'Door-to-prophylaxis' as a novel quality improvement metric in prevention of venous thromboembolism following traumatic injury

Objective

Venous thromboembolism (VTE) risk reduction strategies include early initiation of chemoprophylaxis, reducing missed doses, weight-based dosing and dose adjustment using anti-Xa levels. We hypothesized that time to initiation of chemoprophylaxis would be the strongest modifiable risk for VTE, even after adjusting for competing risk factors.

Methods

A prospectively maintained trauma registry was queried for patients admitted July 2017-October 2021 who were 18 years and older and received emergency release blood products. Patients with deep vein thrombosis or pulmonary embolism (VTE) were compared to those without (no VTE). Door-to-prophylaxis was defined as time from hospital arrival to first dose of VTE chemoprophylaxis (hours). Univariate and multivariate analyses were then performed between the two groups.

Results

2047 patients met inclusion (106 VTE, 1941 no VTE). There were no differences in baseline or demographic data. VTE patients had higher injury severity score (29 vs 24), more evidence of shock by arrival lactate (4.6 vs 3.9) and received more post-ED transfusions (8 vs 2 units); all p<0.05. While there was no difference in need for enoxaparin dose adjustment or missed doses, door-to-prophylaxis time was longer in the VTE group (35 vs 25 hours; p=0.009). On multivariate logistic regression analysis, every hour delay from time of arrival increased likelihood of VTE by 1.5% (OR 1.015, 95% CI 1.004 to 1.023, p=0.004).

Conclusion

The current retrospective study of severely injured patients with trauma who required emergency release blood products found that increased door-to-prophylaxis time was significantly associated with an increased likelihood for VTE. Chemoprophylaxis initiation is one of the few modifiable risk factors available to combat VTE, therefore early initiation is paramount. Similar to door-to-balloon time in treating myocardial infarction and door-to-tPA time in stroke, "door-to-prophylaxis time" should be considered as a hospital metric for prevention of VTE in trauma.

Level of evidence

Level III, retrospective study with up to two negative criteria.

Measuring the Use of End-of-Life Symptom Relief Medications in Long-Term Care Homes-a Qualitative Study

Background

At the end of life, individuals may experience physical symptoms such as pain, and guidelines recommend medications to manage these symptoms. Yet, little is known about the symptom management long-term care (LTC) residents receive at the end of life. Our research team developed a metric-whether residents receive one or more prescriptions for an end-of-life symptom management medication in their last two weeks-to explore end-of-life care for LTC residents. This qualitative study aimed to inform the refinement of the end-of-life prescribing metric, including the acceptability and applicability to assess the quality of a resident's symptom management at end-of-life.

Methods

We conducted 14 semi-structured interviews with Ontario health-care providers (physicians and nurses) who work in LTC homes and family caregivers of residents who died in LTC. Interviews were conducted virtually between February 2021 and December 2022, and were analyzed using thematic analysis.

Results

We identified three major themes relating to perceptions of the metric: 1) appropriateness, 2) health-care provider applicability, and 3) caregiver applicability. Participants noted that the metric may be appropriate to assess end-of-life care, but noted important nuances. Regarding applicability, health-care providers found value in the metric and that it could inform their practice. Conversely, caregivers found limited value in the metric.

Conclusion

The proposed metric captures a very specific aspect of end-of-life care-whether end-of-life medications were prescribed or not. Participants deemed that the metric may reflect whether LTC homes have processes to manage a resident's end-of-life symptoms with medication. However, participants thought the metric could not provide a complete picture of end-of-life care and its quality.

More than metrics: The role of socio-environmental factors in determining the success of athlete monitoring

The perceived value of athlete monitoring systems (AMS) has recently been questioned. Poor perceptions of AMS are important, because where practitioners lack confidence in monitoring their ability to influence programming, and performance is likely diminished. To address this, researchers have primarily sought to improve factors related to monitoring metrics, e.g., validity rather than socio-environmental factors, e.g., buy-in. Seventy-five practitioners (response rate: n = 30) working with Olympic and Paralympic athletes were invited to take part in a survey about their perceptions of AMS value. Fifty-two per cent (n = 13) was confident in the sensitivity of their athlete self-report measures, but only 64% (n = 16), indicated their monitoring was underpinned by scientific evidence. A scientific base was associated with improved athlete feedback (rS (23) = 0.487, p =0.014*) and feedback correlated with athlete monitoring adherence (rS (22) = 0.675, p =  <0.001**). If athletes did not complete their monitoring, 52% (n = 13) of respondents felt performance might be compromised. However, most respondents 56% (n = 14), had worked with internationally successful athlete(s) who did not complete their monitoring. While AMS can be a useful tool to aid performance optimisation, its potential value is not always realised. Addressing socio-environmental factors alongside metric-factors may improve AMS efficacy.

RNAdvisor: a comprehensive benchmarking tool for the measure and prediction of RNA structural model quality

RNA is a complex macromolecule that plays central roles in the cell. While it is well known that its structure is directly related to its functions, understanding and predicting RNA structures is challenging. Assessing the real or predictive quality of a structure is also at stake with the complex 3D possible conformations of RNAs. Metrics have been developed to measure model quality while scoring functions aim at assigning quality to guide the discrimination of structures without a known and solved reference. Throughout the years, many metrics and scoring functions have been developed, and no unique assessment is used nowadays. Each developed assessment method has its specificity and might be complementary to understanding structure quality. Therefore, to evaluate RNA 3D structure predictions, it would be important to calculate different metrics and/or scoring functions. For this purpose, we developed RNAdvisor, a comprehensive automated software that integrates and enhances the accessibility of existing metrics and scoring functions. In this paper, we present our RNAdvisor tool, as well as state-of-the-art existing metrics, scoring functions and a set of benchmarks we conducted for evaluating them. Source code is freely available on the EvryRNA platform: https://evryrna.ibisc.univ-evry.fr.

Model-based evaluation of spatiotemporal data reduction methods with unknown ground truth through optimal visualization and interpretability metrics

Optimizing and benchmarking data reduction methods for dynamic or spatial visualization and interpretation (DSVI) face challenges due to many factors, including data complexity, lack of ground truth, time-dependent metrics, dimensionality bias and different visual mappings of the same data. Current studies often focus on independent static visualization or interpretability metrics that require ground truth. To overcome this limitation, we propose the MIBCOVIS framework, a comprehensive and interpretable benchmarking and computational approach. MIBCOVIS enhances the visualization and interpretability of high-dimensional data without relying on ground truth by integrating five robust metrics, including a novel time-ordered Markov-based structural metric, into a semi-supervised hierarchical Bayesian model. The framework assesses method accuracy and considers interaction effects among metric features. We apply MIBCOVIS using linear and nonlinear dimensionality reduction methods to evaluate optimal DSVI for four distinct dynamic and spatial biological processes captured by three single-cell data modalities: CyTOF, scRNA-seq and CODEX. These data vary in complexity based on feature dimensionality, unknown cell types and dynamic or spatial differences. Unlike traditional single-summary score approaches, MIBCOVIS compares accuracy distributions across methods. Our findings underscore the joint evaluation of visualization and interpretability, rather than relying on separate metrics. We reveal that prioritizing average performance can obscure method feature performance. Additionally, we explore the impact of data complexity on visualization and interpretability. Specifically, we provide optimal parameters and features and recommend methods, like the optimized variational contractive autoencoder, for targeted DSVI for various data complexities. MIBCOVIS shows promise for evaluating dynamic single-cell atlases and spatiotemporal data reduction models.

Brain organoid data synthesis and evaluation

Introduction

Datasets containing only few images are common in the biomedical field. This poses a global challenge for the development of robust deep-learning analysis tools, which require a large number of images. Generative Adversarial Networks (GANs) are an increasingly used solution to expand small datasets, specifically in the biomedical domain. However, the validation of synthetic images by metrics is still controversial and psychovisual evaluations are time consuming.

Methods

We augment a small brain organoid bright-field database of 40 images using several GAN optimizations. We compare these synthetic images to the original dataset using similitude metrcis and we perform an psychovisual evaluation of the 240 images generated. Eight biological experts labeled the full dataset (280 images) as syntetic or natural using a custom-built software. We calculate the error rate per loss optimization as well as the hesitation time. We then compare these results to those provided by the similarity metrics. We test the psychovalidated images in a training step of a segmentation task.

Results and discussion

Generated images are considered as natural as the original dataset, with no increase of the hesitation time by experts. Experts are particularly misled by perceptual and Wasserstein loss optimization. These optimizations render the most qualitative and similar images according to metrics to the original dataset. We do not observe a strong correlation but links between some metrics and psychovisual decision according to the kind of generation. Particular Blur metric combinations could maybe replace the psychovisual evaluation. Segmentation task which use the most psychovalidated images are the most accurate.

Analytical Study of Mandible: Prerequisite for Sex Determination

Background

Human skull consists of various bones. One of them is mandible which is quite resistant, tough and shows systemic differences in form between individuals of different sex. It resists putrefaction also. There are characteristic features in the mandible that help us to differentiate sex in case of unknown victims like in mass disasters or in case fragmentary remains of the skeleton are found. Analysis of mandible with regard to its features is of great assistance in the determination of sex.

Materials and Methods

A total of 80 dry mandible bones were collected. Morphological and morphometric parameters were studied to determine their sex. A total of nine parameters, i.e., three non-metric and six metric parameters were observed for each mandible. Data was collected for each parameter.

Results

Among 80 dry mandible bones, 55 were males and 25 were females. 81.2% males bones had a square chin whereas, 80% females had a rounded chin. Gonial flare was everted in 89% males and inverted in 68% females.

Conclusion

Mandible exhibits significant sexual differences. Various morphological and morphometric parameters are essential for sex determination in case of mandible bone.

A proposed metric set for evaluation of genome assembly quality

Quality control is essential for genome assemblies; however, a consensus has yet to be reached on what metrics should be adopted for the evaluation of assembly quality. N50 is widely used for contiguity measurement, but its effectiveness is constantly in question. Prevailing metrics for the completeness evaluation focus on gene space, yet challenging areas such as tandem repeats are commonly overlooked. Achieving correctness has become an indispensable dimension for quality control, while prevailing assembly releases lack scores reflecting this aspect. We propose a metric set with a set of statistic indexes for effective, comprehensive evaluation of assemblies and provide a score of a finished assembly for each metric, which can be utilized as a benchmark for achieving high-quality genome assemblies.

Effects of Physiological Signal Removal on Resting-State Functional MRI Metrics

Resting-state fMRIs (rs-fMRIs) have been widely used for investigation of diverse brain functions, including brain cognition. The rs-fMRI has easily elucidated rs-fMRI metrics, such as the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), voxel-mirrored homotopic connectivity (VMHC), and degree centrality (DC). To increase the applicability of these metrics, higher reliability is required by reducing confounders that are not related to the functional connectivity signal. Many previous studies already demonstrated the effects of physiological artifact removal from rs-fMRI data, but few have evaluated the effect on rs-fMRI metrics. In this study, we examined the effect of physiological noise correction on the most common rs-fMRI metrics. We calculated the intraclass correlation coefficient of repeated measurements on parcellated brain areas by applying physiological noise correction based on the RETROICOR method. Then, we evaluated the correction effect for five rs-fMRI metrics for the whole brain: FC, fALFF, ReHo, VMHC, and DC. The correction effect depended not only on the brain region, but also on the metric. Among the five metrics, the reliability in terms of the mean value of all ROIs was significantly improved for FC, but it deteriorated for fALFF, with no significant differences for ReHo, VMHC, and DC. Therefore, the decision on whether to perform the physiological correction should be based on the type of metric used.

The non-Riemannian nature of perceptual color space

For over 100 y, the scientific community has adhered to a paradigm, introduced by Riemann and furthered by Helmholtz and Schrodinger, where perceptual color space is a three-dimensional Riemannian space. This implies that the distance between two colors is the length of the shortest path that connects them. We show that a Riemannian metric overestimates the perception of large color differences because large color differences are perceived as less than the sum of small differences. This effect, called diminishing returns, cannot exist in a Riemannian geometry. Consequently, we need to adapt how we model color differences, as the current standard, ΔE, recognized by the International Commission for Weights and Measures, does not account for diminishing returns in color difference perception.

The scientific community generally agrees on the theory, introduced by Riemann and furthered by Helmholtz and Schrödinger, that perceived color space is not Euclidean but rather, a three-dimensional Riemannian space. We show that the principle of diminishing returns applies to human color perception. This means that large color differences cannot be derived by adding a series of small steps, and therefore, perceptual color space cannot be described by a Riemannian geometry. This finding is inconsistent with the current approaches to modeling perceptual color space. Therefore, the assumed shape of color space requires a paradigm shift. Consequences of this apply to color metrics that are currently used in image and video processing, color mapping, and the paint and textile industries. These metrics are valid only for small differences. Rethinking them outside of a Riemannian setting could provide a path to extending them to large differences. This finding further hints at the existence of a second-order Weber–Fechner law describing perceived differences.

A New Performance Metric to Estimate the Risk of Exposure to Infection in a Health Care Setting: Descriptive Study

Background

Despite several measures to monitor and improve hand hygiene (HH) in health care settings, health care-acquired infections (HAIs) remain prevalent. The measures used to calculate HH performance are not able to fully benefit from the high-resolution data collected using electronic monitoring systems.

Objective

This study proposes a novel parameter for quantifying the HAI exposure risk of individual patients by considering temporal and spatial features of health care workers’ HH adherence.

Methods

Patient exposure risk is calculated as a function of the number of consecutive missed HH opportunities, the number of unique rooms visited by the health care professional, and the time duration that the health care professional spends inside and outside the patient’s room without performing HH. The patient exposure risk is compared to the entrance compliance rate (ECR) defined as the ratio of the number of HH actions performed at a room entrance to the total number of entrances into the room. The compliance rate is conventionally used to measure HH performance. The ECR and the patient exposure risk are analyzed using the data collected from an inpatient nursing unit for 12 weeks.

Results

The analysis of data collected from 59 nurses and more than 25,600 records at a musculoskeletal rehabilitation unit at the Toronto Rehabilitation Institute, KITE, showed that there is no strong linear relation between the ECR and patient exposure risk (r=0.7, P<.001). Since the ECR is calculated based on the number of missed HH actions upon room entrance, this parameter is already included in the patient exposure risk. Therefore, there might be scenarios that these 2 parameters are correlated; however, in several cases, the ECR contrasted with the reported patient exposure risk. Generally, the patients in rooms with a significantly high ECR can be potentially exposed to a considerable risk of infection. By contrast, small ECRs do not necessarily result in a high patient exposure risk. The results clearly explained the important role of the factors incorporated in patient exposure risk for quantifying the risk of infection for the patients.

Conclusions

Patient exposure risk might provide a more reliable estimation of the risk of developing HAIs compared to ECR by considering both the temporal and spatial aspects of HH records.

Assessment of helicopter passengers' vibration discomfort: proposal for improvement of the ISO 2631-1 standard

High levels of vibration exist in helicopters and manufacturers are seeking to quantify vibration discomfort. They use the ISO 2631-1 standard, proposed for all types of transport. This study aimed to verify the validity of this index in the specific case of helicopters. Perception tests were carried out in the laboratory. Volunteers assessed the discomfort of vibratory stimuli on test benches generating vertical and triaxial vibrations. Foot, seat, and backrest accelerations were measured for each participant according to each stimulus. The ISO 2631-1 comfort indices were then compared with the evaluations given by the participants. The results showed that the standard provided a good estimate of discomfort. However, it lacks precision in estimating the discomfort of stimuli which include amplitude modulations, as can happen in helicopters. A new discomfort index is proposed based on ISO 2631-1 and allows better prediction of subjective assessments. Practitioner Summary: An improved index based on ISO 2631-1 standard is proposed to estimate helicopter vibratory discomfort for seated passengers. It takes into account the amplitude modulations that can appear at low frequencies in helicopters. This modification allowed a significant improvement of the accuracy of ISO 2631-1 for such stimuli.

How Trend of Increasing Data Volume Affects the Energy Efficiency of 5G Networks

As the rapid growth of mobile users and Internet-of-Everything devices will continue in the upcoming decade, more and more network capacity will be needed to accommodate such a constant increase in data volumes (DVs). To satisfy such a vast DV increase, the implementation of the fifth-generation (5G) and future sixth-generation (6G) mobile networks will be based on heterogeneous networks (HetNets) composed of macro base stations (BSs) dedicated to ensuring basic signal coverage and capacity, and small BSs dedicated to satisfying capacity for increased DVs at locations of traffic hotspots. An approach that can accommodate constantly increasing DVs is based on adding additional capacity in the network through the deployment of new BSs as DV increases. Such an approach represents an implementation challenge to mobile network operators (MNOs), which is reflected in the increased power consumption of the radio access part of the mobile network and degradation of network energy efficiency (EE). In this study, the impact of the expected increase of DVs through the 2020s on the EE of the 5G radio access network (RAN) was analyzed by using standardized data and coverage EE metrics. An analysis was performed for five different macro and small 5G BS implementation and operation scenarios and for rural, urban, dense-urban and indoor-hotspot device density classes (areas). The results of analyses reveal a strong influence of increasing DV trends on standardized data and coverage EE metrics of 5G HetNets. For every device density class characterized with increased DVs, we here elaborate on the process of achieving the best and worse combination of data and coverage EE metrics for each of the analyzed 5G BSs deployment and operation approaches. This elaboration is further extended on the analyses of the impact of 5G RAN instant power consumption and 5G RAN yearly energy consumption on values of standardized EE metrics. The presented analyses can serve as a reference in the selection of the most appropriate 5G BS deployment and operation approach, which will simultaneously ensure the transfer of permanently increasing DVs in a specific device density class and the highest possible levels of data and coverage EE metrics.

Informing Stewardship Measures in Canadian Food Animal Species through Integrated Reporting of Antimicrobial Use and Antimicrobial Resistance Surveillance Data-Part I, Methodology Development

This study explores methodologies for the data integration of antimicrobial use (AMU) and antimicrobial resistance (AMR) results within and across three food animal species, surveyed at the farm-level by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS). The approach builds upon existing CIPARS methodology and principles from other AMU and AMR surveillance systems. Species level data integration involved: (1) standard CIPARS descriptive and temporal analysis of AMU/AMR, (2) synthesis of results, (3) selection of AMU and AMR outcomes for integration, (4) selection of candidate AMU indicators to enable comparisons of AMU levels between species and simultaneous assessment of AMU and AMR trends, (5) exploration of analytic options for studying associations between AMU and AMR, and (6) interpretation and visualization. The multi-species integration was also completed using the above approach. In addition, summarized reporting of internationally-recognized indicators of AMR (i.e., AMR adjusted for animal biomass) and AMU (mg/population correction unit, mg/kg animal biomass) is explored. It is envisaged that this approach for species and multi-species AMU-AMR data integration will be applied to the annual CIPARS farm-level data and progressively developed over time to inform AMU-AMR integrated surveillance best practices for further enhancement of AMU stewardship actions.

Informing Stewardship Measures in Canadian Food Animal Species through Integrated Reporting of Antimicrobial Use and Antimicrobial Resistance Surveillance Data-Part II, Application

Using the methodology developed for integrated analysis and reporting of antimicrobial use (AMU) and antimicrobial resistance (AMR) data, farm-level surveillance data were synthesized and integrated to assess trends and explore potential AMU and AMR associations. Data from broiler chicken flocks (n = 656), grower-finisher pig herds (n = 462) and turkey flocks (n = 339) surveyed by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) at the farm-level (2015-2019) were used. The analyses showed a reduction in mean flock/herd level number of defined daily doses using Canadian standards (nDDDvetCA) adjusted for kg animal biomass that coincided with the decline in % resistance in the three species. This was noted in most AMU-AMR pairs studied except for ciprofloxacin resistant Campylobacter where resistance continued to be detected (moderate to high levels) despite limited fluoroquinolone use. Noteworthy was the significantly negative association between the nDDDvetCA/kg animal biomass and susceptible Escherichia coli (multispecies data), an early indication that AMU stewardship actions are having an impact. However, an increase in the reporting of diseases in recent years was observed. This study highlighted the value of collecting high-resolution AMU surveillance data with animal health context at the farm-level to understand AMR trends, enable data integration and measure the impact of AMU stewardship actions.

Quantifying Performance in Robotic Surgery Training Using Muscle-Based Activity Metrics

Training to perform robotic surgery is time-consuming with uncertain metrics of the level of achieved skill. We tested the feasibility of using muscle co-contraction as a metric to quantify robotic surgical skill in a virtual simulation environment. We recruited six volunteers with varying skill levels in robotic surgery. The volunteers performed virtual tasks using a robotic console while we recorded their muscle activity. A co-contraction metric was then derived from the activity of pairs of opposing hand muscles and compared to the scores assigned by the training software. We found that muscle-based metrics were more sensitive than motion-based scores in quantifying the different levels of skill between simulated tasks and in novices vs. experts across different tasks. Therefore, muscle-based metrics may help quantify in general terms the level of robotic surgical skill and could potentially be used for biofeedback to increase the rate of learning.

Pediatric/Congenital Cardiac Catheterization Quality: An Analysis of Existing Metrics

OBJECTIVES

The aim of this study was to enumerate and categorize quality metrics relevant to the pediatric/congenital cardiac catheterization laboratory (PCCL).

BACKGROUND

Diagnostic and interventional catheterization procedures are an increasingly important part of the care of young patients with cardiac disease. Measurement of the performance of PCCL programs in a stringent and consistent fashion is a crucial step toward improving outcomes. To the best of our knowledge, a systematic evaluation of current quality metrics in PCCL has not been performed previously.

METHODS

Potential metrics were evaluated by: 1) a systematic review of peer-reviewed research; 2) a review of metrics from organizations interested in quality improvement, patient safety, and/or PCCL programs; and 3) a survey of U.S. PCCL cardiologists. Collected metrics were grouped on 2 dimensions: 1) Institute of Medicine domains; and 2) the Donabedian structure/process/outcome framework. Survey responses were dichotomized between favorable and unfavorable responses and then compared within and between categories.

RESULTS

In the systematic review, 6 metrics were identified (from 9 publications), all focused on safety either as an outcome (adverse events [AEs], mortality, and failure to rescue along with radiation exposure) or as a structure (procedure volume or operator experience). Four organizations measure quality metrics of PCCL programs, of which only 1 publicly reports data. For the survey, 229 cardiologists from 118 hospital programs responded (66% of individuals and 72% of hospital programs). The highest favorable ratings were for safety metrics (p < 0.001), of which major AEs, failure to rescue, and procedure-specific AEs had the highest ratings. Of respondents, 67% stated that current risk adjustment were not effective. Favorability ratings for hospital characteristics, PCCL characteristics, and quality improvement processes were significantly lower than for safety and less consistent within categories.

CONCLUSIONS

There is a limited number of PCCL quality metrics, primarily focused on safety. Confidence in current risk adjustment methodology is low. The knowledge gaps identified should guide future research in the development of new quality metrics.

Some Integral Inequalities Involving Metrics

In this work, we establish some integral inequalities involving metrics. Moreover, some applications to partial metric spaces are given. Our results are extension of previous obtained metric inequalities in the discrete case.

A Novel Metric to Quantify the Effect of Pathway Enrichment Evaluation With Respect to Biomedical Text-Mined Terms: Development and Feasibility Study

BACKGROUND

Natural language processing has long been applied in various applications for biomedical knowledge inference and discovery. Enrichment analysis based on named entity recognition is a classic application for inferring enriched associations in terms of specific biomedical entities such as gene, chemical, and mutation.

OBJECTIVE

The aim of this study was to investigate the effect of pathway enrichment evaluation with respect to biomedical text-mining results and to develop a novel metric to quantify the effect.

METHODS

Four biomedical text mining methods were selected to represent natural language processing methods on drug-related gene mining. Subsequently, a pathway enrichment experiment was performed by using the mined genes, and a series of inverse pathway frequency (IPF) metrics was proposed accordingly to evaluate the effect of pathway enrichment. Thereafter, 7 IPF metrics and traditional P value metrics were compared in simulation experiments to test the robustness of the proposed metrics.

RESULTS

IPF metrics were evaluated in a case study of rapamycin-related gene set. By applying the best IPF metrics in a pathway enrichment simulation test, a novel discovery of drug efficacy of rapamycin for breast cancer was replicated from the data chosen prior to the year 2000. Our findings show the effectiveness of the best IPF metric in support of knowledge discovery in new drug use. Further, the mechanism underlying the drug-disease association was visualized by Cytoscape.

CONCLUSIONS

The results of this study suggest the effectiveness of the proposed IPF metrics in pathway enrichment evaluation as well as its application in drug use discovery.

Journal Metrics in Psychiatry: What do the rankings tell us?

BACKGROUND

Metrics of journal's impact factor may suggest the journal's influence in a particular field, but they have been used inadvertently as a measure of the journal and individual publications' scientific quality.

METHODS

We assessed how scientific journals in the field of psychiatry and mental health are ranked (top 20) according to the scores of distinct metrics (Eigenfactor score, Google Scholar Metrics, Journal Citation Reports, Scimago Journal & Country Rank, and Source Normalized Impact per Paper), described their main characteristics and perfomed a spearman's correlation analyses to investigate to which extent these metrics are associated. We also discussed the limitations of dealing with these metrics and the rankings they provide as a proxy of the journal's quality.

RESULTS

Only 5 (12.5%) journals appear in all metrics (JAMA Psychiatry, American Journal of Psychiatry, Molecular Psychiatry, Schizophrenia Bulletin, and the Journal of Child Psychology and Psychiatry), more than one-third of the journals show up in only one and less than half (42.5%) appear in three or more. Only JAMA Psychiatry is in one of the first five positions of all metrics. No journal ranked in the same position across the metrics. On the other hand, we found the correlations between all the metrics were statistically significant.

LIMITATIONS

The metrics included are not exhaustive.

CONCLUSIONS

Although each metric provides a particular ranking, they are highly correlated. Rankings also change according to distinct subject categories in which they are assessed. We suggest less emphasis should be given to Journal Metrics to infer journal's quality.

Latin America and the Caribbean SARS-CoV-2 Surveillance: Longitudinal Trend Analysis

Background

The COVID-19 pandemic has placed unprecedented stress on economies, food systems, and health care resources in Latin America and the Caribbean (LAC). Existing surveillance provides a proxy of the COVID-19 caseload and mortalities; however, these measures make it difficult to identify the dynamics of the pandemic and places where outbreaks are likely to occur. Moreover, existing surveillance techniques have failed to measure the dynamics of the pandemic.

Objective

This study aimed to provide additional surveillance metrics for COVID-19 transmission to track changes in the speed, acceleration, jerk, and persistence in the transmission of the pandemic more accurately than existing metrics.

Methods

Through a longitudinal trend analysis, we extracted COVID-19 data over 45 days from public health registries. We used an empirical difference equation to monitor the daily number of cases in the LAC as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano–Bond estimator in R. COVID-19 transmission rates were tracked for the LAC between September 30 and October 6, 2020, and between October 7 and 13, 2020.

Results

The LAC saw a reduction in the speed, acceleration, and jerk for the week of October 13, 2020, compared to the week of October 6, 2020, accompanied by reductions in new cases and the 7-day moving average. For the week of October 6, 2020, Belize reported the highest acceleration and jerk, at 1.7 and 1.8, respectively, which is particularly concerning, given its high mortality rate. The Bahamas also had a high acceleration at 1.5. In total, 11 countries had a positive acceleration during the week of October 6, 2020, whereas only 6 countries had a positive acceleration for the week of October 13, 2020. The TAC displayed an overall positive trend, with a speed of 10.40, acceleration of 0.27, and jerk of –0.31, all of which decreased in the subsequent week to 9.04, –0.81, and –0.03, respectively.

Conclusions

Metrics such as new cases, cumulative cases, deaths, and 7-day moving averages provide a static view of the pandemic but fail to identify where and the speed at which SARS-CoV-2 infects new individuals, the rate of acceleration or deceleration of the pandemic, and weekly comparison of the rate of acceleration of the pandemic indicate impending explosive growth or control of the pandemic. Enhanced surveillance will inform policymakers and leaders in the LAC about COVID-19 outbreaks.

Measures of electronic health record use in outpatient settings across vendors

Electronic health record (EHR) log data capture clinical workflows and are a rich source of information to understand variation in practice patterns. Variation in how EHRs are used to document and support care delivery is associated with clinical and operational outcomes, including measures of provider well-being and burnout. Standardized measures that describe EHR use would facilitate generalizability and cross-institution, cross-vendor research. Here, we describe the current state of outpatient EHR use measures offered by various EHR vendors, guided by our prior conceptual work that proposed seven core measures to describe EHR use. We evaluate these measures and other reporting options provided by vendors for maturity and similarity to previously proposed standardized measures. Working toward improved standardization of EHR use measures can enable and accelerate high-impact research on physician burnout and job satisfaction as well as organizational efficiency and patient health.

Metrics for assessing physician activity using electronic health record log data

Electronic health record (EHR) log data have shown promise in measuring physician time spent on clinical activities, contributing to deeper understanding and further optimization of the clinical environment. In this article, we propose 7 core measures of EHR use that reflect multiple dimensions of practice efficiency: total EHR time, work outside of work, time on documentation, time on prescriptions, inbox time, teamwork for orders, and an aspirational measure for the amount of undivided attention patients receive from their physicians during an encounter, undivided attention. We also illustrate sample use cases for these measures for multiple stakeholders. Finally, standardization of EHR log data measure specifications, as outlined here, will foster cross-study synthesis and comparative research.

Inflationary routes to Gaussian curved topography

Gaussian-curved shapes are obtained by inflating initially flat systems made of two superimposed strong and light thermoplastic impregnated fabric sheets heat-sealed together along a specific network of lines. The resulting inflated structures are light and very strong because they (largely) resist deformation by the intercession of stretch. Programmed patterns of channels vary either discretely through boundaries or continuously. The former give rise to faceted structures that are in effect non-isometric origami and that cannot unfold as in conventional folded structures since they present the localized angle deficit or surplus. Continuous variation of the channel direction in the form of spirals is examined, giving rise to curved shells. We solve the inverse problem consisting in finding a network of seam lines leading to a target axisymmetric shape on inflation. They too have strength from the metric changes that have been pneumatically driven, resistance to change being met with stretch and hence high forces like typical shells.

Small and Large Animal Veterinarian Perceptions of Antimicrobial Use Metrics for Hospital-Based Stewardship in the United States

Background: Robust measurement and tracking of antimicrobial use (AMU) is a fundamental component of stewardship interventions. Feeding back AMU metrics to individual clinicians is a common approach to changing prescribing behavior. Metrics must be meaningful and comprehensible to clinicians. Little is known about how veterinary clinicians working in the United States (US) hospital setting think about AMU metrics for antimicrobial stewardship. Objective: To identify hospital-based veterinary clinicians' attitudes toward audit and feedback of AMU metrics, their perceptions of different AMU metrics, and their response to receiving an individualized prescribing report. Methods: Semi-structured interviews were conducted with veterinarians working at two hospitals in the Eastern US. Interviews elicited perceptions of antimicrobial stewardship in veterinary medicine. Respondents were shown a personalized AMU Report characterizing their prescribing patterns relative to their peers and were asked to respond. Interviews were recorded, transcribed, and analyzed using the framework method with matrices. Results: Semi-structured interviews were conducted with 34 veterinary clinicians (22 small animal and 12 large animal). Respondents generally felt positive about the reports and were interested in seeing how their prescribing compared to that of their peers. Many respondents expressed doubt that the reports accurately captured the complexities of their prescribing decisions and found metrics associated with animal daily doses (ADDs) confusing. Only 13 (38.2%) respondents felt the reports would change how they used antimicrobials. When asked how the impact of the reports could be optimized, respondents recommended providing a more detailed explanation of how the AMU metrics were derived, education prior to report roll-out, guidance on how to interpret the metrics, and development of meaningful benchmarks for goal-setting. Conclusions: These findings provide important insight that can be used to design veterinary-specific AMU metrics as part of a stewardship intervention that are meaningful to clinicians and more likely to promote judicious prescribing.

Quantifying the Contribution of Habitats and Pathways to a Spatially Structured Population Facing Environmental Change

The consequences of environmental disturbance and management are difficult to quantify for spatially structured populations because changes in one location carry through to other areas as a result of species movement. We develop a metric, G, for measuring the contribution of a habitat or pathway to network-wide population growth rate in the face of environmental change. This metric is different from other contribution metrics, as it quantifies effects of modifying vital rates for habitats and pathways in perturbation experiments. Perturbation treatments may range from small degradation or enhancement to complete habitat or pathway removal. We demonstrate the metric using a simple metapopulation example and a case study of eastern monarch butterflies. For the monarch case study, the magnitude of environmental change influences the ordering of node contribution. We find that habitats within which all individuals reside during one season are the most important to short-term network growth under complete removal scenarios, whereas the central breeding region contributes most to population growth over all but the strongest disturbances. The metric G provides for more efficient management interventions that proactively mitigate impacts of expected disturbances to spatially structured populations.

Development of an electronic definition for de-escalation of antibiotics in hospitalized patients

BACKGROUND

Antimicrobial stewardship programs (ASPs) promote the principle of de-escalation: moving from broad to narrow spectrum agents and stopping antibiotics when no longer indicated. A standard, objective definition of de-escalation applied to electronic data could be useful for ASP assessments.

METHODS

We derived an electronic definition of antibiotic de-escalation and performed a retrospective study among five hospitals. Antibiotics were ranked into 4 categories: narrow spectrum, broad spectrum, extended spectrum, and agents targeted for protection. Eligible adult patients were cared for on inpatient units, had antibiotic therapy for at least 2 days, and were hospitalized for at least 3 days after starting antibiotics. Number of antibiotics and rank were assessed at two time points: day of antibiotic initiation and either day of discharge or day 5. De-escalation was defined as reduction in either the number of antibiotics or rank. Escalation was an increase in either number or rank. Unchanged was either no change or discordant directions of change. We summarized outcomes among hospitals, units, and diagnoses.

RESULTS

Among 39,226 eligible admissions, de-escalation occurred in 14,138 (36%), escalation in 5,129 (13%), and antibiotics were unchanged in 19,959 (51%). De-escalation varied among hospitals (median 37%, range 31-39%, p<.001). Diagnoses with lower de-escalation rates included intra-abdominal (23%) and skin and soft tissue (28%) infections. Critical care had higher rates of both de-escalation and escalation compared with wards.

CONCLUSIONS

Our electronic de-escalation metric demonstrated variation among hospitals, units, and diagnoses. This metric may be useful for assessing stewardship opportunities and impact.

Reliability assessment for blood oxygen saturation levels measured with optoacoustic imaging

SIGNIFICANCE

Quantitative optoacoustic (OA) imaging has the potential to provide blood oxygen saturation (SO2) estimates due to the proportionality between the measured signal and the blood's absorption coefficient. However, due to the wavelength-dependent attenuation of light in tissue, a spectral correction of the OA signals is required, and a prime challenge is the validation of both the optical characterization of the tissue and the SO2.

AIM

We propose to assess the reliability of SO2 levels retrieved from spectral fitting by measuring the similarity of OA spectra to the fitted blood absorption spectra.

APPROACH

We introduce a metric that quantifies the trends of blood spectra by assigning a pair of spectral slopes to each spectrum. The applicability of the metric is illustrated with in vivo measurements on a human forearm.

RESULTS

We show that physiologically sound SO2 values do not necessarily imply a successful spectral correction and demonstrate how the metric can be used to distinguish SO2 values that are trustworthy from unreliable ones.

CONCLUSIONS

The metric is independent of the methods used for the OA data acquisition, image reconstruction, and spectral correction, thus it can be readily combined with existing approaches, in order to monitor the accuracy of quantitative OA imaging.

Freestanding Dialysis Facility Quality Incentive Program Scores and Mortality Among Incident Dialysis Patients in the United States

RATIONALE & OBJECTIVE

The Centers for Medicare & Medicaid Services introduced the Quality Incentive Program (QIP) along with the bundled payment reform to improve the quality of dialysis care in the United States. The QIP has been criticized for using easily obtained laboratory indicators without patient-centered measures and for a lack of evidence for an association between QIP indicators and patient outcomes. This study examined the association between dialysis facility QIP performance scores and survival among patients after initiation of dialysis.

STUDY DESIGN

Retrospective cohort study.

SETTING & PARTICIPANTS

Study participants included 84,493 patients represented in the US Renal Disease System's patient-level data who had initiated dialysis between January 1, 2013, and December 1, 2013, and who did not, during the first 90 days after dialysis initiation, die, receive a transplant, or become lost to follow-up. Patients were followed up for the study outcome through March 31, 2014.

PREDICTOR

Dialysis facility QIP scores.

OUTCOME

Mortality.

ANALYTICAL APPROACH

Using a unique facility identifier, we linked Medicare freestanding dialysis facility data from 2015 with US Renal Disease System patient-level data. Kaplan-Meier product limit estimator was used to describe the survival of study participants. Cox proportional hazards regression was used to assess the multivariable association between facility performance scores and patient survival.

RESULTS

Excluding patients who died during the first 90 days of dialysis, 11.8% of patients died during an average follow-up of 5 months. Facilities with QIP scores<45 (HR, 1.39; 95% CI, 1.15-1.68) and 45 to<60 (HR, 1.21; 95% CI, 1.10-1.33) had higher patient mortality rates than facilities with scores≥90.

LIMITATIONS

Because the Centers for Medicare & Medicaid Services have revised QIP criteria each year, the findings may not relate to years other than those studied.

CONCLUSIONS

Dialysis facilities characterized by lower QIP scores were associated with higher rates of patient mortality. These findings need to be replicated to assess their consistency over time.

Multiple Instances QoS Routing in RPL: Application to Smart Grids

The Smart Grid (SG) aims to transform the current electric grid into a "smarter" network where the integration of renewable energy resources, energy efficiency and fault tolerance are the main benefits. This is done by interconnecting every energy source, storage point or central control point with connected devices, where heterogeneous SG applications and signalling messages will have different requirements in terms of reliability, latency and priority. Hence, data routing and prioritization are the main challenges in such networks. So far, RPL (Routing Protocol for Low-Power and Lossy networks) protocol is widely used on Smart Grids for distributing commands over the grid. RPL assures traffic differentiation at the network layer in wireless sensor networks through the logical subdivision of the network in multiple instances, each one relying on a specific Objective Function. However, RPL is not optimized for Smart Grids, as its main objective functions and their associated metric does not allow Quality of Service differentiation. To overcome this, we propose OFQS an objective function with a multi-objective metric that considers the delay and the remaining energy in the battery nodes alongside with the dynamic quality of the communication links. Our function automatically adapts to the number of instances (traffic classes) providing a Quality of Service differentiation based on the different Smart Grid applications requirements. We tested our approach on a real sensor testbed. The experimental results show that our proposal provides a lower packet delivery latency and a higher packet delivery ratio while extending the lifetime of the network compared to solutions in the literature.

Cross-cultural measurement invariance of the General Health Questionnaire-12 in a German and a Colombian population sample

While the General Health Questionnaire, 12-item version (GHQ-12) has been widely used in cross-cultural comparisons, rigorous tests of the measurement equivalence of different language versions are still lacking. Thus, our study aims at investigating configural, metric and scalar invariance across the German and the Spanish version of the GHQ-12 in two population samples. The GHQ-12 was applied in two large-scale population-based samples in Germany (N = 1,977) and Colombia (N = 1,500). To investigate measurement equivalence, confirmatory factor analyses were conducted in both samples. In the German sample mean GHQ-12 total scores were higher than in the Colombian sample. A one-factor model including response bias on the negatively worded items showed superior fit in the German and the Colombian sample; thus both versions of the GHQ-12 showed configural invariance. Factor loadings and intercepts were not equal across both samples; thus GHQ-12 showed no metric and scalar invariance. As both versions of the GHQ-12 did not show measurement equivalence, it is not recommendable to compare both measures and to conclude that mental distress is higher in the German sample, although we do not know if the differences are attributable to measurement problems or represent a real difference in mental distress. The study underlines the importance of measurement equivalence in cross-cultural comparisons.

Productivity in Pediatric Palliative Care: Measuring and Monitoring an Elusive Metric

CONTEXT

Workforce productivity is poorly defined in health care. Particularly in the field of pediatric palliative care (PPC), the absence of consensus metrics impedes aggregation and analysis of data to track workforce efficiency and effectiveness. Lack of uniformly measured data also compromises the development of innovative strategies to improve productivity and hinders investigation of the link between productivity and quality of care, which are interrelated but not interchangeable.

OBJECTIVES

To review the literature regarding the definition and measurement of productivity in PPC; to identify barriers to productivity within traditional PPC models; and to recommend novel metrics to study productivity as a component of quality care in PPC.

METHODS

PubMed^® and Cochrane Database of Systematic Reviews searches for scholarly literature were performed using key words (pediatric palliative care, palliative care, team, workforce, workflow, productivity, algorithm, quality care, quality improvement, quality metric, inpatient, hospital, consultation, model) for articles published between 2000 and 2016. Organizational searches of Center to Advance Palliative Care, National Hospice and Palliative Care Organization, National Association for Home Care & Hospice, American Academy of Hospice and Palliative Medicine, Hospice and Palliative Nurses Association, National Quality Forum, and National Consensus Project for Quality Palliative Care were also performed. Additional semistructured interviews were conducted with directors from seven prominent PPC programs across the U.S. to review standard operating procedures for PPC team workflow and productivity.

RESULTS

Little consensus exists in the PPC field regarding optimal ways to define, measure, and analyze provider and program productivity. Barriers to accurate monitoring of productivity include difficulties with identification, measurement, and interpretation of metrics applicable to an interdisciplinary care paradigm. In the context of inefficiencies inherent to traditional consultation models, novel productivity metrics are proposed.

CONCLUSIONS

Further research is needed to determine optimal metrics for monitoring productivity within PPC teams. Innovative approaches should be studied with the goal of improving efficiency of care without compromising value.

Comparing Institution Nitrogen Footprints: Metrics for Assessing and Tracking Environmental Impact

When multiple institutions with strong sustainability initiatives use a new environmental impact assessment tool, there is an impulse to compare. The first seven institutions to calculate nitrogen footprints using the Nitrogen Footprint Tool have worked collaboratively to improve calculation methods, share resources, and suggest methods for reducing their footprints. This article compares those seven institutions' results to reveal the common and unique drivers of institution nitrogen footprints. The footprints were compared by scope and sector, and the results were normalized by multiple factors (e.g., population, amount of food served). The comparisons found many consistencies across the footprints, including the large contribution of food. The comparisons identified metrics that could be used to track progress, such as an overall indicator for the nitrogen sustainability of food purchases. The comparisons also pointed to differences in system bounds of the calculations, which are important to standardize when comparing across institutions. The footprints were influenced by factors both within and outside of the institutions' ability to control, such as size, location, population, and campus use. However, these comparisons also point to a pathway forward for standardizing nitrogen footprint tool calculations, identifying metrics that can be used to track progress, and determining a sustainable institution nitrogen footprint.

Landscape composition and configuration in the central highlands of Ethiopia

Landscape dynamics are common phenomenon in the human-dominated environments whereby it can be observed that the composition and configuration between landscape elements change over time. This dynamism brings about habitat loss and fragmentation that can greatly alter ecosystem services at patch, class, and landscape levels. We conducted a study to examine composition and configuration of forested landscape in the central highlands of Ethiopia using satellite images of over a period of four decades, and FRAGSTAT raster dataset was used to analyze fragmentation. Our result showed five land use/land cover (LULC) types in the study area. Cultivated land and settlement land increased at the expense of forestland, shrubland, and grassland. Fragmentation analysis showed the number of patches increased for all LULC types, indicating the level of fragmentation and interspersion. Juxtaposition increased for shrubland, grassland, and cultivated lands and decreased for settlement and forestland resulting in the fragmentation and isolation of patches. The study of LULC along with fragmentation at the landscape level can help improve our understanding of the pace at which conversion of landscape elements is happening and the impacts on ecosystem services as studies of LULC are courser in nature and would not show how each land use is reducing in size, proximity and shape among other things that determine ecosystem services. Such type of studies in rural landscapes are very vital to consider appropriate land management policies for the landscape level by taking into account the interaction between each element for sustainable development. We recommend land managers, conservationists, and land owners for observing the roles of each patch in the matrix to maximize the benefits than focusing on a single element.

Seizure control as a new metric in assessing efficacy of tumor treatment in low-grade glioma trials

Patients with low-grade glioma frequently have brain tumor-related epilepsy, which is more common than in patients with high-grade glioma. Treatment for tumor-associated epilepsy usually comprises a combination of surgery, anti-epileptic drugs (AEDs), chemotherapy, and radiotherapy. Response to tumor-directed treatment is measured primarily by overall survival and progression-free survival. However, seizure frequency has been observed to respond to tumor-directed treatment with chemotherapy or radiotherapy. A review of the current literature regarding seizure assessment for low-grade glioma patients reveals a heterogeneous manner in which seizure response has been reported. There is a need for a systematic approach to seizure assessment and its influence on health-related quality-of-life outcomes in patients enrolled in low-grade glioma therapeutic trials. In view of the need to have an adjunctive metric of tumor response in these patients, a method of seizure assessment as a metric in brain tumor treatment trials is proposed.

Predicting shunt failure in children: should the global shunt revision rate be a quality measure?

OBJECT

Ventricular shunts for pediatric hydrocephalus continue to be plagued with high failure rates. Reported risk factors for shunt failure are inconsistent and controversial. The raw or global shunt revision rate has been the foundation of several proposed quality metrics. The authors undertook this study to determine risk factors for shunt revision within their own patient population.

METHODS

In this single-center retrospective cohort study, a database was created of all ventricular shunt operations performed at the authors' institution from January 1, 2010, through December 2013. For each index shunt surgery, demographic, clinical, and procedural variables were assembled. An "index surgery" was defined as implantation of a new shunt or the revision or augmentation of an existing shunt system. Bivariate analyses were first performed to evaluate individual effects of each independent variable on shunt failure at 90 days and at 180 days. A final multivariate model was chosen for each outcome by using a backward model selection approach.

RESULTS

There were 466 patients in the study accounting for 739 unique ("index") operations, for an average of 1.59 procedures per patient. The median age for the cohort at the time of the first shunt surgery was 5 years (range 0-35.7 years), with 53.9% males. The 90- and 180-day shunt failure rates were 24.1% and 29.9%, respectively. The authors found no variable-demographic, clinical, or procedural-that predicted shunt failure within 90 or 180 days.

CONCLUSIONS

In this study, none of the risk factors that were examined were statistically significant in determining shunt failure within 90 or 180 days. Given the negative findings and the fact that all other risk factors for shunt failure that have been proposed in the literature thus far are beyond the control of the surgeon (i.e., nonmodifiable), the use of an institution's or individual's global shunt revision rate remains questionable and needs further evaluation before being accepted as a quality metric.

A thesaurus for a neural population code

Information is carried in the brain by the joint spiking patterns of large groups of noisy, unreliable neurons. This noise limits the capacity of the neural code and determines how information can be transmitted and read-out. To accurately decode, the brain must overcome this noise and identify which patterns are semantically similar. We use models of network encoding noise to learn a thesaurus for populations of neurons in the vertebrate retina responding to artificial and natural videos, measuring the similarity between population responses to visual stimuli based on the information they carry. This thesaurus reveals that the code is organized in clusters of synonymous activity patterns that are similar in meaning but may differ considerably in their structure. This organization is highly reminiscent of the design of engineered codes. We suggest that the brain may use this structure and show how it allows accurate decoding of novel stimuli from novel spiking patterns.

DOI:http://dx.doi.org/10.7554/eLife.06134.001

Our ability to perceive the world is dependent on information from our senses being passed between different parts of the brain. The information is encoded as patterns of electrical pulses or ‘spikes’, which other brain regions must be able to decipher. Cracking this code would thus enable us to predict the patterns of nerve impulses that would occur in response to specific stimuli, and ‘decode’ which stimuli had produced particular patterns of impulses.

This task is challenging in part because of its scale—vast numbers of stimuli are encoded by huge numbers of neurons that can send their spikes in many different combinations. Furthermore, neurons are inherently noisy and their response to identical stimuli may vary considerably in the number of spikes and their timing. This means that the brain cannot simply link a single unchanging pattern of firing with each stimulus, because these firing patterns are often distorted by biophysical noise.

Ganmor et al. have now modeled the effects of noise in a network of neurons in the retina (found at the back of the eye), and, in doing so, have provided insights into how the brain solves this problem. This has brought us a step closer to cracking the neural code. First, 10 second video clips of natural scenes and artificial stimuli were played on a loop to a sample of retina taken from a salamander, and the responses of nearly 100 neurons in the sample were recorded for two hours. Dividing the 10 second clip into short segments provided a series of 500 stimuli, which the network had been exposed to more than 600 times.

Ganmor et al. analyzed the responses of groups of 20 cells to each stimulus and found that physically similar firing patterns were not particularly likely to encode the same stimulus. This can be likened to the way that words such as ‘light’ and ‘night’ have similar structures but different meanings. Instead, the model reveals that each stimulus was represented by a cluster of firing patterns that bore little physical resemblance to one another, but which nevertheless conveyed the same meaning. To continue on with the previous example, this is similar to way that ‘light’ and ‘illumination’ have the same meaning but different structures.

Ganmor et al. use these new data to map the organization of the ‘vocabulary’ of populations of cells the retina, and put together a kind of ‘thesaurus’ that enables new activity patterns of the retina to be decoded and could be used to crack the neural code. Furthermore, the organization of ‘synonyms’ is strikingly similar to codes that are favored in many forms of telecommunication. In these man-made codes, codewords that represent different items are chosen to be so distinct from each other that even if they were corrupted by noise, they could be correctly deciphered. Correspondingly, in the retina, patterns that carry the same meaning occupy a distinct area, and new patterns can be interpreted based on their proximity to these clusters.

DOI:http://dx.doi.org/10.7554/eLife.06134.002

Analysis of Metrics for Molecular Sonotransfer in Vitro

Ultrasound induced microbubble (MB) cavitation is used to significantly enhance cell membrane permeabilization, thereby allowing delivery of various therapeutic agents into cells. In order to monitor and quantitatively control the extent of cavitation the uniform dosimetry model is needed. In present study we have simultaneously performed quantitative evaluation of three main sonoporation factors: (1) MB concentration, (2) MB cavitation extent, and (3) doxorubicin (DOX) sonotransfer into Chinese hamster ovary cells. MB concentration measurement results and passively recorded MB cavitation signals were used for MB sonodestruction rate and spectral root-mean-square (RMS) calculations, respectively. Subsequently, time to maximum value of RMS and inertial cavitation dose (ICD) quantifications were performed for every acoustic pressure value. This comprehensive research has led not only to explanation of relation of ICD and MB sonodestruction rate but also to the development of a new sonoporation metric: the inverse of time to maximum value of RMS (1/time to maximum value of RMS). ICD and MB sonodestruction rate intercorrelation and correlation with DOX sonotransfer suggest inertial cavitation to be the key mechanism for cell sonoporation. All these metrics were successfully used for doxorubicin sonotransfer prediction (R(2) > 0.9, p < 0.01) and therefore shows feasibility to be applied for future dosimetric applications for ultrasound-mediated drug and gene delivery.

App Usage Factor: A Simple Metric to Compare the Population Impact of Mobile Medical Apps

Background

One factor when assessing the quality of mobile apps is quantifying the impact of a given app on a population. There is currently no metric which can be used to compare the population impact of a mobile app across different health care disciplines.

Objective

The objective of this study is to create a novel metric to characterize the impact of a mobile app on a population.

Methods

We developed the simple novel metric, app usage factor (AUF), defined as the logarithm of the product of the number of active users of a mobile app with the median number of daily uses of the app. The behavior of this metric was modeled using simulated modeling in Python, a general-purpose programming language. Three simulations were conducted to explore the temporal and numerical stability of our metric and a simulated app ecosystem model using a simulated dataset of 20,000 apps.

Results

Simulations confirmed the metric was stable between predicted usage limits and remained stable at extremes of these limits. Analysis of a simulated dataset of 20,000 apps calculated an average value for the app usage factor of 4.90 (SD 0.78). A temporal simulation showed that the metric remained stable over time and suitable limits for its use were identified.

Conclusions

A key component when assessing app risk and potential harm is understanding the potential population impact of each mobile app. Our metric has many potential uses for a wide range of stakeholders in the app ecosystem, including users, regulators, developers, and health care professionals. Furthermore, this metric forms part of the overall estimate of risk and potential for harm or benefit posed by a mobile medical app. We identify the merits and limitations of this metric, as well as potential avenues for future validation and research.

Q-Score: development of a new metric for continuous glucose monitoring that enables stratification of antihyperglycaemic therapies

BACKGROUND

Continuous glucose monitoring (CGM) has revolutionised diabetes management. CGM enables complete visualisation of the glucose profile, and the uncovering of metabolic 'weak points'. A standardised procedure to evaluate the complex data acquired by CGM, and to create patient-tailored recommendations has not yet been developed. We aimed to develop a new patient-tailored approach for the routine clinical evaluation of CGM profiles. We developed a metric allowing screening for profiles that require therapeutic action and a method to identify the individual CGM parameters with improvement potential.

METHODS

Fifteen parameters frequently used to assess CGM profiles were calculated for 1,562 historic CGM profiles from subjects with type 1 or type 2 diabetes. Factor analysis and varimax rotation was performed to identify factors that accounted for the quality of the profiles.

RESULTS

We identified five primary factors that determined CGM profiles (central tendency, hyperglycaemia, hypoglycaemia, intra- and inter-daily variations). One parameter from each factor was selected for constructing the formula for the screening metric, (the 'Q-Score'). To derive Q-Score classifications, three diabetes specialists independently categorised 766 CGM profiles into groups of 'very good', 'good', 'satisfactory', 'fair', and 'poor' metabolic control. The Q-Score was then calculated for all profiles, and limits were defined based on the categorised groups (<4.0, very good; 4.0-5.9, good; 6.0-8.4, satisfactory; 8.5-11.9, fair; and ≥12.0, poor). Q-Scores increased significantly (P <0.01) with increasing antihyperglycaemic therapy complexity. Accordingly, the percentage of fair and poor profiles was higher in insulin-treated compared with diet-treated subjects (58.4% vs. 9.3%). In total, 90% of profiles categorised as fair or poor had at least three parameters that could potentially be optimised. The improvement potential of those parameters can be categorised as 'low', 'moderate' and 'high'.

CONCLUSIONS

The Q-Score is a new metric suitable to screen for CGM profiles that require therapeutic action. Moreover, because single components of the Q-Score formula respond to individual weak points in glycaemic control, parameters with improvement potential can be identified and used as targets for optimising patient-tailored therapies.

HIV self-testing among key populations: an implementation science approach to evaluating self-testing

OBJECTIVES

To review methods for measuring HIV self-testing (HIVST) among key populations, including both conventional approaches and implementation science approaches.

METHODS

We reviewed the literature on evaluating HIVST among key populations.

RESULTS

Simple HIV self-tests have already entered markets in several regions, but metrics required to demonstrate the benefits and costs of HIVST remain simplistic. Conventional measurements of sensitivity, specificity, acceptability, and behavioural preferences must be supplemented with richer implementation science measurement tools and innovative research designs in order to capture data on the following components: how self-testing affects subsequent linkage to confirmatory testing, preventive services and onward steps in the HIV continuum of care; how self-testing can be marketed to reach untested subpopulations; and how self-testing can be sustained based on overarching organisational and financial models. We outline an implementation science research agenda that incorporates these components, drawing from evaluation study designs focused on HIVST and testing in general.

CONCLUSION

HIVST holds great promise for key populations, but must be guided by implementation research to inform programmes and scale up.

Continuous glucose monitoring and trend accuracy: news about a trend compass

Continuous glucose monitoring (CGM) devices are being increasingly used to monitor glycemia in people with diabetes. One advantage with CGM is the ability to monitor the trend of sensor glucose (SG) over time. However, there are few metrics available for assessing the trend accuracy of CGM devices. The aim of this study was to develop an easy to interpret tool for assessing trend accuracy of CGM data. SG data from CGM were compared to hourly blood glucose (BG) measurements and trend accuracy was quantified using the dot product. Trend accuracy results are displayed on the Trend Compass, which depicts trend accuracy as a function of BG. A trend performance table and Trend Index (TI) metric are also proposed. The Trend Compass was tested using simulated CGM data with varying levels of error and variability, as well as real clinical CGM data. The results show that the Trend Compass is an effective tool for differentiating good trend accuracy from poor trend accuracy, independent of glycemic variability. Furthermore, the real clinical data show that the Trend Compass assesses trend accuracy independent of point bias error. Finally, the importance of assessing trend accuracy as a function of BG level is highlighted in a case example of low and falling BG data, with corresponding rising SG data. This study developed a simple to use tool for quantifying trend accuracy. The resulting trend accuracy is easily interpreted on the Trend Compass plot, and if required, performance table and TI metric.

Measuring the evidence: reviewing the literature of the measurement of therapeutic engagement in acute mental health inpatient wards

Quality nursing plays a central role in the delivery of contemporary health and social care, with a positive correlation being demonstrated between patient satisfaction and the quality of nursing care received. One way to ensure such quality is to develop metrics that measure the effectiveness of various aspects of care across a variety of settings. Effective mental health nursing is predicated on understanding the lived experiences of service users in order to provide sensitively-attuned nursing care. To achieve this, mental health nurses need to establish the all-important therapeutic relationship, showing compassion and creating a dialogue whereby service users feel comfortable to share their experiences that help contextualize their distress. Indeed, service users value positive attitudes, being listened to, and being able to trust those who provide care, while mental health nurses value their ability to relate through talking, listening, and expressing empathy. However, the literature suggests that within mental health practice, a disproportionate amount of time is taken up by other activities, with little time being spent listening and talking to service users. The present study discusses the evidence relating to the therapeutic relationship in acute mental health wards and explores why, after five decades, it is not recognized as a fundamental metric of mental health nursing.

Tree-average distances on certain phylogenetic networks have their weights uniquely determined

A phylogenetic network N has vertices corresponding to species and arcs corresponding to direct genetic inheritance from the species at the tail to the species at the head. Measurements of DNA are often made on species in the leaf set, and one seeks to infer properties of the network, possibly including the graph itself. In the case of phylogenetic trees, distances between extant species are frequently used to infer the phylogenetic trees by methods such as neighbor-joining. This paper proposes a tree-average distance for networks more general than trees. The notion requires a weight on each arc measuring the genetic change along the arc. For each displayed tree the distance between two leaves is the sum of the weights along the path joining them. At a hybrid vertex, each character is inherited from one of its parents. We will assume that for each hybrid there is a probability that the inheritance of a character is from a specified parent. Assume that the inheritance events at different hybrids are independent. Then for each displayed tree there will be a probability that the inheritance of a given character follows the tree; this probability may be interpreted as the probability of the tree. The tree-average distance between the leaves is defined to be the expected value of their distance in the displayed trees. For a class of rooted networks that includes rooted trees, it is shown that the weights and the probabilities at each hybrid vertex can be calculated given the network and the tree-average distances between the leaves. Hence these weights and probabilities are uniquely determined. The hypotheses on the networks include that hybrid vertices have indegree exactly 2 and that vertices that are not leaves have a tree-child.