Accuracy in precordial ECG lead placement: Improving performance through a peer-led educational intervention

Background and objectives

Inaccurate electrocardiography (ECG) lead placement may lead to erroneous diagnoses, such as poor R wave progression. We sought to assess the accuracy of precordial ECG lead placement amongst hospital staff members, and to re-evaluate performance after an educational intervention.

Coaggregation of the T-cell receptor with CD4 and other T-cell surface molecules enhances T-cell activation

The CD4 molecule, expressed by T cells restricted by class II major histocompatibility complex (MHC) molecules, is believed to play a role in T-cell activation. We have previously suggested that CD4 interacts with the T-cell receptor for antigen (TCR) and with class II MHC and that this dual interaction stabilizes the bond between the TCR and antigen in association with MHC. To investigate the contribution of CD4-TCR interaction, we have used the murine monoclonal anti-TCR V beta 8 antibody F23.1 to activate cloned T cells. Weak activation by soluble biotinylated F23.1 was markedly enhanced by crosslinking with either avidin or with anti-immunoglobulin (anti-Ig). The monoclonal anti-L3T4 antibody GK1.5, which normally inhibits the activation induced by F23.1, did not inhibit when GK1.5 and F23.1 were coaggregated on T cells by anti-Ig, and in many experiments activation was enhanced. Coaggregation of anti-Thy-1.2, anti-H-2Kk, or anti-LFA-1 with F23.1 also enhanced T-cell activation, although, unlike GK1.5, these antibodies in soluble form had no effect on the response to F23.1. These results are consistent with a model for T-cell activation that proposes a primary interaction between L3T4 and the TCR to stabilize TCR complexes and so to enhance T-cell activation. A related but less specific accessory role for other T-cell surface molecules is also suggested. We propose that the cellular interaction that leads to physiological T-cell activation not only achieves TCR ligation but also promotes through their ligation or redistribution the interaction of other T-cell surface molecules, all of which contribute to the overall strength of the activation signal.     

The effects of glucose-dependent insulinotropic polypeptide infused at physiological concentrations in normal subjects and Type 2 (non-insulin-dependent) diabetic patients on glucose tolerance and B-cell secretion

Summary The effects of porcine glucose-dependent insulinotropic polypeptide given by continuous intravenous infusion in normal subjects (n=6) and Type 2 (non-insulin-dependent) diabetic patients (n=6) have been investigated. The subjects were studied on 2 separate days after overnight fasts. On each day 25 g of glucose was infused from 0–30 min plus an infusion of either porcine glucose-dependent insulinotropic polypeptide (0.75 pmol·kg^–1·min^–1) or control solution. During the glucose-dependent insulinotropic polypeptide infusion plasma glucose values were reduced in normal subjects from 30–60 min (p<0.01) and in Type 2 diabetic patients at 45 and 60 min (p<0.05). In the normal subjects insulin concentrations were greater from 10–35 min (p<0.01) following glucose-dependent insulinotropic polypeptide infusion and peak values were increased by 123%. In the Type 2 diabetic patients following glucose-dependent insulinotropic polypeptide infusion insulin levels were increased from 4–40 min (p<0.01) but peak values were only increased by 27%. In the normal subjects C-peptide values were greater from 25–45 min (p<0.01) following glucose-dependent insulinotropic polypeptide infusion and peak C-peptide levels were increased by 82%. In the Type 2 diabetic patients following the glucose-dependent insulinotropic polypeptide infusion C-peptide levels were increased from 6–55 min (p<0.01) and peak values were increased by 20%. Plasma glucose-dependent insulinotropic polypeptide levels were within the physiological post prandial range during the glucose-dependent insulinotropic polypeptide infusion. Glucose-dependent insulinotropic polypeptide is insulinotropic in normal subjects and Type 2 diabetic patients at physiological concentrations and results in improved glucose tolerance. This insulinotropic effect is less marked in the diabetic patients and may represent insensitivity of the B cell to glucose-dependent insulinotropic polypeptide.     

Improving attention control in dysphoria through cognitive training: Transfer effects on working memory capacity and filtering efficiency

Impaired filtering of irrelevant information from working memory is thought to underlie reduced working memory capacity for relevant information in dysphoria. The current study investigated whether training‐related gains in working memory performance on the adaptive dual n‐back task could result in improved inhibitory function. Efficacy of training was monitored in a change detection paradigm allowing measurement of a sustained event‐related potential asymmetry sensitive to working memory capacity and the efficient filtering of irrelevant information. Dysphoric participants in the training group showed training‐related gains in working memory that were accompanied by gains in working memory capacity and filtering efficiency compared to an active control group. Results provide important initial evidence that behavioral performance and neural function in dysphoria can be improved by facilitating greater attentional control.     

Serum pooling for rapid expansion of anti-SARS-CoV-2 antibody testing capacity

ObjectivesExamine possible pooling strategies designed to expand SARS-CoV-2 serological testing capacity.MethodsNegative pools were assessed to determine optimal optical density (OD) cutoffs, followed by spiking weak or strong positive samples to assess initial assay performance. Samples were then randomly subjected to pool and individual testing approaches.ResultsSingle positive specimens consistently converted pools of 5, 10, or 20 into positive outcomes. However, weaker IgG-positive samples failed to similarly convert pools of 50 to a positive result. In contrast, a stronger individual positive sample converted all pools tested into positive outcomes. Finally, examination of 150 samples configured into pools of 5, 10, 20 or 50 accurately predicted the presence of positive or negative specimens within each pool.ConclusionsThese results suggest that pooling strategies may allow expansion of serological testing capacity. While limitations exist, such strategies may aid in large-scale epidemiological screening or identification of optimal convalescent plasma donors.     

“Many miles to go …”: a systematic review of the implementation of patient decision support interventions into routine clinical practice

Background

Two decades of research has established the positive effect of using patient-targeted decision support interventions: patients gain knowledge, greater understanding of probabilities and increased confidence in decisions. Yet, despite their efficacy, the effectiveness of these decision support interventions in routine practice has yet to be established; widespread adoption has not occurred. The aim of this review was to search for and analyze the findings of published peer-reviewed studies that investigated the success levels of strategies or methods where attempts were made to implement patient-targeted decision support interventions into routine clinical settings.

Methods

An electronic search strategy was devised and adapted for the following databases: ASSIA, CINAHL, Embase, HMIC, Medline, Medline-in-process, OpenSIGLE, PsycINFO, Scopus, Social Services Abstracts, and the Web of Science. In addition, we used snowballing techniques. Studies were included after dual independent assessment.

Results

After assessment, 5322 abstracts yielded 51 articles for consideration. After examining full-texts, 17 studies were included and subjected to data extraction. The approach used in all studies was one where clinicians and their staff used a referral model, asking eligible patients to use decision support. The results point to significant challenges to the implementation of patient decision support using this model, including indifference on the part of health care professionals. This indifference stemmed from a reported lack of confidence in the content of decision support interventions and concern about disruption to established workflows, ultimately contributing to organizational inertia regarding their adoption.

Conclusions

It seems too early to make firm recommendations about how best to implement patient decision support into routine practice because approaches that use a ‘referral model’ consistently report difficulties. We sense that the underlying issues that militate against the use of patient decision support and, more generally, limit the adoption of shared decision making, are under-investigated and under-specified. Future reports from implementation studies could be improved by following guidelines, for example the SQUIRE proposals, and by adopting methods that would be able to go beyond the ‘barriers’ and ‘facilitators’ approach to understand more about the nature of professional and organizational resistance to these tools. The lack of incentives that reward the use of these interventions needs to be considered as a significant impediment.