In older adults, depression has been associated with increased fall risk, but the reasons for this link are not fully clear. Given parallels between major depression and Parkinson's disease, we hypothesized that major depression and related affective disorders would be associated with impairment in the ability to regulate the stride-to-stride fluctuations in gait cycle timing.We measured stride-to-stride fluctuations of patients with two forms of mood disorders, unipolar major depressive disorder (MDD) and bipolar disorder, and compared their gait to that of a healthy control group. The primary outcomes were two measures of gait unsteadiness that have been associated with fall risk: stride time variability and swing time variability.Compared to the control group, the two patient groups tended to walk more slowly and with decreased swing time and increased stride time. However, none of these differences was statistically significant. Compared to the control group, swing time variability was significantly larger in the subjects with bipolar disorder (p < 0.0001) and in the subjects with MDD (p < 0.0004).Patients with MDD and patients with bipolar disorder display gait unsteadiness. This perturbation in gait may provide a mechanistic link connecting depression and falls. The present findings also suggest the possibility that measurement of variability of gait may provide a readily quantifiable objective approach to monitoring depression and related affective disorders. In older adults, depression has been associated with increased fall risk ,2. EpideParallels between Parkinson's disease and depression also support the possibility of gait unsteadiness in the latter. Psychomotor studies have revealed deficits in the motor performance of persons with major depression similar to some of the motor disturbances observed in Parkinson's disease ,15. In bGiven the associations between fall risk and depression and the parallels between major depression and Parkinson's disease, we hypothesized that major depression and related affective disorders would be associated with gait unsteadiness and impairment in the ability to regulate the dynamics of gait stability. To this end, we measured the stride-to-stride fluctuations in the gait cycle timing of patients with two forms of mood disorders, unipolar major depressive disorder (MDD) and bipolar disorder, and compared their gait to that of a healthy control group. The primary outcomes were two measures of gait unsteadiness: stride time variability and swing time variability ,19,20. WPatients with a clinically defined major affective disorder were recruited from the clinics of McLean Hospital, a psychiatric teaching center in Belmont, MA. Specifically, patients were invited to participate if they were being treated for either bipolar disorder or unipolar MDD, as defined by DSM-IV criteria . PatientSubjects were instructed to walk at their normal pace on level ground for 35 meters, to turn and to walk the same route back, and to continue walking for a total of six minutes. Study subjects were not aware of the specific questions addressed in this investigation.Previously described methods were used to evaluate gait dynamics and analyze the stride-to-stride fluctuations of gait timing ,19,20. BTo focus on the assessment of the intrinsic dynamics of continuous, usual walking and gait unsteadiness and to insure that the analysis was not influenced by outlier data points, previously described analysis methods were used ,19,20. BResults are reported as means ± standard deviation. For continuous data, the Wilcoxon Rank Sum test  was used to compare each patient group to the control group . Subgroup analyses were performed to evaluate the effects of subject characteristics such as age and use of certain drugs. A p-value less than or equal to 0.01 was considered statistically significant (Bonferroni-like adjustment for the five measures of gait). Statistical analysis was performed using SPSS for Windows (version 10.1).Fifty subjects (17 women) were studied. Subjects were 36.3 ± 14.7 years old. Twenty-three of the subjects had bipolar disorder (mean age: 43.4 ± 14.2 yrs), nine subjects had MDD (mean age: 40.9 ± 16.9 yrs), and eighteen of the subjects were healthy controls (mean age: 24.9 ± 3.5 yrs). Scores on the Clinical Global Impression (CGI) scale were 0.2 ± 0.4, 3.8 ± 0.9, and 3.2 ± 0.7 for the control, bipolar and MDD groups, respectively. As expected, the mean CGI scores were significantly higher in both patient groups compared to the control group (p < 0.001 for both groups).Table All but one of the subjects with MDD was being treated for acute illness, as were nineteen of the subjects with bipolar disorder. Among the subjects with bipolar disorder, the subjects whose disease was stable tended to walk more normally  compared to those subjects with bipolar disorder being treated acutely. Swing time variability tended to be larger (p = 0.044) in the subjects with bipolar disorder who were being treated acutely (3.2 ± 1.5 %) compared to those who were more clinically stable (2.2 ± 0.3 %).Among the subjects with MDD, swing time variability tended to be higher in subjects on antidepressants (n = 5) compared to subjects not taking antidepressants (p = 0.027). Other measures of gait and the CGI were similar in the MDD subjects who were on or off antidepressants (p > 0.41). One patient with MDD was taking a neuroleptic and none was taking mood stabilizers. Among bipolar patients, there were no significant differences in any of the gait measures in patients who were taking antidepressants (n = 15), neuroleptics (n = 14) or mood stabilizers (n = 12) compared to those who were not. Compared to controls, swing time CV was significantly increased among bipolar patients who were not taking antidepressants (p < 0.001), not taking neuroleptics (p < 0.002) or not taking mood stabilizers (p < 0.001). Stride time CV tended (p = 0.068) to be increased among bipolar patients who were taking antidepressants, neuroleptics, or mood stabilizers (n = 17), compared to those who were not (n = 6). Compared to the controls, swing time CV was significantly increased among the six bipolar patients who were not taking antidepressants, neuroleptics or mood stabilizers (p < 0.007).Subjects in the two patient groups were generally older than the subjects in the control groups. To evaluate if the group effects were only a result of these age differences, we analyzed the subset of all the subjects who were less than forty years of age. In this subgroup (n = 32), mean ages of all three groups were similar (p > 0.32) and CGI scores remained significantly higher in the two patient groups compared to the control group p < 0.0001). The results of this subset analysis are consistent with those shown in Table . The resPrevious studies reported that patients with clinical depression walk more slowly and with less time spent in the swing phase of the gait cycle ,7. The pAlthough not necessarily apparent to the clinical observer, the present quantitative study suggests that severe clinical depression and related major affective disorders may be associated with an unsteady gait, with certain features reminiscent of impairments in Parkinson's disease. There are, however, subtle but important differences. In advanced Parkinson's disease ,19, gaitIn some previous studies that have examined both stride time variability and swing time variability, an increase in one measure was accompanied by an increase in the other measure ,19. ThisAnother related explanation for the discrepancy been stride time variability and swing time variability has been suggested by Gabell and Nayack . They prIn older adults, depression is associated with an increase in the risk of falls and hip fractures ,3. The mA previous study of gait in depression did not find any significant differences in the gait of subjects who were taking medications compared to those who were not . SpecifiThis preliminary study has a number of limitations. As noted, subjects in the control group were generally younger than the two patient groups (mean differences of 4 and 7 years). However, a number of considerations suggest that the observed increase in swing time variability in the patient groups was not simply a function of aging. 1) Subgroup analysis demonstrates that the differences between the groups persist even when only the relatively young subjects (< 40 years of age) are studied. 2) Like the variability of gait speed and stride length, previous work has shown that the variability of stride time and swing time is similar in healthy young and healthy older adults, and that increases in older adults are a sign of pathology -26,30-32The present study has other limitations and raises additional questions that should be addressed in future studies. Among subjects with MDD, we could not evaluate if there were differences between subjects treated for acute illness and those with more chronic symptoms. Further, among patient with bipolar disorder, we did not control for the patients' acute mood status. The present study may have also been underpowered to detect small differences between the patients with bipolar disorder and MDD. A prospective study of a larger number of patients, perhaps in different age groups before and after they undergo different types of therapy, including pharmacologic interventions, should be helpful in leading to a more complete understanding of the relationships among stride variability, fall risk, and medication usage. Such studies may also be helpful in determining the mechanisms whereby depression and related mood disorders influence stride variability, in assessing how this relationship changes over time and with respect to disease state (i.e., acute or stable symptoms), and in evaluating if stride variability measures may prove clinically useful as an objective measure of major affective disorders. Stride variability is less affected by a conscious effort to alter gait and more closely reflects intrinsic underlying impairment . Additiovariability in major mood disorders may be more sensitive to certain subtle neuropsychiatric influences than measures based only on the mean value of a given parameter. Our findings also demonstrate that measurement of variability of gait may provide a readily quantifiable approach to monitoring depression and other affective disorders. Moreover, these results suggest that this perturbation in gait dynamics may provide a mechanistic link connecting depression and falls in older adults.Despite the limitations of this study, the present findings in a relatively small sample size indicate that patients with MDD and patients with bipolar disorder display gait unsteadiness evidenced by increased swing time variability, even while other measures of gait are not markedly changed. This apparent disparity between measures of stride variability, on the one hand, and gait speed and other features of gait, on the other, raises the possibility that stride-to-stride CV: coefficient of variationThe author(s) declare that they have no competing interests.JMH, ALG and ALS conceived of the study, and participated in its design and coordination. JMH drafted the manuscript. JMH and CKP carried out the time series and statistical analyses. All authors helped to revise the manuscript and read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


If you've ever hit a patch of ice on the road that sent your car swerving left while you resolutely—and futilely—steered right to get back in your lane, you've experienced what neuroscientists call a “visuomotor rotation task.” On a dry road, your response would have been appropriate. But under icy conditions, the same sensory cue produces a decidedly negative result: a car fishtailing out of control. While you're figuring out what movements will straighten out the car, the neurons in your primary motor cortex—the region of the brain responsible for movement—are taking notes. Chances are, your next icy encounter was less dramatic. But how does your brain learn to produce a different movement in response to the same visual cue?Neuroscientists investigate such questions by recording and analyzing the electrical activity of neurons during learning and performance of new sensory-motor transformations. Such studies, for example, show that populations of neurons in different brain areas map sensory cues and desired arm motion by creating an internal representation of the corresponding sensory and motor coordinates in a way that allows flexible responses to changing conditions. In previous studies, Rony Paz and Eilon Vaadia, of The Hebrew University in Israel, found that neurons in the primary motor cortex that fire before monkeys move their arm in a particular direction have higher firing rates after the monkey learns to dissociate the arm direction from the cursor direction . Interestingly, changes in activity preferentially occurred in a subset of neurons that were already tuned  to the direction experienced while learning.While many studies indicate that learning new tasks can generate specific changes in brain activity, it had not been clear how or if such changes improve the internal representation inside the brain. Specifically, is the neuronal code any “better” after learning? Now Paz and Vaadia show that while these neurons are firing at higher rates they are also transmitting more information about specific task parameters.Paz and Vaadia trained two rhesus monkeys to learn various visual-motor tasks—which involved operating a joystick to move a cursor on a screen—and then changed the relationship between the visual feedback (the cursor) and hand movement. Using information-theory analysis—which measures the amount of information that single neurons can tell about the movement—they were able to correlate neuron activity with direction of movement and, conversely, distinguish differences between directions based on neuron activity. Their analysis revealed that the neurons transmit more information about the direction of movement after the monkeys learn a task. To figure out what aspect of neuron activity conveys this improved information, Paz and Vaadia examined two features of neuron signaling—response variability and directional sensitivity—which they reasoned might plausibly accomplish this. Increased information content after learning a task, they found, corresponded to sensitivity to a single direction, and neurons attuned to that direction contributed to the increase.These findings suggest that subsets of directionally sensitive neurons increase their firing rates to more finely tune their sensitivity to that direction. By successfully reconstructing the movement direction from the neuron signals captured after learning a task, Paz and Vaadia also demonstrate that the observed learning improvement can be extracted to predict behavior. The authors argue that their results suggest a close association between properties of neurons—such as directional tuning of cells—and learning a skill that is focused on the same parameter—in this case, direction. Together with results from visual and auditory areas, they propose that similar mechanisms may control the interplay between neurons and learning throughout the central nervous system.


Low and high body mass index (BMI) have been recently shown to be associated with increased and decreased mortality after ICU admission, respectively. The objective of this study was to determine the impact of BMI on mortality and length of stay in patients admitted to the intensive care unit (ICU).2. A multiple logistic regression analysis was used to determine the independent impact of BMI on hospital mortality. The ICU length of stay ratio was defined as the ratio of the observed to the predicted LOS. P-value < 0.05 was considered significant. The 95% confidence interval (CI) was calculated for the odds ratio (OR).In this retrospective cohort study, the Acute Physiology and Chronic Health Evaluation (APACHE) III database of patients admitted to the ICUs of a tertiary academic medical center, from January 1997 to September 2002, was crossed with a Hospital Rule-based Systems database to obtain the height and weight of the patients on admission to the ICU. The cohort was divided in post-operative and non-operative groups. We created the following five subgroups based on the BMI: <18.5, 18.5 to 24.9, 25 to 29.9, 30.0 to 39.9, ≥ 40.0 Kg/mBMI was available in 19,669 of the 21,790 patients in the APACHE III database; 11,215 (57%) of the patients were admitted post-operatively. BMI < 18.5 was associated with increased mortality in both post-operative (OR = 2.14, 95% CI, 1.39 to 3.28) and non-operative (OR = 1.51, 95% CI, 1.13 to 2.01) patients. Post-operative patients with a BMI between 30.0 to 39.9 had a lower mortality rate (OR = 0.68, 95% CI, 0.49 to 0.94). Post-operative patients with BMI <18.5 or BMI ≥ 40 had an ICU length of stay ratio significantly higher than patients with BMI between 18.5 to 24.9. The addition of BMI < 18.5 did not improve significantly the accuracy of our prognostic model in predicting hospital mortality.Low BMI is associated with higher mortality in both post- and non-operative patients admitted to the ICU. LOS is increased in post-operative patients with low and high BMIs. The rel patients. In the mortality.Previous studies did not analyze the data from post-operative and non-operative patients separately when they looked at the impact of BMI on the outcome of critically ill patients. We undertook this study to determine the influence of BMI on mortality in post-operative and non-operative patients admitted to the ICU, in a single tertiary academic medical center. Based on the association of low BMI with increased mortality, a recent publication has highlighted the importance of looking at whether adding BMI would improve the predictive accuracy of the ICU prognostic models. In the In this retrospective, cohort study, we crossed the prospectively collected Acute Physiology and Chronic Health Evaluation (APACHE) III database of adult patients consecutively admitted to the intensive care units of Mayo Medical Center, Rochester, Minnesota, between January 1997 and September 2002, with a Hospital Rule-based Systems database that records the height and weight on admission to the ICU. Patients were admitted to one medical, two surgical and one multi-specialty ICU. Those patients admitted to the neurological, cardiovascular surgery, and coronary care units were not included since they were not part of the APACHE III database. Only first admissions were included in this study. The Mayo Foundation Institutional Review Board approved the study, and a waiver of informed consent was granted. Patients who did not authorize their medical records to be reviewed for research, and those whose weight or height values were missing were excluded.Mayo Medical Center includes two hospitals with a total of approximately 1900 beds. The medical ICU is a 15-bed closed unit in Saint Mary's Hospital. The surgical ICUs consist of a general surgical/trauma 24-bed unit and a 20-bed surgical unit mainly for thoracic and vascular surgery patients, both located at Saint Mary's Hospital. The 12-bed (increased to 17 beds in March 2000) multi-specialty ICU is located in Rochester Methodist Hospital. The patient population in the multi-specialty ICU included liver, kidney, pancreas and bone marrow transplant recipients; and hematology, oncology, general surgery and orthopedic patients.Data were obtained from the APACHE III database using the software provided by Cerner Corporation (Kansas City, MO). Data collected included age, ethnicity, gender, ICU admission source, admission type (postoperative or non-operative), intensity of treatment (low-risk monitor, high-risk monitor, active treatment), ICU admission diagnosis group, ICU length of stay (LOS), APACHE III score, APACHE III-predicted hospital mortality, APACHE III predicted-ICU LOS and hospital discharge status. The admission source was classified as operating room/recovery room (OR/RR), emergency room/direct admission from outpatient clinic (ER/direct), transfer from other floors of the same hospital and transfer from other institutions. All ICU admissions were categorized into three groups based on the intensity of treatment: "active treatment" if a patient received one or more of 33 items of the Therapeutic Intervention Scoring System (TISS) defined as ICU specific therapy on the first ICU day; "high-risk monitor" if a patient who did not receive active treatment on the first ICU day had greater than 10% probability of receiving active treatment during the ICU stay; and "low-risk monitor" if a patient who did not receive active treatment on the first ICU day had less than 10% probability of receiving active treatment during the ICU stay . The ICU2. Four BMI subgroups were created using the cut-off points of the World Health Organization (WHO): 18.5 to 24.9 , 25.0 to 29.9 (grade 1 overweight), 30.0 to 39.9 (grade 2 overweight), ≥ 40 (grade 3 overweight)[The body mass index for each patient (BMI) was calculated as the weight (in kilograms) divided by the square of the height (in meters). All BMIs are presented in Kg/merweight). A fifthP-values.Descriptive data were summarized as mean (standard deviation), median (interquartile range) (IQR) or percentages. The cohort was divided into post-operative and non-operative patients. The primary analysis consisted of a comparison of hospital mortality for each BMI subgroup. A multiple logistic regression model consisting of hospital mortality as a dependent variable, BMI subgroup, APACHE III predicted mortality, admission source, and intensity of treatment as independent variables was created to adjust for potentially confounding variables that could affect hospital mortality. In the post-operative group the admission source was not included in the model since the source in all the patients was either the recovery room or the operating room. This logistic regression model was based on a previous analysis that identified the variables independently associated with hospital mortality. We perfThe ICU LOS ratio was defined as the ratio of the observed to the predicted LOS. LOS ratios less than one indicate stays shorter than predicted. In compP-value < 0.05 was considered statistically significant.StatView 5.0 (SAS Institute, Cary, NC) and MedCalc 7.3 (Mariakerke, Belgium) computer softwares were used for statistical analyses. Patients with missing data were excluded from analysis involving the missing elements. A Of the 21,790 patients with first ICU admissions during the study period, 19,669 had height and weight data. Their baseline characteristics are listed in Table P < 0.0001). Among the ICU admission diagnoses, BMI < 18.5 was associated with increased adjusted mortality in cardiovascular, genitourinary and musculoskeletal groups . Compared to the normal BMI subgroup, the ICU LOS ratio was higher in the BMI < 18.5 (P = 0.0411 by Mann-Whitney U test) and BMI ≥ 40 (P < 0.0001 by Mann-Whitney U test).For post-operative patients, the crude hospital mortality rate was 3.3 %, and the median (IQR) ICU LOS and ICU LOS ratio were 1.04 0.82–2.15) and 0.42 (0.25–0.77) days, respectively. After adjusting for confounding variables, postoperative patients with a BMI < 18.5 had a higher hospital mortality, and those with BMI of 30.0–39.9 had a lower hospital mortality rate (Table  and 0.42P = 0.3414)  ICU LOS and ICU LOS ratio were 1.68 (0.89–3.69) and 0.45 (0.25–0.89) days, respectively. After adjusting for confounding variables, the patients with a BMI < 18.5 had a higher hospital mortality rate (Table ) Tables .P = 0.102).In discriminating hospital survivors from non-survivors, the AUC (95% CI) of the model with BMI < 18.5 was 0.859 (0.854 to 0.864) and the AUC of the model without BMI < 18.5 was 0.858 (0.853 to 0.863) (The results of our retrospective study suggest that a BMI <18.5 is independently associated with higher mortality in post- and non-operative patients admitted to the ICU. We found no difference in the ICU LOS among the BMI subgroups in non-operative patients. In post-operative patients, the LOS was longer in patients with a BMI <18.5 or BMI ≥ 40. We also noted that the addition of BMI does not improve significantly the predictive accuracy of the prognostic model.In this study, we wanted to determine the impact of BMI on mortality in post- and non-operative patients separately since patients admitted to the ICUs from hospital wards have higher mortality than patients admitted from the operating room, independent of disease severity,18. In oOur study has several limitations. It has been speculated that a low BMI is simply the consequence of a serious illness before the hospitalization that it is ultimately fatal,6. We haThis study shows that a BMI < 18.5 is independently associated with increased mortality in post- and non-operative patients admitted to the ICU; and in post-operative patients, the LOS was longer in patients with a BMI < 18.5 or BMI ≥ 40. We also found that the inclusion of BMI < 18.5 in a prognostic model does not improve the accuracy of mortality prediction.The authors declare that they have no competing interests.JDF participated in conception, design, acquisition of the data, analysis of the data, and drafting of the manuscript.OG participated in analysis of the data, and critical revision of the manuscript.BA participated in conception, design, analysis of the data, statistical analysis, critical revision of the manuscript, and supervision.The pre-publication history for this paper can be accessed here:


The practice of Evidence-based Medicine requires that clinicians assess the validity of published research and then apply the results to patient care. We wanted to assess whether our soon-to-graduate medical students could appraise and apply research about a diagnostic test within a clinical context and to compare our students with peers trained at other institutions.th year medical students who previously had demonstrated competency at probability revision and just starting first-year Internal Medicine residents were used for this research. Following an encounter with a simulated patient, subjects critically appraised a paper about an applicable diagnostic test and revised the patient's pretest probability given the test result.4The medical students and residents demonstrated similar skills at critical appraisal, correctly answering 4.7 and 4.9, respectively, of 6 questions (p = 0.67). Only one out of 28 (3%) medical students and none of the 15 residents were able to correctly complete the probability revision task (p = 1.00).This study found that most students completing medical school are able to appraise an article about a diagnostic test but few are able to apply the information from the article to a patient. These findings raise questions about the clinical usefulness of the EBM skills possessed by graduating medical students within the area of diagnostic testing. Evidence-based medicine (EBM) has been described as the "conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients" . Thus, tNearly all medical schools now provide their students with instruction on EBM . StudentIn undertaking this research, we wanted to assess the critical appraisal and probability revision skills of our medical students shortly before graduation within the domain of diagnostic testing. We specifically wanted to evaluate medical students who had previously demonstrated competency at probability revision in a classroom setting. Because EBM is designed to support the delivery of clinical care, transfer of these skills from the classroom to the exam room seemed an appropriate measure of instructional success. We were also interested in comparing the skills of our students nearing graduation to physicians just entering the Internal Medicine residency at our medical center with the intention of comparing the skills of our students to those of students who had trained at other medical schools.The data were collected during a performance-based assessment utilizing standardized patients (SPs). During this assessment, subjects had a series of 15 minute encounters with SPs followed by a 10 minute post-encounter activity, thus making each station 25 minutes in length. A 25 minute non-SP based station was integrated into this assessment during which subjects were asked to read and appraise an article about a diagnostic test and apply the information to a preceding SP encounter.Two different groups of subjects participated in this research. The first group was composed of medical students who were assigned to the Psychiatry clerkship in the late winter and spring of 2003. The second group was composed of all incoming first-year Internal Medicine residents who were in the process of orienting to the residency in June 2003 in preparation for their clinical duties.Subjects were asked to critically appraise a research study about a diagnostic test using a worksheet derived from the article about diagnostic tests published in Users' Guides to EBM series . They weThe fourth year medical students, who were participating in their Psychiatry clerkship, were asked to assess an article about a questionnaire to aid in the diagnosis of Major Depression and Panic Disorder . The IntFor this study, the calculated posttest probability was considered correct if it was ±5% of the correct answer derived from Bayes' Theorem. The performances of the medical students and the Internal Medicine residents were compared using Fisher's Exact Test for dichotomous outcomes and t-test for continuous outcomes. Cronbach's alpha was used to calculate the internal reliability of the 6-item critical appraisal worksheet for each group of subjects. The analyses were undertaken using NCSS 2004 (Kayesville, UT). An alpha of 0.05 was used and all tests were 2-tailed. Approval from the institutional review board was obtained for this project.th year medical students who had demonstrated mastery of Bayesian probability revision during a preceding Laboratory Medicine clerkship. The data from these students were analyzed for this report. The other 10 students were dropped from the analysis because they were either M3s or M4s who had not yet completed their Laboratory Medicine clerkship.Thirty-eight medical students on the Psychiatry clerkship completed the critical appraisal exercise. Twenty-eight of these students were 4Twenty-two first year Internal Medicine residents participated in this performance-based assessment and completed the EBM appraisal task and Bayesian inference exercises during their clinical skills assessment. For this report we used the data from the 15 residents who were recent graduates of US medical schools. The data from the 7 non-US graduates were dropped from the analysis.Twenty-six of the 28 medical students (93%) correctly identified whether there was an independent, blind comparison of the test with a reference standard Table . SeventeAll 15 residents (100%) correctly identified whether there was an independent, blind comparison of the test with a reference standard. Eight (53%) correctly identified the reference standard. Eleven (73%) correctly assessed whether referral bias was present, and fourteen (93%) were able to comment on the generalizability of the study. Thirteen (87%) of the Internal Medicine residents were able to identify the sensitivity and specificity of the test for congestive heart failure. The internal reliability of the 6-item appraisal work sheet was 0.66 for this group of subjects. On average, a resident, who had just recently graduated from a US medical school, correctly answered 81% of the questions related to critical appraisal but none of the 15 residents (0%) were able to revise the pretest probability given a test result.Overall, the performances of the two groups of subjects were very similar. We did not find any significant differences in their ability to critically appraise an article about a diagnostic test. Medical students, on average, correctly answered 4.7 of the 6 questions related to appraisal while residents correctly answered 4.9 of these questions (p = 0.67). The two groups also showed similar performance on each of the 6 items on the worksheet as shown in Table Over the past decade, EBM has become a major driving force world wide, impacting medical education, policymaking, and research. The teaching of evidence-based medicine has been increasingly integrated into curricula at all levels of medical education as advocated by the Medical School Objectives Program developed by the Association of American Medical Colleges (AAMC) . Like moOur finding that incoming residents demonstrate similar levels of skill at critically appraisal and also are unable to revise a pretest probability implies that our medical students' skill deficit is not solely due to a local curricular problem. Because the residents had only just graduated from 12 different US medical schools, this finding suggests that many medical school graduates are able to critically appraise articles on diagnostic testing but few are able to take the next step- that of revising the probability of disease given a test result.rd year medical students demonstrated good performance at critically appraisal [There are few other assessments of the EBM skills of graduating medical students using simulated clinical encounters. In an earlier study, 3ppraisal , a findippraisal . To our ppraisal .Our study has a number of limitations. The first is the very small sample size. However, it is unlikely that a larger sample size would change our conclusion that by the end of medical school students have largely mastered critical appraisal of an article on diagnostic testing but are unable to use this information to revise a patient's probability of disease. A second limitation is that these data were collected at only one medical school. However, as we find the same pattern of competencies in the recently graduated students who are entering our Internal Medicine program it is likely that our findings apply to many other medical schools. A third limitation is that we had our two groups of subjects critically appraise two different articles although they were very similar from this perspective. A final limitation is that it is possible that our subjects would have demonstrated competency in probability revision if we had provided them with a Bayes nomogram or computer spreadsheet. But we wanted to assess whether our students could apply EBM skills to a clinical encounter without any other external supports except for a simple calculator. In the same way, we do not allow our students to take handbooks or other work aids into their 15 minute OSCE encounters with standardize patients.The poor performance of our students and residents at probability revision is worrisome although previous studies have shown that many clinicians do not master Bayesian inference. Nearly 25 years ago, Casscells documented that few students or faculty at Harvard Medical School were able to correctly complete a probability revision problem . Eddy duCurrently, most of our medical students are able to critically appraise research articles about diagnostic testing but few are able to apply this information at the patient level using Bayesian inference. Because we are able to document the same pattern of skills in entering Internal Medicine residents, we expect this lack of competence with probability revision to be wide spread amongst medical learners. This raises concerns about the clinical utility of the EBM training many students are currently receiving within the domain of diagnostic testing.The authors declare that they have no competing interests.GB conceived of the study. GB, SV, JT, EF participated in study design. GB, EF, RF participated in data collection. GB performed the data analysis. GB, SV, ST, EF, RF participated in drafting the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Escherichia coli and Bacillus subtilis. Computer modeling of chemotaxis in these species now reveals some important differences in the network architecture that controls this complex behavior.When we think of foraging for food, we usually imagine animals wandering in the woods, poking behind bushes and trees, trying to find something tasty. Amazingly, even single-cell bacteria display a simplified version of this behavior. Many species of bacteria can respond to chemical or nutritional cues (chemoattractants) in the environment by moving toward locations with more favorable conditions, a process known as chemotaxis. The bacteria adjust their movements by rotating threadlike projections called flagella either clockwise or counterclockwise; these adjustments are made by a network of proteins in response to chemoattractants. Chemotaxis has been identified in many bacterial species, but two of the best-studied examples are in E. coli and B. subtilis have been identified and well studied, but much remains to be learned about this biological process. As scientists have begun to understand how the proteins work together, they're discovering a network of interactions that operates a bit like an electronic circuit. Researchers have found that using the circuit as a model for protein networks has helped them to understand how complex system properties arise from seemingly simple interactions between proteins. These properties can be explored with the aid of computer simulations, whereby researchers can rapidly test a given system under many different situations and can tweak the properties of the proteins and their connections.Most of the proteins involved in chemotaxis in E. coli and B. subtilis. Not surprisingly, the proteins involved in the signaling pathway are conserved—that is, they have changed very little since they first evolved—even though these species are evolutionarily very distant. In many cases, a gene from one species can even substitute for the ortholog (a conserved gene that retains the same function even though two species have diverged) in the other. Despite these similarities, however, disrupting the function of orthologous genes in these two species often has different, even opposite, effects. This is surprising, especially given that the chemotactic behaviors of E. coli and B. subtilis are almost identical. In order to understand this puzzling observation, the researchers constructed a network model of the chemotaxis system in B. subtilis and used simulations to understand how the network properties differ from those of existing models of E. coli chemotaxis.The team, led by Adam Arkin of the University of California at Berkeley, has compared the system level properties of chemotaxis in the two bacterial species The group found that despite the similarities in proteins and the nearly identical behavior between the two species, the mechanisms underlying the behavior are quite distinctive. When comparing the system properties of these two bacterial systems, the researchers also made an unusual observation. Though the two “circuits” have different wiring, the system properties underlying the behavior, called the control strategy, are very similar. The two species of bacteria therefore achieve the same chemotaxis behavior by using similar proteins, but in different ways.Arkin and colleagues draw two important conclusions from these results. First, these two systems have conserved proteins, but the proteins are wired together differently. This means that wiring of signaling networks cannot be inferred simply by identifying the conserved proteins in the network. Second, in these systems, conserved proteins use different mechanisms to accomplish the same overall control strategy. This raises the question of how such systems evolve. The authors suggest that the control strategy itself may be an evolutionarily conserved property. These conclusions will be important to keep in mind as researchers examine these systems in more detail and begin to examine more complex systems as well.


Omega-3 fatty acids play a critical role in the development and function of the central nervous system. Emerging research is establishing an association between omega-3 fatty acids  and major depressive disorder. Evidence from epidemiological, laboratory and clinical studies suggest that dietary lipids and other associated nutritional factors may influence vulnerability and outcome in depressive disorders. Research in this area is growing at a rapid pace. The goal of this report is to integrate various branches of research in order to update mental health professionals. Major depressive disorder (MDD) is a recurrent, debilitating, and potentially life threatening illness. Over the last 100 years, the age of onset of major depression has decreased, and its overall incidence has increased in Western countries. The increases in depression, up to 20-fold higher post 1945, cannot be fully explained by changes in attitudes of health professionals or society, diagnostic criteria, reporting bias, institutional or other artifacts .Depression is undoubtedly an extremely complex and heterogeneous condition. This is reflected by the non-universal results obtained using cognitive-behavior and antidepressant medications. As research continues to mount, it is becoming clear that neurobiology/physiology, genetics, life stressors, and environmental factors can all contribute to vulnerability to depression. While much attention has been given to genetics and life stressors, only a small group of international researchers have focused on nutritional influences on depressive symptoms. Collectively, the results of this relatively small body of research indicate that nutritional influences on MDD are currently underestimated . Omega-3Omega-3 fatty acids are long-chain, polyunsaturated fatty acids (PUFA) of plant and marine origin. Because these essential fatty acids cannot be synthesized by the human body, they must be derived from dietary sources. Flaxseed, hemp, canola and walnut oils are all generally rich sources of the parent omega-3, alpha linolenic acid (ALA). Dietary ALA can be metabolized in the liver to the longer-chain omega-3 eicosapentaenoic (EPA) and docosahexaenoic acid (DHA). This conversion is limited in human beings, it is estimated that only 5–15% of ALA is ultimately converted to DHA . Aging, The dietary intake of omega-3 fatty acids has dramatically declined in Western countries over the last century, the North American diet currently has omega-6 fats outnumbering omega-3 by a ratio of up to 20:1. There are a number of reasons for this skewed ratio, most notably the mass introduction of the aforementioned omega-6 rich oils into the food supply, either directly or through animal rearing practices . The ideA number of epidemiological studies support a connection between dietary fish/seafood consumption and a lower prevalence of depression. Significant negative correlations have been reported between worldwide fish consumption and rates of depression . ExaminaNot all studies support a connection between omega-3 intake and mood. A recent cross-sectional study of male smokers, using data collected between 1985 and 1988, indicated that subjects reporting anxiety or depressed mood had higher intakes of both omega-3 and omega-6 fatty acids . In a laThe epidemiological studies which support a connection between dietary fish and depression clearly do not prove causation. There are a number of cultural, economic and social factors which may confound the results. Most significantly, those who do consume more fish may generally have healthier lifestyle habits, including exercise and stress management. Despite the limitations, the epidemiological data certainly justify a closer examination of omega-3 fatty acids in those actually with depression.There are a number of methods used to determine EFA status in the human body, notably the plasma and red blood cell (RBC) phospholipids. These are a reflection of dietary fatty acid intake within the preceding few weeks. While not identical, significant correlations exist between blood and brain phospholipids. A number of studies have found decreased omega-3 content in the blood of depressed patients -21. FurtMore recently, investigators have been utilizing adipose tissue as a longer term measurement of EFA intake (1–3 years). In a study of 150 elderly males from Crete, the parent omega-3 ALA adipose tissue stores were negatively correlated with depression . A separRelationships between omega-3 status and post-partum depression have also been investigated. In a cohort of 380 Australian women, plasma DHA was investigated at 6 months post-partum. Logistic regression analysis indicated that a 1% increase in plasma DHA was associated with a 59% reduction in the reporting of depressive symptoms . It is wSuicide attempts have also been associated with low levels of RBC EPA. In a study involving 100 suicide attempt cases in China compared to 100 hospital admission controls, there was an eightfold difference in suicide attempt risk between the lowest and highest RBC EPA level quartiles . The seaThe overlap between cardiovascular disease and depression has also been noted, with omega-3 status emerging as a common thread. Indeed, major depression in acute coronary syndrome patients is associated with significantly lower plasma levels of omega-3 fatty acids, particularly DHA . In addiIt is important to note that not every study supports an association between lowered omega-3 status and depression. Two studies have actually shown significant increases in plasma and RBC omega-3 status among depressed patients ,33. A reDetailed reviews of the possible neurobehavioral mechanisms of omega-3 fatty acids have been previously published and are beyond the scope of this review ,36. The The second area where omega-3 fatty acids may exert significant influence in major depression is via cytokine modulation. A growing body of research has documented an association between depression and the production these proinflammatory immune chemicals. These cytokines, including interleukin-1 beta (IL-1β), -2 and -6, interferon-gamma, and tumor necrosis factor alpha (TNFα), can have direct and indirect effects on the CNS. Some of the documented activities of these cytokines include lowered neurotransmitter precursor availability, activation of the hypothalamic-pituitary axis, and alterations of the metabolism of neurotransmitters and neurotransmitter mRNA . ResearcOmega-3 fatty acids, and EPA in particular, are well documented inhibitors of proinflammatory cytokines such as IL-1 β and TNFα. In addition, it has recently been suggested that the anti-inflammatory role of omega-3 fatty acids may influence brain derived neurotrophic factor (BDNF) in depression . BDNF isThe epidemiological and laboratory studies, along with the research which shows depressed patients appear to have lowered omega-3 status, have naturally led to clinical investigations. A number of case reports have appeared in the literature, the first of which was over 20 years ago. In this initial series of case reports, flaxseed oil (source of the parent omega-3 ALA) at various dosages, was reported to improve the symptoms of bipolar depression and agoraphobia . An addiDespite the interesting results, there are major scientific problems with case reports, most notably the placebo response. A recently published case report published took advantage of modern brain imaging to corroborate clinical improvements. In this case a patient with treatment resistant depression was placed on a daily dose of 4 g pure EPA, and after one month there were significant improvements, including a co-morbid social phobia. After nine months the patient was reportedly symptom free. It was found that over the course of the nine months of treatment, there was a 53 percent increase in cerebral phosphomonoesters and the ratio of cerebral phosphomonoesters to phosphodiesters increased 79 percent, indicating reduced neuronal phospholipid turnover. Utilizing MRI technology, the researchers found that the EPA treatment was associated with structural brain changes, including a reduction in lateral ventricular volume. This is likely to be a result of increased phospholipid biosynthesis and reduced phospholipid breakdown . Given tA series of case reports also suggest that 1 – 4 g of pure EPA may be helpful in anorexia nervosa, a condition with the highest risk of morbidity and mortality among psychiatric disorders . In all An interesting study examined fish oil vs.marine oil extracted from Antarctic krill in premenstrual syndrome. Krill is similar to fish oil, with the exception that it contains naturally-occurring phospholipids, and contains more EPA per gram than standard fish oil capsules (240 mg/g EPA in krill vs.180 mg/g in standard fish oil). In the 3-month trial, patients (n = 70) received 2 g of krill oil or 2 g fish oil daily for one month, then for eight days prior to, and two days during, menstruation for the following two months. Evaluation at 45 days and three months showed that krill oil significantly improved depressive symptoms of premenstrual syndrome. The absence of significant effects of fish oil on mood suggests that the presence of the phospholipids and/or higher amounts of EPA may be responsible for the therapeutic effect of krill oil .There have been some controlled studies that have examined omega-3 fatty acids and a placebo intervention in depression. The first small clinical study (n = 30) showed that four months of treatment with 9.6 g of omega-3 fatty acids (6.2 g EPA/3.4 g DHA) was of therapeutic value in bipolar disorder. Specifically, this study showed a highly significant effect in treating depression (p < 0.001 HRSD scores) . In a seIn a small pilot study (n = 30), Harvard researchers found that just 1 g of EPA could reduce aggression  and depressive symptom scores  among borderline personality disorder patients. The results of this 2-month, placebo-controlled study are encouraging, given the difficulty in treating borderline personality disorder. It is also of note that 90 percent of participants remained in the study and no clinically relevant side effects were noticed with EPA .In a double-blind, placebo-controlled trial over two months, high dose fish oil (9.6 g/day) was added to standard antidepressant therapy in 28 patients with MDD. In this study the patients who received the omega-3 fish oil capsules had a significantly decreased score on the HRSD compared to those taking the placebo. Once again, the fish oil, even at this high dose, was well tolerated with no adverse events reported .Various doses of pure EPA have also been investigated in depression. In a 12-week, randomized, double-blind, placebo-controlled study, patients (n = 70) were given ethyl-EPA at doses of 1 g, 2 g or 4 g. The patients in this case had experienced persistent depression, despite ongoing standard antidepressant pharmacotherapy at adequate does. Interestingly, in this study, "less was more." Those in the 1 g per day group had the best outcome. The patients who received 1 g per day of EPA were the only group to show statistically significant improvements. Among the 1 g/day group, 53 percent achieved a 50 percent reduction in HRSD scores. The 1 g EPA led to improvements in depression, anxiety, sleep, lassitude, libido, and suicidal ideation. These findings suggest that omega-3 fatty acids can augment antidepressant pharmacotherapy and/or alleviate depression by entirely different means than standard medications [th – 36th week of pregnancy and was assessed through 12 weeks post-partum. In these women the fish oil combination did not reduce the risk of relapse [To date, the published data on supplementation with pure EPA on MDD or depressive symptoms have been positive. With regard to DHA or a combination of EPA and DHA, there have been three negative reports. A trial on DHA alone as monotherapy in the treatment of MDD was recently reported. In this study, 2 g pure DHA or placebo was administered to 36 patients with depression for six weeks. The response differences between the groups, as measured by scores on the Montgomery-Asberg Depression Rating Scale did not reach statistical significance . In an o relapse . Finally relapse .It is important to consider the nutrients which can ultimately influence omega-3 status. Among them, four important dietary factors also relate to MDD: zinc, selenium, folic acid and dietary antioxidants. A number of studies have shown that zinc levels are lower among patients with depression and a recent study found that 25 mg zinc supplementation may improve depressive symptoms . InteresRegarding folic acid, a growing body of research has documented the low levels of folic acid among patients with depression . In addiIn patients with MDD there are in fact signs of oxidative stress and lipid peroxidation, and antidepressant medications may reverse the severity of oxidative stress in depressed patients . A recenWhile far from robust, there is enough epidemiological, laboratory and clinical evidence to suggest that omega-3 fatty acids may play a role in certain cases of depression. Fish oil supplements are well tolerated, and have been shown to be without significant side effects over large scale, 3-year research . GeneralThe research reviewed here shows that the data is far from unequivocal. Large trials are warranted to truly determine efficacy, appropriate dosing and the potentially active components – EPA, DHA, or both. It is also clear that omega-3 intake occurs in dietary context, one that includes other important nutrients. Future research should consider the influence of zinc, selenium, folic acid and dietary antioxidant status to determine who may be a successful candidate for omega-3 supplementation.In the meantime, given the current excess intake of omega-6 rich oils, and the emerging research on omega-3 fatty acids and MDD, all mental health professionals should at least ensure adequate intake of omega-3 fatty acids among patients with MDD. The current average North American intake of EPA and DHA is approximately 130 mg per day, well short of the minimum 650 mg recommended by the international panel of lipid experts [


Cytokinesis, in which newly formed daughter cells separate, is the culmination of the cell cycle. It is necessary for normal growth and development, and it is also a sine qua non in the pathogenesis of cancers—cells that can't divide can't form tumors, can't metastasize, and can't kill. Therefore, understanding the full range of proteins involved in cytokinesis has both deep theoretical and immediate practical applications. In this issue, Ulrike Eggert and colleagues report results from two complementary screening approaches to identify those proteins and to discover molecules that inhibit them.Drosophila cells, the first screen used almost 20,000 double-stranded RNAs, representing virtually the entire Drosophila genome. A double-stranded RNA pairs with, and causes the destruction of, a matching messenger RNA, thus preventing the encoded protein from being formed, a process called RNA interference (RNAi). The authors identified 214 proteins whose absence prevented cytokinesis. While some of these, including actin and Myosin, were already known to be essential for the process, others were not. The latter included a new discovery, CG4454 , which was found to be one of the handful of proteins deemed most critical to cytokinesis.A cell cannot divide if it lacks a protein vital for cytokinesis or if that protein is inhibited. When that occurs, the cell retains both nuclei, and can be quickly identified by an automated process. Working with Drosophila cells, but this time used over 50,000 “small molecules,” a catchall term for molecules small enough to pass easily into cells. The vast majority of drugs currently in clinical use are small molecules. This screen revealed 50 cytokinesis inhibitors, of which 25, dubbed binucleines, were selected for further characterization. Not surprisingly, several inhibited actin, whose role in cytokinesis is key in contraction of the cytokinesis furrow.The second screen also treated For the purposes of this study, however, binucleines affecting other proteins were even more interesting. By comparing the appearances of binucleate cells from the small-molecule screen with those from the RNAi screen, Eggert et al. identified one molecule and three proteins that caused a similar phenotype, suggesting that the three proteins acted within a single pathway, which the molecule could disrupt. One of the three proteins was CG4454/Borr, and the researchers' results indicated it interacts with Aurora B, an essential but still poorly understood protein that is needed for proper division of the chromosomes. The identified binucleine will be a valuable reagent for exploring the details of the Aurora B pathway.Drosophila, the insights they provide into the cell cycle are likely to be applicable to humans as well. Equally importantly, they provide the proof of principle for a new drug discovery method. A major bottleneck in drug development is target identification—determining which of the cell's thousands of proteins is the right one to inhibit with a drug. The unique aspect of this study is the parallel use of the two approaches—small molecules and RNAi—to provide a “stereoscopic” view of cytokinesis and its inhibition. Working together, they provide a set of proteins and a matched set of inhibitors, the target and the bullet at the same time.While these results are from


The aim of this body of research is to determine whether injuries in the home are more common in particular types of housing. Previous home injuries research has tended to focus on behaviours or the provision of safety equipment to families with young children. There has been little consideration of the physical environment. This study reports methodological developments in database linkage and analysis to improve researchers abilities to utilise large administrative and clinical databases to carry out health and health services research.The study involved linking a database of home injuries obtained from an emergency department surveillance system with an external survey of all homes in an area and population denominators for home types derived from a health service administrative database. Analysis of injury incidence by housing type was adjusted for potential biases due to deprivation and distance to hospital. For non-injured individuals data confidentiality considerations required the deprivation and distance measures be imputed. The process of randomly imputing these variables and the testing of the validity of this approach is detailed.There were 14,081 first injuries in 112,248 residents living in 54,081 homes over a two-year period. The imputation method worked well with imputed and observed measures in the injured group being very similar. Re-randomisation and a repeated analysis gave identical results to the first analysis. One particular housing type had a substantially elevated odds ratio for injury occurrence, OR = 2.07 (95% CI: 1.87 to 2.30).The method of data linkage, imputation and statistical analysis used provides a basis for improved analysis of database linkage studies. Home injuries are frequent and result in greater mortality and morbidity than road traffic injuries. It is eThe present study was designed to utilise three such datasets relating to all residential properties in a defined geographical area in the United Kingdom, the resident population, and their attendances at local hospital emergency departments (EDs). These datasets could not be linked comprehensively at individual level on account of constraints on identifiability of individuals. This article describes the novel challenges that result, and the methodology used to obviate them.This study was carried out as part of the wider Housing and Neighbourhood and Health (HANAH) project. This isAll properties in the study area were viewed externally. Domestic properties were classified into categories based on floor area (four groups), five period groups, and five build types, viz. detached, semi-detached, flat conversions, purpose-built flats, and terraced housing. Ninety-four of the 100 combinations of the three housing type variables were found in the study area. Analysis was carried out at individual property level: analysis at postcode or zip code level was not possible because very few postcodes (13%) comprised a single property type. Postcodes contained an average of 14 properties.Data on injuries treated at EDs were obtained for the period 1999 – 2000 from the All Wales Injury Surveillance System (AWISS) which routinely obtains individual level data from EDs surrounding the study area and is described in detail elsewhere. BrieflyTo obtain denominator data for each property type we used the National Health Service Administrative Register (NHSAR), a list of all people registered with the free-to-use primary care health service in Wales. Data on this system are highly confidential and denominator population profiles were obtained by providing a list of all properties in the ninety four different groups to the NHSAR staff who then matched these with their system and obtained the number of people in each of the property types, subdivided by age and sex. This system has previously been used to obtain small area population data.In analysing data on injury attendance at hospital EDs it is important to take into account the potential confounders of deprivation and access, which are known to be strongly related to injury occurrence and ED attendance respectively. For eacDuring 1999 and 2000, 14,171 out of 112,248 residents made one or more emergency department visits for a home injury. We sought to combine three files comprising individual-level injuries data from an emergency department surveillance system; an external assessment of the built form in all 54,801 homes in the area; and denominator populations for each of ninety-four property types delivered from a health service registration system. Application of logistic regression to model injury risk on built form, property size and age, subject age, sex, deprivation and distance from emergency department jointly necessitates construction of a single linked data file. The objective was to construct an appropriately linked database and hence determine whether injuries occur more commonly in different types of home.The study population of 112,248 individuals made 16,358 ED attendances for home injuries during the study period. The vast majority (99.5%, n = 16,277) of these attendance records included adequate data on age, gender, proximity and Townsend score. These 16,277 attendances involved 14,171 residents of the study area. Thus the average number of visits during the study period among those who ever visited the ED was 1.15, in other words 15% of the visits were repeat visits. The main analyses were constructed to compare the 14,171 first injury records identified as the subject's first attendance at ED for a home injury during the study period with those of the remaining 98,077 subjects. This has the effect of identifying all subjects who had one or more ED attendance for home injury during the study period.The other datasets to be linked were the population distribution by housing group, age and sex (112,248 subjects, no missing data) and a file listing 54,913 properties, of which we restrict attention to the 54,801 with complete data. Table Following discussion of preliminary results it was decided to use actual deprivation and proximity scores for the injured, and to impute values randomly according to property type for the uninjured. This is appropriate because risk scores for the remaining variables, age and sex taken together as a forty two category categorical variable, were uncorrelated with risk scores for all other variables (see later), hence imputing according to property type alone and disregarding age and sex is a reasonable strategy.The process of randomly imputing property records, and hence Townsend and proximity scores, to the 112,248 population according to housing type is not trivial. Using ordinary stratified sampling does not work, simply because the number of residents is larger than the number of properties. The overall occupancy ratio was 112,248 residents in 54,801 properties, i.e. 2.05 individuals per property, but this figure varied widely between the 94 property types. For example, for property type 1 there were just under 2 people per property, 114 properties and 226 population. We then choose randomly 114 of the 226 population to match one-to-one to the 114 properties in a random order, leaving the remaining 112 to be matched to a random sample of the 114 properties also in a random order. This simply achieves a maximal degree of representativity with an appropriate degree of randomness. A multi-stage randomisation and linkage process (further details available from the authors) successfully linked the vast majority (14,081/14,171) of first attendances with the merged population-properties file. This has the effect of producing a merged data file in which the deprivation and distance scores randomly imputed to the uninjured both incorporate the correct means to produce an appropriate degree of adjustment for confounding, and also the correct amount of variation to produce appropriate logistic regression coefficients to perform the adjustment.The resulting linked file, comprising reconstructed data for all 112,248 residents, containing elements originating in population, properties and events files, has complete data for demographics, property type and randomly imputed Townsend and proximity measures. Among the 112,248 subjects, 14,081 are identified as having had one or more attendances for injuries following home accidents. Actual Townsend and proximity measures and the code for injury type 1 are available for each of the 14,081 injured individuals.The actual and imputed Townsend and proximity values were summarised for the injured and uninjured and compared. This was done by t-test, paired or unpaired as appropriate, rather than by non-parametric methods which were associated with a serious loss of power due to the gross discreteness of the small area based, randomly imputed Townsend score. Associations between random and actual Townsend and proximity scores were characterised by Spearman rank correlations. Examination of these results, together with the low correlations of a risk score for age and sex with those for property type variables, Townsend and proximity, suggested it was appropriate to include in the logistic regression model composite Townsend and proximity scores, defined as the actual value in the injured and the randomly imputed value in the uninjured. Property size, age and build type were entered as categorical variables. Preliminary analyses indicated that Townsend score should be included as a continuous variable, but distance from hospital discretised into five categories. On account of the known marked sex-age interaction, sex and subject's age were entered together as a 42-group categorical variable, age being discretised into groups under 1, 1–4, 5–9, ..., 90–94 and 95 and over.The main analysis proceeded as above, using the 14,081 who were ever injured during the study period as the group with the outcome of interest. Both univariate analyses for each explanatory variable in turn and a multivariate analysis were produced.Also, the main analysis was repeated after re-running the randomisation parts of the linkage process. This step is more radical than might appear. In particular, due to the small amount of missing data, the randomised matching program does not pick up exactly the same set of 14,081 events records on both occasions. Essentially, the process draws 14,081 out of 14,114 potentially matchable events.Table Table The effect of the random imputation process was explored in the main logistic regression model. In the final model the effect of age and sex jointly was dominant, followed by build type, then distance, property age, Townsend score  and floor area (p = 0.007). Table The results of the main multiple logistic regression model in table The main methodological finding of the study is that the random imputation process developed here is a reasonable one. This approach enabled us to base analyses on a very large dataset notwithstanding confidentiality issues precluding comprehensive linkage directly at individual level. It is feasible to incorporate randomisation into the linkage process, even when the target group is larger than the source. The reasonableness of the imputation process can be judged by comparison of the actual and imputed variables for the injured population. For the Townsend score the actual and imputed scores are essentially identical in distribution, thus showing that the methodology does not produce a biased result. For the distance variable the mean imputed value is 7.4% higher than the actual distance. Whilst this difference is statistically significant the magnitude of the effect on residual confounding cannot be large, given the odds ratios for attendance rates by distance in Table th (most distant) one. These figures are similar to those obtained in the univariate logistic regression based on the composite distance measure, and suggest that the latter regression coefficients, and hence also those in the multiple regression, may be attenuated by around 10% only.The low correlation between randomly imputed and actual values, for distance from hospital and Townsend score, could result in attenuated regression coefficients and hence underadjustment for the confounding effect of these variables. For distance, which is by far the more influential of the two variables, a logistic regression in which the entire population of 112,248 is assumed to have the same distribution into the 5 distance groups as applies to the 54,801 properties gives odds ratios 1.469, 1.318, 1.445, 1.200 for the first 4 distance categories relative to the 5Of primary importance to the validity of the methodology set out here, the results obtained after a second randomisation were almost identical. The unadjusted analyses for age-sex and housing type were unaltered, as these variables do not come from the random imputation. The analyses for deprivation and proximity and the results of multivariate analyses for build type and other variables were altered, but only to a very minor degree. These results provide considerable reassurance that the random element that was necessary in order to achieve the linkage process introduced very little additional uncertainty into the final analyses.It appears that injured people tend to live in property types more associated with deprivation than the uninjured. Their actual Townsend scores are in line with what we would expect from their property types. On the composite data, i.e. when we replace random by actual Townsend scores for the injured only, there is a substantial difference in mean Townsend score, 0.85 v. 0.70, and all the 0.15 points difference is attributable to a real effect of deprivation on risk.(6). On the composite data (with means 7.73 v. 8.37 km), nearly the whole of the difference (0.57 out of 0.64 km) is attributable to this self-selection effect.Conversely, the injured and uninjured tend to live in property types equally distanced from hospital. The actual distance is less for the injured than the randomly imputed distance, which is in line with the known tendency for hospital attendance for less serious types of injury to be related to proximityThis process is an important methodological development to increase the power of linkage studies when all individual data elements are not available for all individuals. As a result the analysis was based on 112,248 subjects and not on ninety-four groups. Thus, the power to detect important differences is substantially enhanced.Further work is continuing in the relationship between specific features of built type and injury occurrence, using the methodology described in this paper.The author(s) declare that they have no competing interests.All authors contributed to the design of the study. RGN devised the conceptual design of the data imputation and carried out the statistical analysis. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


In the first part of the study healthy controls (n = 18) were compared with euthymic Bipolar Disorder patients (Type I and Type II) who were taking either lithium (n = 14) or sodium valproate (n = 11), and temporal lobe choline/creatine (Cho/Cr) ratios were determined. In the second part we examined a separate group of euthymic Bipolar Disorder Type I patients taking sodium valproate (n = 9) and compared these to controls (n = 11). Here we measured the absolute concentrations of choline in both temporal and frontal lobes.The present study utilized The results from the first part of the study showed that bipolar patients chronically treated with both lithium and sodium valproate had significantly reduced temporal lobe Cho/Cr ratios. In contrast, in the second part of the study, there were no effects of sodium valproate on either absolute choline concentrations or on Cho/Cr ratios in either temporal or frontal lobes.These findings suggest that measuring Cho/Cr ratios may not accurately reflect brain choline concentrations. In addition, the results do not support previous suggestions that either lithium or valproate increases choline concentrations in bipolar patients. Bipolar disorder is a chronic severe mental illness affecting approximately 1% of the adult population. The most widely used mood stabilizer for this condition is lithium , and humin vivo utilizes proton magnetic resonance spectroscopy (1H-MRS). Previous studies of bipolar patients utilizing this methodology have had mixed findings. Overall, while some studies have suggested there may be increased choline concentrations in specific situations [The most appropriate method to measure brain choline concentrations tuations -18, moretuations -27, and tuations . In bothtuations ,30. Nonetuations ,32, althin-vitro study suggested that valproate may inhibit choline acetyltransferase activity [Sodium valproate is also widely used as a mood stabilizer, both alone and in combination with lithium . To dateactivity . In one activity , and incactivity . Nonethe1H-MRS spectra is composed primarily of phosphocholine and glycerophosphocholine, along with free choline, acetylcholine, and cytidine diphosphate choline. Also, we have shown in animal studies that both lithium and valproate can both decrease creatine concentrations [Most of the previous studies have examined Cho/Cr ratios. However, it should be noted that the "choline" resonance peak seen in trations . TherefoIn the first part of the study patients taking either lithium or valproate were examined using the Cho/Cr ratio method, and both Bipolar Type I and Bipolar Type II patients were included who could also be taking other medications. In the second part of this study only Bipolar Type I patients on valproate monotherapy were included, and quantification of choline concentrations was made. Some of the data from the first part of this study has been reported previously .All subjects gave full informed consent, and both studies were approved by the ethics committee at the University of Alberta. Healthy controls were examined using a detailed, but non-standardized, psychiatric interview. They were excluded if there was any personal history, or immediate family history, of psychiatric disorder. For patients, diagnoses were made using DSM-IV criteria for Bipolar Disorder Type I or Type II following detailed psychiatric interview, with additional information being available in almost all cases from long-term psychiatric clinic records. They also had to be taking a dose of either lithium or valproate which maintained their blood levels within the ranges of 0.4–1.2 mmol/l for lithium and 200–700 μmol/l for sodium valproate. Serum lithium and valproate levels were also measured on the day of MRS scanning. Other medications taken by the patient were noted. In the second part of the study the same criteria were used, except that only patients meeting diagnostic criteria for Bipolar Disorder Type I were included, and they had to be on sodium valproate monotherapy. This was done to examine Bipolar Type I patients in more detail, and to remove a possible confounding variable. All patients had to be euthymic for the previous 3 months, as determined by interviews with the patient, and additional interviews with their relatives and bipolar clinic records when available. MRS scans were carried out within 24 hours of this interview.1H measurements.For both studies magnetic resonance experiments were performed using a Magnex 3 T scanner with 80 cm bore equipped with actively shielded gradient, and spectrometer control was provided by an Surrey Medical Imaging System (SMIS) console. The subjects head was immobilized with a restraint system. Signal transmission and reception were achieved using a quadrature birdcage resonator for 1H MR spectra were acquired using the PRESS localization method [1H MRS spectra in which all the major metabolite peaks can be seen.Initially, MRI data were acquired using gradient echo imaging sequences to produce multiple slice images along both coronal and transverse planes. This allowed registration of a 2 × 2 × 3 cm volume-of-interest (VOI) to be selected in the temporal lobe. n method ,40, with3 voxels placed in the cortex of the left frontal lobe, the cortex of the left temporal lobe, and in the external standard solution. The average coordinates [1 and T2 values of the metabolites in the brain and external standard solution, MRS data were collected with different TE values at a constant TR and different TR values at a constant TE both for the healthy volunteers and the patients and also from external standard solution [3), it was not possible to exactly match the voxel size or location between the two studies.To accurately quantify the brain concentration of creatine we used a 125 ml glass sphere containing a solution of 4 mmol creatine as an external standard. The PRESS sequence was used to acquire proton MRS data with TE1 = 25 msec, TE2 = 25 msec, TR = 3000 msec, and 128 scan averages. The MRS data were acquired from three 2 × 2 × 2 cmrdinates ,42 of thb, in millimoles per kg of wet brain, the CSF volume fraction, fcsf, in the spectroscopic voxels must be corrected. Thus, brain metabolite concentrations were calculated as described in the following equation:For quantitative measurement of brain metabolite concentrations we used previously described methodology ,43. In tvoxel is the volume of a 8 cm3 spectroscopic voxel [b represents the number of metabolite molecules per unit voxel in brain.where Vic voxel , and Nb post-hoc Tukey tests. The MRS data was analyzed using Student's unpaired t-test using a significance level of p < 0.05 comparing diagnostic groups (patients vs controls) in each brain region .Means ± SEM were used in the statistical analysis. Sex differences were analyzed using chi-squared, and age differences with ANOVA with A total of 18 healthy controls, 14 bipolar patients taking lithium, and 11 bipolar patients taking valproate completed this study. Of the 14 bipolar patients taking lithium, 7 were Type I and 7 were Type II. In the valproate group, 7 were Type I and 4 were Type II. These groups were studied both separately and together, but as there were no statistically significant differences between the Type I and Type II patients, the results for both types are presented together. Of the 14 bipolar patients taking lithium 12 patients were taking other psychotropic medications: these were benzodiazepines (7 patients), antidepressants (5 patients), and antipsychotics (2 patients). Of the 11 patients taking sodium valproate 10 patients were taking other psychotropic medications: these were benzodiazepines (5 patients), antidepressants (5 patients), and antipsychotics (4 patients).post hoc, p < 0.05).The mean age for the lithium group was 40.43 ± 2.96 years, for the valproate group 35.47 ± 2.27 years, and for the control group was 31.35 ± 2.89 years. These differences were statistically significant (F = 3.68, df = 2, p = <0.05), which was attributable to the lithium group being significantly older than the control group (Tukey 2 = 0.167, df 1, p > 0.05), 5 females and 9 males in the lithium group (χ2 = 1.143, df 1, p > 0.05), and 6 females and 5 males in the valproate group (χ2 = 0.474, df 1, p > 0.05).There were no gender differences within the groups: 10 females and 8 males in the control group  as a primary correlate of Choline concentrations. This result has been reported briefly in a previous publication . The meaA total of 11 healthy controls and 9 Bipolar Type I patients taking valproate as monotherapy were entered into this study. The mean age for the control group was 37.3 ± 2.2 years, and for the valproate patients 42.4 ± 3.0 years. These differences were not statistically significant (F = 1.49, df = 1, p = 0.27).2 = 0.474, df 1, p > 0.05). The mean serum valproate levels were 472 ± 36 μmol/l, and the range was 284–728 μmol/l.There were no gender differences within the groups: 7 females and 2 males in the valproate group and 5 females and 6 males in the control group  or temporal (t = 0.203 df = 18, p = 0.84) lobes  or temporal (t = 0.539, df = 18, p = 0.59) lobes . ThirdlWe conclude that, taking all current evidence together including the findings from the present study, it is unlikely that either lithium or valproate significantly alter brain choline concentrations. However, given the large differences in patients populations, medications received, and MRS methodologies it is difficult to directly compare all these studies. In addition, the methodology used to measure choline concentrations can significantly alter the results. Future MRS studies in bipolar patients should, therefore, examine metabolite concentrations rather than a ratio of choline compared to other metabolites.None declared.


The key elements in tuberculosis (TB) control are to cure the individual patient, interrupt transmission of TB to others and prevent the tubercle bacilli from becoming drug resistant. Incomplete treatment may result in excretion of bacteria that may also acquire drug resistance and cause increased morbidity and mortality. Treatment outcome results serves as a tool to control the quality of TB treatment provided by the health care system. The aims of this study were to evaluate the treatment outcome for new cases of culture positive pulmonary TB registered in Norway during the period 1996–2002 and to identify factors associated with non-successful treatment.This was a register-based cohort study. Treatment outcome was assessed according to sex, birthplace, age group, isoniazid (INH) susceptibility, mode of detection and treatment periods (1996–1997, 1998–1999 and 2000–2002). Logistic regression was also used to estimate the odds ratio for treatment success vs. non-success with 95% confidence interval (CI), taking the above variables into account.Among the 655 patients included, the total treatment success rate was 83% (95% CI 80%–86%). The success rates for those born in Norway and abroad were 79% (95% CI 74%–84%) and 86% (95% CI 83%–89%) respectively. There was no difference in success rates by sex and treatment periods. Twenty-two patients (3%) defaulted treatment, 58 (9%) died and 26 (4%) transferred out. The default rate was higher among foreign-born and male patients, whereas almost all who died were born in Norway. The majority of the transferred out group left the country, but seven were expelled from the country. In the multivariate analysis, only high age and initial INH resistance remained as significant risk factors for non-successful treatment.Although the TB treatment success rate in Norway has increased compared to previous studies and although it has reached a reasonable target for treatment outcome in low-incidence countries, the total success rate for 1996–2002 was still slightly below the WHO target of success rate of 85%. Early diagnosis of TB in elderly patients to reduce the death rate, abstaining from expulsion of patients on treatment and further measures to prevent default could improve the success rate further. The key elements in tuberculosis (TB) control are to detect the disease as early as possible and to ensure that those diagnosed complete their treatment and get cured. The World Health Organization (WHO) target for treatment success is 85 percent of all detected smear-positive cases . Even whNorway has about 4.5 million inhabitants, with foreign-born residents comprising 6.9% of the total population in 2002. The proportion of TB cases from foreign-born residents has increased from 19 % in 1986 to 76 % in 2002 [The aims of this study were to evaluate the treatment outcome for new culture positive pulmonary TB cases registered in Norway during the period 1996–2002, and to identify factors associated with non-successful treatment.Mycobacteria. A total of 25 microbiological laboratories isolate M. tuberculosis from patient samples. The laboratory at the Norwegian Institute of Public Health functions as a national reference laboratory for TB. The Pharmacy at the National Hospital is the only pharmacy distributing drugs for TB treatment, and TB prescriptions are compared with the National TB Registry in order to identify cases that may not have been notified. The notification is therefore considered to be quite complete [This was a register-based cohort study. In Norway, there is compulsory nominative notification of all TB cases directly to the National TB Registry. Both suspected and confirmed cases have to be reported by clinicians. Laboratories of clinical microbiology are also required to report all isolates of complete . There iIn this study, we included all new cases with culture positive pulmonary TB notified during 1996–2002. The sputum smear results were not recorded or reported for all cases, especially in the first years of the study period. We therefore based our analysis of treatment outcome on new cases with culture positive pulmonary TB.The mode of detection was determined by information on the notification form. Data on susceptibility to TB drugs was obtained from the notification forms and laboratory reports. In addition to the information in the TB Registry, we used data from the Cause of Death Registry at Statistics Norway to determine the cause of death for those who died under treatment or before start of treatment.Recommended regime for TB treatment in the study period consisted of isoniazid (INH), rifampicin and pyrazinamide in the intensive phase (two months). Ethambutol was added when resistance was suspected such as in foreign-born patients and in previously treated patients. The continuation phase consisted of four months with INH and rifampicin .Directly Observed Therapy (DOT) was used before 2003 on an individual basis. However, we have no data to show how many patients in this study received DOT.cured (finished treatment with negative bacteriology result at the end of treatment), completed treatment (finished treatment, but without bacteriology result at the end of treatment), failure (remaining smear/ culture positive at five months despite correct intake of medication), defaulted treatment (patients who interrupted their treatment for two consecutive months or more after registration), died (patients who died due to TB or other cause before or during treatment), transferred out (patients whose treatment results are unknown due to emigration before or during treatment). Patients who changed treatment due to multi-drug resistant TB (MDR-TB), i.e. resistance to both INH and rifampicin, were also defined as failures [The treatment outcome was divided into six categories according to WHO guidelines, with some modifications . These cfailures .Treatment success was defined as the sum of the cases that were cured and that completed treatment.The proportion of patients with a potentially bacteriologically unsuccessful outcome (failure, default, transfer) was also calculated .We used the statistical package SPSS, version 11.0 for data analysis. To estimate the odds ratio for treatment outcome (success vs. non-success), logistic regression analysis was used. Confidence interval (CI) for the odds ratio has also been given. Variables such as sex, birthplace, age group, INH susceptibility, mode of detection and treatment periods (1996–1997, 1998–1999 and 2000–2002) were entered into both univariate and multivariate logistic regression model. P values of less than 0.05 were considered statistically significant.Six hundred and fifty-five new culture positive pulmonary TB patients were included in the study table . Of thesIn our study, the proportion of patients with a potentially bacteriologically unsuccessful outcome (failure, default, transfer) was 8%.The average duration of residence in Norway for foreign-born patients at TB registration was 3.8 (range 1–31) years. There were no differences in the treatment success rates for those who had lived in Norway for less than three years and for those who had stayed longer than three years.Among the 22 patients who defaulted treatment (3%) table , four haThere were 26 patients (4%) who were transferred out table . Of thesAltogether 58 patients (9%) died, 19 (3%) before treatment start and 39 (6%) while on treatment. Of those who died before treatment start, four were diagnosed after death at autopsy. Eighty four percent of those who died were born in Norway. The median age for all who died was 80 years. For those who died before treatment start, the median age was 71 years. For those who died while on treatment, the median age was 81 years and the average duration of treatment was 67 days. Sixteen patients died within 14 days of treatment start. For 23 patients, TB was the primary cause of death. It was the only cause of death for nine of those 23 patients. For further 20 patients, TB was a contributing factor to their death. Fourteen patients died from other diseases than TB. The cause of death was unknown for one patient (table There was no systematic registration of TB/ human immunodeficiency virus (HIV) co-infection at the TB Registry. For those who died while on treatment or before treatment started, HIV disease was registered as the cause of death for two patients table .Table Susceptibility testing for the main TB drugs was done in most of the patients. However, susceptibility testing for streptomycin was done for fewer patients than other main TB drugs. Resistance to INH and streptomycin was most common, and resistance was frequent among foreign-born patients. Of those with MDR-TB, two were born in Norway and eight abroad.Of the 655 patients included in this study, 453 were detected through passive case finding (due to their symptoms). Another 101 patients were discovered through the immigration TB screening program. A total of 52 patients were detected through following ups of close contacts of identified infectious cases (22 cases) and of previous abnormal mass miniature radiology (MMR) (32 cases). The remainder was discovered through other screening programs. No information on mode of detection was available for three patients.In our study, the total treatment success rate for new culture positive pulmonary TB for the period 1996–2002 was 83%. This is close to the WHO target of success rate of 85% of all smear positive cases. However, subgroups of patients contributing to low success rate warrant special attention such as those who defaulted treatment, those who were transferred out and those who died. The first two subgroups mainly comprise patients who were born abroad and the last subgroup mainly comprises patients who were born in Norway. Despite these problems, Norway has reached the reasonable target for treatment outcome in low-incidence countries .Our study shows a default rate of 3%. Higher default rates have been described in other studies such as Vaud County, Switzerland (16%) , HamburgIn the transferred out group, the majority of patients left the country on their own initiative, but seven were expelled. Most of the patients who left the country were on treatment, but we do not have information about their treatment outcome. It is worrying that some of the patients who were expelled moved to countries with political unrest and poorly functioning TB programs. In this group three patients already had isolated INH resistant strains and one had MDR-TB. Expelling patients with TB before completion of treatment is unfortunate, unless it can be guaranteed that adequate treatment will be provided elsewhere. Efforts should be made to ensure the continuity of treatment for patients who move out of the country and, if possible, to allow them to start and complete their treatment, even if they have to leave the country later. The Netherlands have adopted a system where patients are not expelled from the country as long as they are on treatment. According to the new Norwegian manual for TB control and prevention , health The death rate in our study was 9%. Other studies from low TB incidence regions of the world showed death rates among TB patients of 24%, 14% and 6% in Baltimore City, USA , Vaud CoAs indicated in the results section, TB/HIV co-infection is not a common cause of death for TB patients in Norway as most of the patients born in Norway were elderly persons with low risk of HIV and most foreign-born patients were from countries with low levels of HIV infection . TherefoIn the logistic regression model, increasing age and INH resistance were significant risk factors for non-successful treatment. We expected to find that age played a role, since old age in itself will contribute towards higher mortality, partly through co-existing illness. INH is a powerful bactericidal drug and resistance to the drug might reduce the effectiveness of standard short-course treatment . TreatmeAlthough the TB treatment success rate in Norway has increased compared to previous studies and although it has reached a reasonable target for treatment outcome in low-incidence countries, the total success rate for 1996–2002 was still slightly below the WHO target of success rate of 85%. Early diagnosis of TB in elderly patients to reduce the death rate, abstaining from expulsion of patients on treatment and further measures to prevent default could improve the success rate further.CI- Confidence intervalHIV- Human immunodeficiency virusINH- IsoniazidIUATLD- International Union Against Tuberculosis and Lung DiseaseKCNV-Royal Netherlands Tuberculosis AssociationMDR-TB- Multi-drug resistant tuberculosis, i.e. resistance to both isoniazid and rifampicinTB- TuberculosisWHO- World Health OrganizationThe author(s) declare that they have no competing interests.MGF participated in all phases of preparation of the manuscript  and is corresponding author. AT, TWS, EH, ABB and GB have participated the interpretation of results and writing of the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here: