To What Extent Do Local Nursing Home Prescribing Patterns Relate to Psychotropic Prescribing in Assisted Living?

ObjectiveIn nursing homes (NHs), psychoactive medication use has received notable attention, but less is known about prescribing in assisted living (AL). This study examined how antipsychotic and antianxiety medication prescribing in AL compares with NHs.DesignObservational, cross-sectional AL data linked to publicly reported NH measures.Setting and ParticipantsRandom sample of 250 AL communities and the full sample of 3371 NHs in 7 states.MethodsWe calculated the percentage of residents receiving antipsychotics and antianxiety medications. For each AL community, we calculated the distance to NHs in the state. Linear models estimated the relationship between AL prescribing and that of the closest and farthest 5 NHs, adjusting for AL characteristics and state fixed effects.ResultsThe prescribing rate of potentially inappropriate antipsychotics (i.e., excluding for persons with recorded schizophrenia and Tourette syndrome) and of antianxiety medications (excluding for those on hospice) in AL was 15% and 21%, respectively. Unadjusted mean antipsychotic prescribing rates were nominally higher in AL than NHs (14.8% vs 14.6%; P = .056), whereas mean antianxiety prescribing was nominally lower in AL (21.2% vs 22.6%; P = .032). In adjusted analyses, AL rates of antipsychotic use were not associated with NH rates. However, being affiliated with an NH was associated with a lower rate of antipsychotic use [b = −0.03; 95% confidence interval (CI) −0.50 to −0.001; P = .043], whereas antianxiety rates were associated with neighboring NHs’ prescribing rates (b = 0.43; 95% CI 0.16–0.70; P = .002).Conclusions and ImplicationsThis study suggests reducing antipsychotic medication use in NHs may influence AL practices in a way not accounted for by local NH patterns. And, because antianxiety medications have not been the focus of national campaigns, they may be more subject to local prescribing behaviors. It seems advantageous to consider prescribing in AL when efforts are implemented to change NH prescribing, as there seems to be related influence whether by affiliation or region.     

Methods for development of a core outcome set for clinical trials integrating traditional Chinese medicine and Western medicine

Clinical trial outcome reporting differs between studies integrating traditional Chinese medicine (TCM) and Western medicine, so that some clinical trials are not eligible for inclusion in a systematic review. The excluded studies are therefore less widely disseminated, and even valid studies are less likely to yield impact. This problem may be addressed by developing core outcome sets (COSs) for integrative medicine in specific healthcare areas. The first stage of development is to define the scope of the COS for integrative medicine, the second stage is to establish the need for such a COS, and the third stage is to develop a protocol and register the COS. The final stage involves three steps: (i) development of a comprehensive list of outcomes (including efficacy outcomes and safety outcomes and TCM syndromes) using systematic review, qualitative or cross-sectional research, and reviews of package inserts and medical records; (ii) merging and grouping of outcomes within domains; (iii) conducting two rounds of Delphi survey and consensus meetings with a range of stakeholders. The final COS will include a general COS and core TCM syndrome- set. Development of COSs for clinical trials of integrative medicine may help to standardize outcome reporting and reduce publication bias in the future.     

Whole genome analysis to detect potential vaccine-induced changes on Shigella sonnei genome

Shigellosis or bacillary dysentery is endemic worldwide and is a significant cause of death in children less than five years of age in developing countries. There are no licensed Shigella vaccines and glycoconjugates are among the leading candidate vaccines against shigellosis today.We used whole genome sequence analysis (WGA) to find out whether immunization, with an investigational Shigella sonnei glycoconjugate, could induce selective pressure leading to changes in the genome of S. sonnei. An outbreak of culture-proven S. sonnei shigellosis which occurred immediately after vaccination in one of the cohorts of volunteers participating in a phase III trial of the vaccine in Israel created a unique condition in which the epidemic agent “co-existed” with the developing immune responses induced by the vaccine and natural infection among vaccinees who developed S. sonnei shigellosis. By comparing the whole genomes of S. sonnei isolated from vaccinees and from volunteers in the control group, we show at a very high sensitivity that a potent S. sonnei glycoconjugate that conferred 74% protective efficacy against the homologous disease did not induce changes in the genome of S. sonnei and in particular on the O-antigen gene cluster.     

Polygenic risk scores and risk-stratified breast cancer screening: Familiarity and perspectives of health care professionals

PurposeHealth care professionals are expected to take on an active role in the implementation of risk-based cancer prevention strategies. This study aimed to explore health care professionals’ (1) self-reported familiarity with the concept of polygenic risk score (PRS), (2) perceived level of knowledge regarding risk-stratified breast cancer (BC) screening, and (3) preferences for continuing professional development.MethodsA cross-sectional survey was conducted using a bilingual—English/French—online questionnaire disseminated by health care professional associations across Canada between November 2020 and May 2021.ResultsA total of 593 professionals completed more than 2 items and 453 responded to all questions. A total of 432 (94%) participants were female, 103 (22%) were physicians, and 323 (70%) were nurses. Participants reported to be unfamiliar with (20%), very unfamiliar (32%) with, or did not know (41%) the concept of PRS. Most participants reported not having enough knowledge about risk-stratified BC screening (61%) and that they would require more training (77%). Online courses and webinar conferences were the preferred continuing professional development modalities.ConclusionThe study indicates that health care professionals are currently not familiar with the concept of PRS or a risk-stratified approach for BC screening. Online information and training seem to be an essential knowledge transfer modality.     

Heterozygous loss-of-function variants in LHX8 cause female infertility characterized by oocyte maturation arrest

PurposeThe genetic causes of oocyte maturation arrest leading to female infertility are largely unknown, and no population-based genetic analysis has been applied in cohorts of patients with infertility. We aimed to identify novel pathogenic genes causing oocyte maturation arrest by using a gene-based burden test.MethodsThrough comparison of exome sequencing data from 716 females with infertility characterized by oocyte maturation arrest and 3539 controls, we performed a gene-based burden test and identified a novel pathogenic gene LHX8. Splicing event was evaluated using a minigene assay, expression of LHX8 protein was assessed in HeLa cells, and nuclear subcellular localization was determined in both HeLa cells and mouse oocytes.ResultsA total of 5 heterozygous loss-of-function LHX8 variants were identified from 6 independent families (c.389+1G>T, c.412C>T [p.Arg1381], c.282C>A [p.Cys941]; c.257dup [p.Tyr861]; and c.180del, [p.Ser61Profs130]). All the identified variants in LHX8 produced truncated LHX8 protein and resulted in loss of LHX8 nuclear localization in both HeLa cells and mouse oocytes.ConclusionBy combining genetic evidence and functional evaluations, we identified a novel pathogenic gene LHX8 and established the causative relationship between LHX8 haploinsufficiency and female infertility characterized by oocyte maturation arrest.     

Application of an extreme learning machine network with particle swarm optimization in syndrome classification of primary liver cancer

ObjectiveBy optimizing the extreme learning machine network with particle swarm optimization, we established a syndrome classification and prediction model for primary liver cancer (PLC), classified and predicted the syndrome diagnosis of medical record data for PLC and compared and analyzed the prediction results with different algorithms and the clinical diagnosis results. This paper provides modern technical support for clinical diagnosis and treatment, and improves the objectivity, accuracy and rigor of the classification of traditional Chinese medicine (TCM) syndromes.MethodsFrom three top-level TCM hospitals in Nanchang, 10,602 electronic medical records from patients with PLC were collected, dating from January 2009 to May 2020. We removed the electronic medical records of 542 cases of syndromes and adopted the cross-validation method in the remaining 10,060 electronic medical records, which were randomly divided into a training set and a test set. Based on fuzzy mathematics theory, we quantified the syndrome-related factors of TCM symptoms and signs, and information from the TCM four diagnostic methods. Next, using an extreme learning machine network with particle swarm optimization, we constructed a neural network syndrome classification and prediction model that used “TCM symptoms + signs + tongue diagnosis information + pulse diagnosis information” as input, and PLC syndrome as output. This approach was used to mine the nonlinear relationship between clinical data in electronic medical records and different syndrome types. The accuracy rate of classification was used to compare this model to other machine learning classification models.ResultsThe classification accuracy rate of the model developed here was 86.26%. The classification accuracy rates of models using support vector machine and Bayesian networks were 82.79% and 85.84%, respectively. The classification accuracy rates of the models for all syndromes in this paper were between 82.15% and 93.82%.ConclusionCompared with the case of data processed using traditional binary inputs, the experiment shows that the medical record data processed by fuzzy mathematics was more accurate, and closer to clinical findings. In addition, the model developed here was more refined, more accurate, and quicker than other classification models. This model provides reliable diagnosis for clinical treatment of PLC and a method to study of the rules of syndrome differentiation and treatment in TCM.     

Rate of re-bleeding of arteriovenous malformations in the first year after rupture

Prior rupture is an established risk factor for subsequent hemorrhage from arteriovenous malformations (AVM). Recent natural history studies have reinvigorated the important concept that the re-bleed rate is not constant; rather, it is particularly greater in the first year after hemorrhage. In this study, we reviewed our own cohort of 129 patients with AVMs. Eighty-one presented with hemorrhage (63%), and of these patients, 38 had at least one month of subsequent clinical follow-up and were included in our analysis. Over a total of 140 patient-years, the annual re-hemorrhage rate was 7.9%, though it was 15.8% in the first year. Two-thirds of those AVM that hemorrhaged in the first year were associated with aneurysms. The overall permanent morbidity of re-hemorrhage was 45%; the mortality rate was 9%. Although the re-hemorrhage rate in the first year varied from 6% to 15.8% across series in the literature, it was generally double the overall re-hemorrhage rate provided in each study. These results have significant therapeutic implications, favoring surgical treatment of ruptured AVM and/or their associated aneurysm when feasible to avoid the incumbent greater risk of early rehemorrhage.