Early life characteristics, social mobility during childhood and risk of stroke in later life: findings from a Swedish cohort.

AIMS: To investigate if early life characteristics and social mobility during childhood are associated with incident thrombotic stroke (TS), haemorrhagic stroke (HS) and other stroke (OS). METHODS: Our study population consists of all live births at Uppsala University Hospital in 1915-1929 (Uppsala Birth Cohort; n = 14,192), of whom 5532 males and 5061 females were singleton births and lived in Sweden in 1964. We followed them from 1 January 1964 until first diagnosis of stroke (in the National Patient Register or Causes of Death Register), emigration, death, or until 31 December 2008. Data were analysed using Cox regression, stratifying by gender. RESULTS: Gestational age was negatively associated with TS and OS in women only. Women had increased risk of TS if they were born early preterm (<35 weeks) (HR 1.54 (95% CI 1.02-2.31)) or preterm (35-36 weeks) (HR 1.37 (95% CI 1.03-1.83)) compared to women born at term. By contrast, only women who were early preterm (HR 1.98 (95% CI 1.27-3.10) had an increased risk of OS. Men who were born post-term (⩾42 weeks) had increased risk of HS (HR 1.45 (95% CI 1.04-2.01)) compared with men born at term, with no association for women. TS was associated with social mobility during childhood in women: women whose families were upwardly or downwardly mobile had increased risk of TS compared to women who were always advantaged during childhood. CONCLUSIONS: Gestational age and social mobility during childhood were associated with increased risk of stroke later in life, particularly among women, but there was some heterogeneity between stroke subtypes

Development of the Perinatal Depression Inventory (PDI)-14 using item response theory: a comparison of the BDI-II, EPDS, PDI, and PHQ-9

The objective of this study is to develop a simple, brief, self-report perinatal depression inventory that accurately measures severity in a number of populations. Our team developed 159 Likert-scale perinatal depression items using simple sentences with a fifth-grade reading level. Based on iterative cognitive interviewing (CI), an expert panel improved and winnowed the item pool based on pre-determined criteria. The resulting 67 items were administered to a sample of 628 pregnant and 251 postpartum women with different levels of depression at private and public sector obstetrics clinics, together with the Beck Depression Inventory (BDI-II), Edinburg Postpartum Depression Scale (EPDS), and the Patient Health Questionnaire (PHQ-9), as well as Module A of the Structured Clinical Interview for DSM-IV Diagnoses (SCID). Responses were evaluated using Item Response Theory (IRT). The Perinatal Depression Inventory (PDI)-14 items are highly informative regarding depression severity and function similarly and informatively across pregnant/postpartum, white/non-white, and private-clinic/public-clinic populations. PDI-14 scores correlate well with the PHQ-9, EPDS, and BDI-II, but the PDI-14 provides a more precise measure of severity using far fewer words. The PDI-14 is a brief depression assessment that excels at accurately measuring depression severity across a wide range of severity and perinatal populations.Electronic supplementary materialThe online version of this article (doi:10.1007/s00737-015-0553-9) contains supplementary material, which is available to authorized users

Cluster headache attack remission with sphenopalatine ganglion stimulation:experiences in chronic cluster headache patients through 24 months

BACKGROUND: Cluster headache (CH) is a debilitating headache disorder with severe consequences for patient quality of life. On-demand neuromodulation targeting the sphenopalatine ganglion (SPG) is effective in treating the acute pain and a subgroup of patients experience a decreased frequency of CH attacks. METHODS: We monitored self-reported attack frequency, headache disability, and medication intake in 33 patients with medically refractory, chronic CH (CCH) in an open label follow-up study of the original Pathway CH-1 study. Patients were followed for at least 24 months (average 750 ± 34 days, range 699-847) after insertion of an SPG microstimulator. Remission periods (attack-free periods exceeding one month, per the ICHD 3 (beta) definition) occurring during the 24-month study period were characterized. Attack frequency, acute effectiveness, medication usage, and questionnaire data were collected at regular clinic visits. The time point “after remission” was defined as the first visit after the end of the remission period. RESULTS: Thirty percent (10/33) of enrolled patients experienced at least one period of complete attack remission. All remission periods followed the start of SPG stimulation, with the first period beginning 134 ± 86 (range 21-272) days after initiation of stimulation. On average, each patient’s longest remission period lasted 149 ± 97 (range 62-322) days. The ability to treat acute attacks before and after remission was similar (37 % ± 25 % before, 49 % ± 32 % after; p = 0.2188). Post-remission headache disability (HIT-6) was significantly improved versus baseline (67.7 ± 6.0 before, 55.2 ± 11.4 after; p = 0.0118). Six of the 10 remission patients experienced clinical improvements in their preventive medication use. At 24 months post insertion headache disability improvements remained and patient satisfaction measures were positive in 100 % (10/10). CONCLUSIONS: In this population of 33 refractory CCH patients, in addition to providing the ability to treat acute attacks, neuromodulation of the SPG induced periods of remission from cluster attacks in a subset of these. Some patients experiencing remission were also able to reduce or stop their preventive medication and remissions were accompanied by an improvement in headache disability

Latitude drives diversification in M adagascar's endemic dry forest rodent E liurus myoxinus (subfamily N esomyinae)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100288/1/bij12143.pd

Designing a complex intervention for dementia case management in primary care

Background: Community-based support will become increasingly important for people with dementia, but currently services are fragmented and the quality of care is variable. Case management is a popular approach to care co-ordination, but evidence to date on its effectiveness in dementia has been equivocal. Case management interventions need to be designed to overcome obstacles to care co-ordination and maximise benefit. A successful case management methodology was adapted from the United States (US) version for use in English primary care, with a view to a definitive trial. Medical Research Council guidance on the development of complex interventions was implemented in the adaptation process, to capture the skill sets, person characteristics and learning needs of primary care based case managers. Methods: Co-design of the case manager role in a single NHS provider organisation, with external peer review by professionals and carers, in an iterative technology development process. Results: The generic skills and personal attributes were described for practice nurses taking up the case manager role in their workplaces, and for social workers seconded to general practice teams, together with a method of assessing their learning needs. A manual of information material for people with dementia and their family carers was also created using the US intervention as its source. Conclusions: Co-design produces rich products that have face validity and map onto the complexities of dementia and of health and care services. The feasibility of the case manager role, as described and defined by this process, needs evaluation in ‘real life’ settings

Single-molecule live-cell imaging reveals RecB-dependent function of DNA polymerase IV in double strand break repair

© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. Several functions have been proposed for the Escherichia coli DNA polymerase IV (pol IV). Although much research has focused on a potential role for pol IV in assisting pol III replisomes in the bypass of lesions, pol IV is rarely found at the replication fork in vivo. Pol IV is expressed at increased levels in E. coli cells exposed to exogenous DNA damaging agents, including many commonly used antibiotics. Here we present live-cell single-molecule microscopy measurements indicating that double-strand breaks induced by antibiotics strongly stimulate pol IV activity. Exposure to the antibiotics ciprofloxacin and trimethoprim leads to the formation of double strand breaks in E. coli cells. RecA and pol IV foci increase after treatment and exhibit strong colocalization. The induction of the SOS response, the appearance of RecA foci, the appearance of pol IV foci and RecA-pol IV colocalization are all dependent on RecB function. The positioning of pol IV foci likely reflects a physical interaction with the RecA* nucleoprotein filaments that has been detected previously in vitro. Our observations provide an in vivo substantiation of a direct role for pol IV in double strand break repair in cells treated with double strand break-inducing antibiotics

Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining

Background Worldwide, over 14% of individuals hospitalized for psychiatric reasons have readmissions to hospitals within 30 days after discharge. Predicting patients at risk and leveraging accelerated interventions can reduce the rates of early readmission, a negative clinical outcome (i.e., a treatment failure) that affects the quality of life of patient. To implement individualized interventions, it is necessary to predict those individuals at highest risk for 30-day readmission. In this study, our aim was to conduct a data-driven investigation to find the pharmacological factors influencing 30-day all-cause, intra- and interdepartmental readmissions after an index psychiatric admission, using the compendium of prescription data (prescriptome) from electronic medical records (EMR). Methods The data scientists in the project received a deidentified database from the Mount Sinai Data Warehouse, which was used to perform all analyses. Data was stored in a secured MySQL database, normalized and indexed using a unique hexadecimal identifier associated with the data for psychiatric illness visits. We used Bayesian logistic regression models to evaluate the association of prescription data with 30-day readmission risk. We constructed individual models and compiled results after adjusting for covariates, including drug exposure, age, and gender. We also performed digital comorbidity survey using EMR data combined with the estimation of shared genetic architecture using genomic annotations to disease phenotypes. Results Using an automated, data-driven approach, we identified prescription medications, side effects (primary side effects), and drug-drug interaction-induced side effects (secondary side effects) associated with readmission risk in a cohort of 1275 patients using prescriptome analytics. In our study, we identified 28 drugs associated with risk for readmission among psychiatric patients. Based on prescription data, Pravastatin had the highest risk of readmission (OR = 13.10; 95% CI (2.82, 60.8)). We also identified enrichment of primary side effects (n = 4006) and secondary side effects (n = 36) induced by prescription drugs in the subset of readmitted patients (n = 89) compared to the non-readmitted subgroup (n = 1186). Digital comorbidity analyses and shared genetic analyses further reveals that cardiovascular disease and psychiatric conditions are comorbid and share functional gene modules (cardiomyopathy and anxiety disorder: shared genes (n = 37; P = 1.06815E-06)). Conclusions Large scale prescriptome data is now available from EMRs and accessible for analytics that could improve healthcare outcomes. Such analyses could also drive hypothesis and data-driven research. In this study, we explored the utility of prescriptome data to identify factors driving readmission in a psychiatric cohort. Converging digital health data from EMRs and systems biology investigations reveal a subset of patient populations that have significant comorbidities with cardiovascular diseases are more likely to be readmitted. Further, the genetic architecture of psychiatric illness also suggests overlap with cardiovascular diseases. In summary, assessment of medications, side effects, and drug-drug interactions in a clinical setting as well as genomic information using a data mining approach could help to find factors that could help to lower readmission rates in patients with mental illness