. Here, to assess the stability of each clustering solution, we used the Davies-Bouldin cluster validation index (DBI) http://www.fmrib.ox.ac.uk/fsl/) we applied a general linear model to each voxel of raw statistical TBSS images using permutation-based non-parametric testing. We corrected for multiple comparison using threshold-free cluster enhancement  Using FSL 4.1.5  suggested that the 5-, 9- and 14- cluster solutions were optimal. The resulting clusters appeared to meaningfully recapitulate well-established white matter tracts and subdivisions within tracts, as well as relationships among tracts. Importantly, across cluster solutions, many clusters exhibited a notable degree of stability , with changes occurring in a progressive hierarchical manner from one solution to the next  were taken into account , the genu (anterior) and the body (intermediate) First, we draw attention to the corpus callosum (CC), the primary conduit for interhemispheric communication between the cerebral hemispheres. Despite the lack of Of note, with respect to absolute FA values, the CC body exhibited the highest initial and peak FA, and the genu the lowest. These differences are consistent with prior findings regarding fiber size and myelination Across cluster solutions, the cerebral peduncles consistently clustered with the anterior limb of the internal capsule. The two combined exhibited the greatest increases in FA during development (indexed with both absolute difference and %-increase). They also ranked among the lowest with respect to measures of loss during adulthood, suggesting relative preservation of their integrity with age. The strength of the relationship between voxels within the anterior limb of the internal capsule and the cerebral peduncles is not surprising, given that the fronto-pontine tracts, which project from the frontal cortex to the pons, travel through the anterior limb of the internal capsule We note that distinctions between the anterior and posterior limbs of the internal capsule were prominent across all cluster solutions – likely reflecting their different functions. The anterior limb conveys the fronto-pontine and thalamo-cortical pathways, both of which are critical to information transfer with the prefrontal lobes Although not the primary focus of the proposed work, we carried out traditional multiple regression-based analyses of voxel-wise increases in FA. For these analyses we used linear and quadratic models. Linear models revealed overall age-related increases in FA for most WM tracts . Quadratic models, which detected curvilinear trends associated with age-related decreases in adulthood, were also significant . F-test comparisons revealed a significantly better fit for the quadratic models, further highlighting the non-linearity of age-related changes in FA. No significant linear negative effects of age were noted see .Cluster analyses of FA of skeletonized white matter tracts successfully differentiated the major tracts and subdivisions, based on their developmental trajectories in a cross-sectional DTI sample spanning ages 7–48 years. While nearly all tracts exhibited quadratic trajectories for FA, they differed with respect to the magnitude of increases in white matter during childhood and adolescence, as well as in the rates and extent of decreases during middle adulthood. These findings recapitulate those of prior DTI and histological studies a priori expectations. As such, it lends itself well to both hypothesis generation and replication studies.Despite its initial development in the mid 1980's rd decade of life for nearly half the tracts examined. A striking aspect of our results was the young age at which maximal FA was estimated to be reached, which presumably is also when age-related decline in FA can be estimated to begin. Across clusters, peak ages based on quadratic fits varied between 23 and 34 years old, and estimated absolute loss by age 48 reached between 5 and 8% for several clusters. This age range surprised us, as WM volume loss has generally been documented to occur at or after age 40 The prominence of quadratic trajectories in our sample is particularly noteworthy, as the findings do not simply reflect curvilinear patterns during early development. Rather, they appear to reflect decreases in white matter integrity that are estimated to begin in the 3Intriguingly, well-established subdivisions of the corpus callosum were delineated by cluster analyses. Specifically, the genu, which supports interhemispheric transmission among frontal regions, showed a more gradual pattern of increases in FA While model-free data-mining is extensively used in the biological community, particularly in genetics, it is only recently gaining acceptance in neuroimaging. In particular, independent component analysis (ICA) has played a major role in revealing the brain's functional architecture, and more recently, its structural architecture We note a number of methodological considerations and limitations related to our results - particularly the limitations inherent to our sample. Our age range did not capture the developmentally active period prior to age 7 years, nor did it include adulthood beyond the fifth decade, when the greatest losses of structural integrity in the brain occur. The limited age range may explain the relatively low complexity of trajectories identified, which mostly tended to be quadratic. We chose to avoid higher-order models  for characterizing trajectories, to prevent artifactual fits that can arise at the extremes of smaller samples, such as ours. A larger sample including individuals spanning the entire lifespan will likely reveal more complex developmental trajectories. Greater sampling densities  in future cross-sectional studies will bolster efforts to define age-based trajectories with a higher degree of fidelity. Even more important will be the incorporation of longitudinal designs. Future work may also take advantage of the proposed approach to allow exploration of developmental trajectories in clinical populations, without assumptions based upon neurotypical populations .Additionally, the resolution of our diffusion data was relatively low (3-mm isotropic), and we did not take advantage of more advanced acquisition and/or reconstruction strategies  In conclusion, data-driven clustering methods applied to DTI FA in a cross-sectional sample extending from childhood to mid-adulthood revealed distinct developmental trajectories in major white matter tracts and their subdivisions. Independent replication of these results will provide a powerful means of generating and testing novel hypotheses regarding structural connectivity in the human brain.Figure S1Evolution of Cluster Solutions.Panel A : K-means cluster analysis was employed to group and differentiate white matter voxels based on their cross-sectional age-related fractional anisotropy (FA) trajectory across individuals aged 7–48 years. Skeletonized FA for the first five cluster solutions are depicted in each column in MNI space, revealing a high degree of stability across solutions. In each column (solution), each color represents a distinct cluster. Panel B (Trajectories and Atlas-Based Projections): The first five cluster solutions are depicted in rows. Scatter plots for each cluster in a given solution show the data points included in each cluster and their mean trajectories. All trajectories are baselined with respect to the initial trajectory value to facilitate visual comparison. Age in years is shown on the abscissas. The middle graph (solid black line) in the top row shows the Davies-Bouldin cluster validation index (DBI) for determining optimal clustering solutions. Local minima were detected for the 5-, 9-, and 14-cluster solutions. The trajectories for all clusters in each solution, set to initial baseline, are shown in the second column from the right. To facilitate visualization, the right-most column provides an ICBM-81 atlas-based tract projection, with each tract color-coded based upon the dominant cluster to which its voxels were assigned.(TIF)Click here for additional data file.Table S1Evaluation of tract continuity within 5, 9, and 14-cluster solutions. For each solution, we list the following for each cluster: 1) % of voxels contained in the largest continuous tract within the cluster, and 2) the percentages of voxels that are part of large continuous tracts within the cluster . Measures are reported separately for each hemisphere  and the whole brain (whole).(XLS)Click here for additional data file.Table S2Fractional Anisotropy (FA) Trajectory Characteristics for ICBM-81 DTI Atlas Tracts. Measures of age-related increases in FA during development are provided for each of the ICBM-81 DTI Atlas Tracts, as well as age-related decreases during adulthood and trajectory curvature (second-order parameter from quadratic model).(XLS)Click here for additional data file.


Health-related quality of life (HRQOL) is affected by chronic HIV-infection (CHI). No data are available if and to what extent HRQOL is affected in patients who were diagnosed during primary HIV-1 infection (PHI).Included were Dutch, male, adult, HIV-1 infected patients, attending the AMC outpatient clinic who seroconverted after December 31st of 1996. 59 Patients identified during PHI and a randomly selected group of 99 patients that were identified with CHI in the same period were eligible. Patients were excluded if they ever had an CDC-C event or suffered any significant comorbidity. Subjects were asked to complete the SF-36 and the Multidimensional Fatigue Inventory (MFI-20) questionnaires. SF-36 and MFI-20 scores were compared with age- and gender-matched Dutch or German general population norms, respectively.123 patients were included: 48 from the PHI group and 75 from the CHI group. Patients in the PHI group tended to be younger, fewer were on HAART and they had at the moment of diagnosis a higher CD4 count and a higher plasma viral load. The PHI group was more severely impaired and in more dimensions of HRQOL than the CHI group. Likewise, although fatigue was present in both PHI and CHI groups. PHI patients scored higher in every dimension. Figure 1HIV-infected patients in the HAART-era have severely impaired HRQOL and suffer from fatigue. Patients that presented with PHI in the past are impaired to a larger extent and in more dimensions than patients diagnosed with HIV during CHI. This difference is present in both HRQOL and fatigue.