Flowchart for predicting achieving the target area under the concentration-time curve of vancomycin in critically ill Japanese patients: A multicenter retrospective study

INTRODUCTION

In therapeutic drug monitoring (TDM) of vancomycin (VCM), the area under the concentration-time curve (AUC) is related to the clinical efficacy and toxicity. Therefore, herein, we examined the factors associated with achieving the target AUC at follow-up and developed a decision flowchart for achieving the target AUC in critically ill patients.

METHODS

This multicenter retrospective observational study was conducted at eight hospitals. We retrospectively analyzed data from patients who had received VCM in the intensive care unit from January 2020 to December 2022. Decision-tree (DT) analysis was performed using factors with p < 0.1 in univariate analysis as the independent variables. Case data were split up to two times, and four subgroups were included. The primary endpoint was achieving the target AUC at the follow-up TDM (AUCfollow-up) and target AUCfollow-up achievement was defined as an AUC of 400-600 μg‧h/mL. The initial AUC values were calculated with the 2-point concentrations (peak and trough) using the Bayesian estimation software Practical AUC-guided TDM (PAT).

RESULTS

Among 70 patients (median age [interquartile range], 66 [56, 79] years; 50 % women), the AUCfollow-up was achieved in 70 % (49/70). Three factors were selected for the decision flow chart: predicted AUCfollow-up of 400-600 μg‧h/mL, dosing at 12-h intervals, and CCr of 130 mL/min/1.73 m2 or higher; the accuracy was adequate (92 %, R2 0.52).

CONCLUSION

We successfully identified the factors associated with achieving the target AUC of VCM at follow-up TDM and developed a simple-to-use DT model. However, the validity of the findings needs to be evaluated.

[Implementation and Effectiveness of Measures to Prevent Recurrence of Incidents Developed through Root Cause Analysis Using Work Flowchart]

PURPOSE

Incidents are recommended to be analyzed by root cause analysis (RCA). Our institution also conducts RCA for incidents and takes measures to prevent recurrence. The purpose of this study was to evaluate the effectiveness of countermeasures against the root causes analyzed by RCA in order to prevent recurrence of incidents.

METHODS

Since the treatment planning CT scanner was replaced, incidents of failure to zero adjustment the coordinates of the bed position occurred four times during a three-month period. The RCA was used to investigate the root causes of these incidents and to formulate measures to prevent recurrence. To evaluate the effectiveness of the recurrence prevention measures, we collected the number of recurrence of incidents during the first year after the effectiveness of the recurrence prevention measures, and used the chi-square test to determine the significant difference in the probability of an incident occurring at a significance level of 5% or less.

RESULTS

The measures to prevent the recurrence of incidents were to double-check that the coordinates of the bed position were adjusted to zero and to simulate operations based on a work flow that incorporated this double-check. During the first year period following the implementation of these recurrence prevention measures, the number of recurrence incidents was zero, and the probability of their occurrence decreased statistically significantly (p<0.05).

CONCLUSION

Thorough double-checks and work simulation based on the work flow are effective methods for preventing the recurrence of incidents.

Focal electroclinical features in generalized tonic-clonic seizures: Decision flowchart for a diagnostic challenge

OBJECTIVE

Bilateral tonic-clonic seizures with focal semiology or focal interictal electroencephalography (EEG) can occur in both focal and generalized epilepsy types, leading to diagnostic errors and inappropriate therapy. We investigated the prevalence and prognostic values of focal features in patients with idiopathic generalized epilepsy (IGE), and we propose a decision flowchart to distinguish between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal EEG or semiology.

METHODS

We retrospectively analyzed video-EEG recordings of 101 bilateral tonic-clonic seizures from 60 patients (18 with IGE, 42 with focal epilepsy). Diagnosis and therapeutic response were extracted after ≥1-year follow-up. The decision flowchart was based on previous observations and assessed concordance between interictal and ictal EEG.

RESULTS

Focal semiology in IGE was observed in 75% of seizures and 77.8% of patients, most often corresponding to forced head version (66.7%). In patients with multiple seizures, direction of head version was consistent across seizures. Focal interictal epileptiform discharges (IEDs) were observed in 61.1% of patients with IGE, whereas focal ictal EEG onset only occurred in 13% of seizures and 16.7% of patients. However, later during the seizures, a reproducible pattern of 7-Hz lateralized ictal rhythm was observed in 56% of seizures, associated with contralateral head version. We did not find correlation between presence of focal features and therapeutic response in IGE patients. Our decision flowchart distinguished between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal features with an accuracy of 96.6%.

SIGNIFICANCE

Focal semiology associated with bilateral tonic-clonic seizures and focal IEDs are common features in patients with IGE, but focal ictal EEG onset is rare. None of these focal findings appears to influence therapeutic response. By assessing the concordance between interictal and ictal EEG findings, one can accurately distinguish between focal and generalized epilepsies.

A flowchart for adequate controls in virus-based monosynaptic tracing experiments identified Cre-independent leakage of the TVA receptor in RΦGT mice

BACKGROUND

A pseudotyped modified rabies virus lacking the rabies glycoprotein (G-protein), which is crucial for transsynaptic spread, can be used for monosynaptic retrograde tracing. By coupling the pseudotyped virus with transgene expression of the G-protein and the avian leukosis and sarcoma virus subgroup A receptor (TVA), which is necessary for cell entry of the virus, researchers can investigate specific neuronal populations. Responder mouse lines, like the RΦGT mouse line, carry the genes encoding the G-protein and TVA under Cre-dependent expression. These mouse lines are valuable tools because they reduce the number of viral injections needed compared to when using helper viruses. Since RΦGT mice do not express Cre themselves, introducing the pseudotyped rabies virus into their brain should not result in viral cell entry or spread.

RESULTS

We present a straightforward flowchart for adequate controls in tracing experiments, which we employed to demonstrate Cre-independent expression of TVA in RΦGT mice.

CONCLUSIONS

Our observations revealed TVA leakage, indicating that RΦGT mice should be used with caution for transgene expression of TVA. Inaccurate tracing outcomes may occur if TVA is expressed in the absence of Cre since background leakage leads to nonspecific cell entry. Moreover, conducting appropriate control experiments can identify the source of potential caveats in virus-based neuronal tracing experiments.

Effectiveness and Utility of Flowcharts on Learning in a Classroom Setting: A Mixed-Methods Study

OBJECTIVE

Graphical representation of information organizes and promotes meaningful learning. As an example of graphical organizers, flowcharts can simplify and summarize complex information. The evidence of classroom use of flowcharts as an instructional tool is unclear. We investigated the effectiveness of flowcharts on student learning as an in-class instructional tool in a cardiovascular therapeutic course. Student experiences with the use and application of flowcharts were explored.

METHODS

An explanatory sequential mixed-methods study was conducted with pharmacy students enrolled in an acute-care cardiovascular course from 2019-2021. The quantitative phase comprised a survey to determine flowchart effectiveness and a comparison of student performance in three content areas. The qualitative phase of the study used focused group interviews to understand student perceptions of flowchart use.

RESULTS

Survey results indicated that using flowcharts improved understanding (110/128, 86%), integration of material (114/128, 89%), and overall knowledge (111/128, 87%). Student performance in the 3 content areas, shock, arrhythmia, and acute coronary syndrome were statistically significant with flowcharts implementation. Emerging themes from student interviews were (1) used as a medium for retention and recall, (2) used as a study tool, and (3) used as a decision-making framework.

CONCLUSION

Flowcharts provide an alternative approach to teaching complex content, which allows students to organize and summarize information that promotes meaningful learning. The ease of implementation combined with the generalized nature of flowcharts makes it an effective graphical organizer that can be used across various disciplines.

Designing the Continuous Glucose Monitor Experience: An App Design Process Overview

Users of continuous glucose monitors (CGMs) experience the product in part through software. Smartphone and watch apps empower people affected by diabetes to make real-time treatment decisions based on glucose readings and aggregate data such as medication, nutrition, and activity information. As CGMs evolve and gain greater market adoption, there's opportunity for these apps to play a greater role in users' lives and diabetes management. To do so, designers should follow the best practices established by the broader technology community and apply them to the needs of this community. The process of thorough discovery research, clear problem definition, iterative design, and testing can lower barriers toward broader adoption, and favorably influence the health of users through their mobile apps.

Diagnostic flowchart for tuberculous pleurisy, pleural infection, and malignant pleural effusion

BACKGROUND

Several markers for the diagnosis of pleural effusion have been reported; however, a comprehensive evaluation using those markers has not been performed. Therefore, this study aimed to develop a diagnostic flowchart for tuberculous pleurisy, pleural infection, malignant pleural effusion, and other diseases by using these markers.

METHODS

We retrospectively collected data from 174 patients with tuberculous pleurisy, 215 patients with pleural infection other than tuberculous pleurisy, 360 patients with malignant pleural effusion, and 209 patients with other diseases at Fukujuji Hospital from January 2012 to October 2022. The diagnostic flowchart for four diseases was developed by using several previously reported markers.

RESULTS

The flowchart was developed by including seven markers: pleural ADA ≥40 IU/L, pleural fluid LDH <825 IU/L, pleural fluid ADA/TP < 14, neutrophil predominance or cell degeneration, peripheral blood WBC ≥9200/μL or serum CRP ≥12 mg/dL, pleural amylase ≥75 U/L, and the presence of pneumothorax according to the algorithm of a decision tree. The accuracy ratio of the flowchart was 71.7 % for the diagnosis of the four diseases, with 79.3 % sensitivity and 75.4 % positive predictive value (PPV) for tuberculosis pleurisy, 75.8 % sensitivity and 83.2 % PPV for pleural infection, 88.6 % sensitivity and 68.8 % PPV for malignant pleural effusion, and 33.0 % sensitivity and 60.0 % PPV for other diseases in the flowchart. The misdiagnosis ratios were 4.6 % for tuberculosis pleurisy, 6.8 % for pleural infection, and 8.3 % for malignant pleural effusion.

CONCLUSION

This study developed a useful diagnostic flowchart for tuberculous pleurisy, pleural infection, malignant pleural effusion, and other diseases.

Designing Combinations of Pictogram and Text Size for Icons: Effects of Text Size, Pictogram Size, and Familiarity on Older Adults' Visual Search Performance

OBJECTIVE

This study aimed to determine suitable combinations of text and pictogram sizes for older adults and investigated the visual prioritization of pictogram versus text.

BACKGROUND

Icons have become an indispensable part of application (app) design. Pictogram size and text size of icons influence the usability of apps, especially by aged users. However, few studies have investigated the influences of different pictogram and text size combinations on readability, legibility, and visual search performance for older adults.

METHOD

This study used eye-tracking technology to investigate the effects of different pictogram and text size combinations as well as familiarity on readability, legibility, and visual search performance for older adults. A 3 (pictogram size) × 3 (text size) × 2 (familiarity) repeated-measures experimental design was used.

RESULTS

The results of this study suggest that pictogram size and text size significantly affect visual search performance and that familiarity moderates the effect of text size on distribution of fixation duration proportion for text and pictograms.

CONCLUSION

Large pictogram and text sizes improved the readability and legibility of icons for older adults. Furthermore, the older adults fixated the area of text prior to pictograms when the pictogram size was larger than 72 × 72 px (1.38° × 1.38°) in the visual search task.

APPLICATION

The results of this study suggest using different combinations of pictogram and text sizes for older adults under different scenarios. The findings of this study act as practical support for designers and developers of mobile apps for older adults.

Developing a flowchart to evaluate the use of Closed System Drug-Transfer Devices with monoclonal antibodies: Focus on the clinical trial setting

OBJECTIVE

Available guidelines are ambiguous about safe handling monoclonal antibodies (MABs) and whether or not to use a Closed System Drug-Transfer Device (CSTD). In this article we want to describe a standardized working method on handling MABs in a clinical trial setting.

DATA SOURCES

The current workflow at the clinical trial unit of the Ghent University Hospital was critically analyzed, after which an extensive literature review was performed using the National Institute for Occupational Safety and Health Working Group guidelines and the database PubMed (Keywords: monoclonal antibodies, closed system transfer devices, safety guidelines, safe handling, management, administration, (bio)compatibility, volume loss, contamination, clinical trial unit. Period: 2020-2022).

DATA SUMMARY

Literature data are ambiguous. CSTDs can reduce cross-contamination and minimize exposure to potential hazardous drugs for healthcare professionals. However, in recent years more questions have been raised about their in-use compatibility and their impact on final product quality. This makes the debate on implementing CSTDs a hot topic in daily pharmacy practice and demands a holistic and standardized approach when deciding whether or not to use a CSTD when handling MABs. In a clinical trial setting, where safety data are frequently not available and the compatibility of CSTDs and investigational product is often unknown, this poses additional challenges that need to be taken into account.

CONCLUSION

We developed a flowchart which standardizes the use of a CSTD when handling MABs. It allows other healthcare professionals and clinical trial sponsors to define and evaluate the necessary criteria when standardizing the position of a CSTD in their safe handling procedures.

Development and diagnostic accuracy of dyslexia early identification flowchart for pediatric practice

This study developed and evaluated the Rapid Automatized naming, Phonological Awareness, and Letter Identification (RAPALI) flowchart for early dyslexia identification in pediatric settings. Using early literacy skills at kindergarten level from the Thai emergent literacy for predicting dyslexia longitudinal study, the RAPALI flowchart effectively identified dyslexia risk at grade 3 level, boasting an AUC of 0.71, a sensitivity of 95.5%, and a negative predictive value of 99.1%. RAPALI demonstrated acceptable specificity and positive predictive value. The user-friendly flowchart aids early identification, interventions, and preventive measures for dyslexia, benefiting affected children and their families. However, further validation and adaptation are needed.

Suggested Flowchart Through Integrated C-Reactive Protein and White Blood Cell Count Analysis for Screening for Early Complications After Gastric Bypass: a Single-Center Retrospective Study

INTRODUCTION

Early leakage detection following bariatric procedures is crucial, but a standardized evaluation method is lacking. The aim was to validate the potential benefits of postoperative day 1 (POD1) C-reactive protein (CRP) levels and white blood cell (WBC) counts in distinguishing at-risk patients following Roux-en-Y gastric bypass (RYGB) while considering the impact of obesity-related chronic inflammation.

METHODS

Retrospective analysis of 261 consecutive patients aged 18-65 years with a body mass index (BMI) of 32.5-50 kg/m2 who underwent primary RYGB between 2017 and 2022. Sequential changes in CRP levels and WBC counts measured 48 h preoperatively and on POD1 morning were collected and compared between patients with/without complications and in patients without complications stratified by preoperative CRP levels.

RESULTS

Female patients and those with a higher BMI tended to have higher baseline CRP levels, which were positively related to postoperative CRP. Patients experiencing complications had higher WBC counts and a higher prevalence of WBC counts >14,000/μl (77.8% vs. 25.4%; p<0.001) than those without complications. Baseline CRP ≥ 0.3 mg/dl, a longer operative time, and blood loss >10 ml were significantly more common with WBC counts above 14,000/μl; a reasonable range of change in WBC count (∆WBC) derived from its positive correlation to postoperative WBC count (r=0.6695) may serve as a useful complementary indicator.

CONCLUSION

An individualized CRP threshold setting and integrated interpretation of the WBC count can be more appropriate than using static criteria for differentiating at-risk patients after RYGB. Further studies are needed to validate these findings and determine their generalizability.

[Model construction and software design of computed tomography radiation system based on visualization]

The Monte Carlo N-Particle (MCNP) is often used to calculate the radiation dose during computed tomography (CT) scans. However, the physical calculation process of the model is complicated, the input file structure of the program is complex, and the three-dimensional (3D) display of the geometric model is not supported, so that the researchers cannot establish an accurate CT radiation system model, which affects the accuracy of the dose calculation results. Aiming at these two problems, this study designed a software that visualized CT modeling and automatically generated input files. In terms of model calculation, the theoretical basis was based on the integration of CT modeling improvement schemes of major researchers. For 3D model visualization, LabVIEW was used as the new development platform, constructive solid geometry (CSG) was used as the algorithm principle, and the introduction of editing of MCNP input files was used to visualize CT geometry modeling. Compared with a CT model established by a recent study, the root mean square error between the results simulated by this visual CT modeling software and the actual measurement was smaller. In conclusion, the proposed CT visualization modeling software can not only help researchers to obtain an accurate CT radiation system model, but also provide a new research idea for the geometric modeling visualization method of MCNP.

Design Guidelines of Mobile Apps for Older Adults: Systematic Review and Thematic Analysis

BACKGROUND

Mobile apps are fundamental tools in today's society for practical and social endeavors. However, these technologies are often not usable for older users. Given the increased use of mobile apps by this group of users and the impact that certain services may have on their quality of life, such as mobile health, personal finance, or online administrative procedures, a clear set of guidelines for mobile app designers is needed. Existing recommendations for older adults focus on investigations with certain groups of older adults or have not been extracted from experimental results.

OBJECTIVE

In this research work, we systematically reviewed the scientific literature that provided recommendations for the design of mobile apps based on usability testing with older adults and organized such recommendations into a meaningful set of design guidelines.

METHODS

We conducted a systematic literature review of journal and conference articles from 2010 to 2021. We included articles that carried out usability tests with populations aged >60 years and presented transferable guidelines on mobile software design, resulting in a final set of 40 articles. We then carried out a thematic analysis with 3 rounds of analysis to provide meaning to an otherwise diverse set of recommendations. At this stage, we discarded recommendations that were made by just 1 article, were based on a specific mobile app and were therefore nontransferrable, were based on other authors' literature (as opposed to recommendations based on the results of usability tests), or were not sufficiently argued. With the remaining recommendations, we identified commonalities, wrote a faithful statement for each guideline, used a common language for the entire set, and organized the guidelines into categories, thereby giving shape to an otherwise diverse set of recommendations.

RESULTS

Among the 27 resulting guidelines, the rules Simplify and Increase the size and distance between interactive controls were transversal and of the greatest significance. The rest of the guidelines were divided into 5 categories (Help & Training, Navigation, Visual Design, Cognitive Load, and Interaction) and consequent subcategories in Visual Design (Layout, Icons, and Appearance) and Interaction (Input and Output). The recommendations were structured, explained in detail, and illustrated with applied examples extracted from the selected studies, where appropriate. We discussed the design implications of applying these guidelines, contextualized with relevant studies. We also discussed the limitations of the approach followed, stressing the need for further experimentation to gain a better understanding of how older adults use mobile apps and how to better design such apps with these users in mind.

CONCLUSIONS

The compiled guidelines support the design of mobile apps that cater to the needs of older adults because they are based on the results of actual usability tests with users aged >60 years.

Flowchart for selecting an appropriate surgical airway in neurologically impaired pediatric intubated patients: a case series

OBJECTIVE

Medical advances have resulted in increased survival rates of neurologically impaired children who may require mechanical ventilation and subsequent tracheostomy as a surgical airway. However, at present, there is no definite consensus regarding the timing and methods for placement of a surgical airway in a neurologically impaired intubated child who needs to be cared for over a long-term period. We therefore created a flowchart for the selection of a surgical airway for Neurologically Impaired Pediatric Patients (NIPPs).

METHODS

The flowchart includes information on the patients' backgrounds, such as intubation period, prognosis related to reversibility, and history of aspiration pneumonia. To evaluate the importance of the flowchart, first we conducted a survey of pediatricians regarding selection of a surgical airway, and we also evaluated the appropriateness of the flowchart among pediatricians and caregivers through questionnaire surveys which include satisfaction with the decision-making process, and postoperative course after discharge.

RESULTS

A total of 21 NIPPs with intubation underwent surgery and a total of 24 participants (14 pediatricians and 10 caregivers) completed the survey. The answers regarding the importance of the flowchart showed that eleven pediatricians had experience selecting of surgical airways, nine of whom had had experiences in which they had to make a difficult decision. The answers regarding the appropriateness of the flowchart revealed that all pediatricians and caregivers were satisfied with the decision-making process and postoperative course after discharge using the flowchart.

CONCLUSIONS

The present study demonstrated the effectiveness of our flowchart for selecting an appropriate surgical airway in NIPP. By referring to our flowchart, pediatricians and caregivers are likely to be able to select an appropriate surgical airway, leading to increased satisfaction with the decision-making process and postoperative course.

LEVEL OF EVIDENCE: 4

Inclusion4EU: Co-Designing a Framework for Inclusive Software Design and Development

Digital technology is now pervasive, however, not all groups have uniformly benefitted from technological changes and some groups have been left behind or digitally excluded. Comprehensive data from the 2017 Current Population Survey shows that older people and persons with disabilities still lag behind in computer and internet access. Furthermore unique ethical, privacy and safety implications exist for the use of technology for older persons and people with disabilities and careful reflection is required to incorporate these aspects, which are not always part of a traditional software lifecycle. In this paper we present the Inclusion4EU project that aims to co-design a new framework, guidelines and checklists for inclusive software design and development with end-users from excluded categories, academics with expertise in human-computer interaction and industry practitioners from software engineering.

Radiotherapy Infrastructure Shielding Calculations: software development for shielding calculations in a linear accelerator radiotherapy room

This work aimed to develop and validate software that calculates the shielding thickness required for a radiotherapy room with a linear accelerator utilising geometric and dosimetric data. The software "Radiotherapy Infrastructure Shielding Calculations" (RISC) was developed using MATLAB programming. It does not require the installation of the MATLAB platform, and the user only needs to download and install the application, which displays a graphical user interface (GUI). The GUI includes empty cells to insert numerical values for several parameters to calculate the proper shielding thickness. The GUI comprises two main interfaces, one for the primary and one for the secondary barrier calculation. The interface of the primary barrier is divided into four tabs: (a) primary radiation, (b) patient scattered and leakage radiation, (c) IMRT techniques and (d) the shielding cost calculations. The interface of the secondary barrier includes three tabs: (a) patient scattered and leakage radiation, (b) IMRT techniques and (c) the shielding cost calculations. Each tab consists of two sections: one for input and one for output of the necessary data. The RISC is based on the methods and formulae of the NCRP 151 and calculates the primary and secondary barrier thickness for ordinary concrete with a density of 2.35 g/cm3 and the cost for a radiotherapy room with a linear accelerator that performs conventional or IMRT techniques. Calculations can be performed for photon energies of 4, 6, 10, 15, 18, 20, 25 and 30 MV of a dual-energy linear accelerator, while instantaneous dose rate (IDR) calculations are also performed. The RISC has been validated using all comparative examples of NCRP 151 and the calculations from shielding reports of the Varian IX linear accelerator at Methodist Hospital of Willowbrook and Elekta Infinity at the University Hospital of Patras. The RISC is accompanied by two text files: (a) "Terminology," extensively describing all parameters, and (b) "User's Manual," providing useful instructions to the user. The RISC is user-friendly, simple, fast and precise, providing accurate shielding calculations and quickly and easily reproducing different shielding scenarios for a radiotherapy room with a linear accelerator. Additionally, it could be used during the educational process of shielding calculations by graduate students or trainee medical physicists. As a future work, the RISC will be updated with new features such as skyshine radiation, door shielding, and other types of machines and shielding materials.

Unusual causes of hyperthyrotropinemia and differential diagnosis of primary hypothyroidism: a revised diagnostic flowchart

The clinical consequences of primary hypothyroidism include cardiovascular morbidity, increased mortality, and poor quality of life; therefore guidelines endorsed by several Scientific Societies recommend measuring circulating thyroid-stimulating hormone (TSH) in patients at risk. The assessment of serum TSH levels is also deemed to be the most robust and accurate biomarker during the management of replacement therapy in patients with a previous diagnosis of primary hypothyroidism. In line with a reflex TSH laboratory strategy, free thyroxine is measured only if the TSH falls outside specific cutoffs, in order to streamline investigations and save unjustified costs. This serum TSH-based approach to both diagnosis and monitoring has been widely accepted by several national and local health services; nevertheless, false-negative or -positive testing may occur, leading to inappropriate management or treatment. This review aims to describe several infrequent causes of increased circulating TSH, including analytical interferences, resistance to TSH, consumptive hypothyroidism, and refractoriness to levothyroxine replacement treatment. We propose a clinical flowchart to aid correct recognition of these various conditions, which represent important potential pitfalls in the diagnosis and treatment of primary hypothyroidism.

The Smart Drifter Cluster: Monitoring Sea Currents and Marine Litter Transport Using Consumer IoT Technologies

The study of marine Lagrangian transport holds significant importance from a scientific perspective as well as for practical applications such as environmental-pollution responses and prevention (e.g., oil spills, dispersion/accumulation of plastic debris, etc.). In this regard, this concept paper introduces the Smart Drifter Cluster: an innovative approach that leverages modern "consumer" IoT technologies and notions. This approach enables the remote acquisition of information on Lagrangian transport and important ocean variables, similar to standard drifters. However, it offers potential benefits such as reduced hardware costs, minimal maintenance expenses, and significantly lower power consumption compared to systems relying on independent drifters with satellite communication. By combining low power consumption with an optimized, compact integrated marine photovoltaic system, the drifters achieve unlimited operational autonomy. With the introduction of these new characteristics, the Smart Drifter Cluster goes beyond its primary function of mesoscale monitoring of marine currents. It becomes readily applicable to numerous civil applications, including recovering individuals and materials at sea, addressing pollutant spills, and tracking the dispersion of marine litter. An additional advantage of this remote monitoring and sensing system is its open-source hardware and software architecture. This fosters a citizen-science approach, enabling citizens to replicate, utilize, and contribute to the improvement of the system. Thus, within certain constraints of procedures and protocols, citizens can actively contribute to the generation of valuable data in this critical field.

A Data Transformation Methodology to Create Findable, Accessible, Interoperable, and Reusable Health Data: Software Design, Development, and Evaluation Study

BACKGROUND

Sharing health data is challenging because of several technical, ethical, and regulatory issues. The Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles have been conceptualized to enable data interoperability. Many studies provide implementation guidelines, assessment metrics, and software to achieve FAIR-compliant data, especially for health data sets. Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) is a health data content modeling and exchange standard.

OBJECTIVE

Our goal was to devise a new methodology to extract, transform, and load existing health data sets into HL7 FHIR repositories in line with FAIR principles, develop a Data Curation Tool to implement the methodology, and evaluate it on health data sets from 2 different but complementary institutions. We aimed to increase the level of compliance with FAIR principles of existing health data sets through standardization and facilitate health data sharing by eliminating the associated technical barriers.

METHODS

Our approach automatically processes the capabilities of a given FHIR end point and directs the user while configuring mappings according to the rules enforced by FHIR profile definitions. Code system mappings can be configured for terminology translations through automatic use of FHIR resources. The validity of the created FHIR resources can be automatically checked, and the software does not allow invalid resources to be persisted. At each stage of our data transformation methodology, we used particular FHIR-based techniques so that the resulting data set could be evaluated as FAIR. We performed a data-centric evaluation of our methodology on health data sets from 2 different institutions.

RESULTS

Through an intuitive graphical user interface, users are prompted to configure the mappings into FHIR resource types with respect to the restrictions of selected profiles. Once the mappings are developed, our approach can syntactically and semantically transform existing health data sets into HL7 FHIR without loss of data utility according to our privacy-concerned criteria. In addition to the mapped resource types, behind the scenes, we create additional FHIR resources to satisfy several FAIR criteria. According to the data maturity indicators and evaluation methods of the FAIR Data Maturity Model, we achieved the maximum level (level 5) for being Findable, Accessible, and Interoperable and level 3 for being Reusable.

CONCLUSIONS

We developed and extensively evaluated our data transformation approach to unlock the value of existing health data residing in disparate data silos to make them available for sharing according to the FAIR principles. We showed that our method can successfully transform existing health data sets into HL7 FHIR without loss of data utility, and the result is FAIR in terms of the FAIR Data Maturity Model. We support institutional migration to HL7 FHIR, which not only leads to FAIR data sharing but also eases the integration with different research networks.

MCWS-Transformers: Towards an Efficient Modeling of Protein Sequences via Multi Context-Window Based Scaled Self-Attention

This paper advances the self-attention mechanism in the standard transformer network specific to the modeling of the protein sequences. We introduce a novel context-window based scaled self-attention mechanism for processing protein sequences that is based on the notion of (i) local context and (ii) large contextual pattern. Both notions are essential to building a good representation for protein sequences. The proposed context-window based scaled self-attention mechanism is further used to build the multi context-window based scaled (MCWS) transformer network for the protein function prediction task at the protein sub-sequence level. Overall, the proposed MCWS transformer network produced improved predictive performances, outperforming existing state-of-the-art approaches by substantial margins. With respect to the standard transformer network, the proposed network produced improvements in F1-score of +2.30% and +2.08% on the biological process (BP) and molecular function (MF) datasets, respectively. The corresponding improvements over the state-of-the-art ProtVecGen-Plus+ProtVecGen-Ensemble approach are +3.38% (BP) and +2.86% (MF). Equally important, robust performances were obtained across protein sequences of different lengths.

Design and Validation of a Low-Level Controller for Hierarchically Controlled Exoskeletons

In this work, a generalized low-level controller is presented for sensor collection, motor input, and networking with a high-level controller. In hierarchically controlled exoskeletal systems, which utilize series elastic actuators (SEAs), the hardware for sensor collection and motor command is separated from the computationally expensive high-level controller algorithm. The low-level controller is a hardware device that must collect sensor feedback, condition and filter the measurements, send actuator inputs, and network with the high-level controller at a real-time rate. This research outlines the hardware of two printed circuit board (PCB) designs for collecting and conditioning sensor feedback from two SEA subsystems and an inertial measurement unit (IMU). The SEAs have a joint and motor encoder, motor current, and force sensor feedback that can be measured using the proposed generalized low-level controller presented in this work. In addition, the high and low-level networking approach is discussed in detail, with a full breakdown of the data storage within a communication frame during the run-time operation. The challenges of device synchronization and updates rates of high and low-level controllers are also discussed. Further, the low-level controller was validated using a pendulum test bed, complete with full sensor feedback, including IMU results for two open-loop scenarios. Moreover, this work can be extended to other hierarchically controlled robotic systems that utilize SEA subsystems, such as humanoid robots, assistive rehabilitation robots, training simulators, and robotic-assisted surgical devices. The hardware and software designs presented in this work are available open source to enable researchers with a direct solution for data acquisition and the control of low-level devices in a robotic system.

Implementation of a method for a clinical biochemistry lesson plan based on the flowchart

Biochemistry is believed to be a difficult subject to understand for most life science and medical students. This article explains an experience with a flowchart-based teaching approach that is applicable to different kinds of biochemistry courses (basic, medical, and clinical) for undergraduate and postgraduate students. After preparing the flowcharts, they were given to the students at the beginning of the semester, and the flowchart-based teaching was performed for a whole semester. At the end of the semester, they were asked about the effectiveness and facilitation of learning using flowchart-based teaching. This survey was performed for several semesters. Approximately, 95% stated that it facilitates learning and understanding.

Visualization Design Practices in a Crisis: Behind the Scenes with COVID-19 Dashboard Creators

During the COVID-19 pandemic, a number of data visualizations were created to inform the public about the rapidly evolving crisis. Data dashboards, a form of information dissemination used during the pandemic, have facilitated this process by visualizing statistics regarding the number of COVID-19 cases over time. Prior work on COVID-19 visualizations has primarily focused on the design and evaluation of specific visualization systems from technology-centered perspectives. However, little is known about what occurs behind the scenes during the visualization creation processes, given the complex sociotechnical contexts in which they are embedded. Yet, such ecological knowledge is necessary to help characterize the nuances and trajectories of visualization design practices in the wild, as well as generate insights into how creators come to understand and approach visualization design on their own terms and for their own situated purposes. In this research, we conducted a qualitative interview study among dashboard creators from federal agencies, state health departments, mainstream news media outlets, and other organizations that created (often widely-used) COVID-19 dashboards to answer the following questions: how did visualization creators engage in COVID-19 dashboard design, and what tensions, conflicts, and challenges arose during this process? Our findings detail the trajectory of design practices-from creation to expansion, maintenance, and termination-that are shaped by the complex interplay between design goals, tools and technologies, labor, emerging crisis contexts, and public engagement. We particularly examined the tensions between designers and the general public involved in these processes. These conflicts, which often materialized due to a divergence between public demands and standing policies, centered around the type and amount of information to be visualized, how public perceptions shape and are shaped by visualization design, and the strategies utilized to deal with (potential) misinterpretations and misuse of visualizations. Our findings and lessons learned shed light on new ways of thinking in visualization design, focusing on the bundled activities that are invariably involved in human and nonhuman participation throughout the entire trajectory of design practice.

Accuracy of Dysphagia Standard Assessment (DSA®) bedside screening test: a flowchart for patient eligibility

Background

Oropharyngeal dysphagia (OD) screening tests have improved patient management; however, the complex applicability and high percentage of false negatives do not allow these tests to be considered completely reliable if not supported by an instrumental investigation. The aim of the present study is to evaluate an OD screening test, the Dysphagia Standard Assessment (DSA®) with different volumes and viscosities.

Materials and methods

Prospective study of 72 patients evaluated for suspected OD through a double-blind methodology conducted by two operators. All patients underwent fiberoptic endoscopic evaluation of swallowing (FEES) as a reference test and a separate DSA® test. DSA® was performed by administering boluses with different viscosities, with the signal of interruption of the test being: onset of the cough reflex, wet voice after swallowing, and/or desaturation of O2 ≥ 5%. The Penetration-Aspiration Scale (PAS) was evaluated by FEES. The cut-off identified to diagnose OD was PAS ≥ 3.

Results

The test showed an accuracy of 82%, a sensitivity of 0.93 (95% C.I. 0.84–0.97), and a specificity of 0.78 (95% C.I. 0.67–0.87); positive predictive value 0.55 (95% C.I. 0.43–0.67); negative predictive value 0.97 (95% C.I. 0.90–0.99), positive likelihood ratio 4.37 (95% C.I. 3.6–5.2); likelihood negative ratio 0.08 (95% C.I. 0.06–0.09).

Conclusions

According to the preliminary results, the test showed good outcomes in determining the presence or absence of OD with a wide spectrum of applicability with some limitations that could be overcome by the selection of a target population. For this reason, a flowchart to address patient eligibility was developed.

Towards a Generic Description Schema for Clinical Decision Support Systems

Many clinical decision support systems (CDSS) have shown good performance in the research context, but only a few have been brought into routine care. Analysis of success or failure factors in the design of CDSS may support translation from development to routine care by guiding CDSS design and development along these factors. In this work, we propose a schema to describe CDSS designs in a consistent way. We focus on design criteria with the aim to investigate the observed translation gap in CDSS. Existing description models on different aspects relevant for CDSS are combined to a comprehensive schema that allows description and comparison of CDSS without limitation to the domain or architecture.

Flowchart for Implementing Advanced Imaging and Electrophysiology in Patients With Disorders of Consciousness: To fMRI or Not to fMRI?

The American Academy of Neurology and the European Academy of Neurology have recognized, for the first time, the value of advanced neuroimaging and electrophysiology techniques (AIEs) in the context of diagnosing patients with a disorder of consciousness (DOC). This recognition is part of an important agenda of promoting evidence-based competency in the management of patients with DOC. Nonetheless, considering that these techniques (and the required knowledge) are seldom available outside of advanced medical centers, it is important to provide physicians with a framework for balancing risks and benefits and deciding, on a single patient basis, whether AIEs are suitable. This issue is all the more urgent considering that family members are increasingly aware of the use of AIEs in patients with DOC, pressure for these assessments is likely to increase in the context of ethical and clinical imperatives to meet standards of care, and pathways for reimbursement for such assessments in DOC are yet to be established. The new guidelines, however, provide no guiding principle for physicians to decide when such assessments are appropriate, a limitation that impedes their wide adoption. We address this important gap by proposing an easy to use algorithmic flowchart that is based on the new guidelines and can be used to determine the appropriateness of AIEs for any given patient with DOC and ensure that evidence-based best practices are being followed. We also provide a brief context for understanding the main categories of AIEs available to clinicians, their advantages, and their limitations.

Identification of preferential target sites for the environmental flow estimation using a simple flowchart in Korea

Since the 1960s, rapid urbanization has caused serious deterioration in the quantity and quality of instream flows in South Korea. As demands for healthy instream ecology, landscape, and water-friendly environments have increased, the government has revised the relevant legal codes. In 2017, the environmental flow, defined as the minimum flow to conserve the health of aquatic ecosystems, has been endorsed in the Water Environment Conservation Act. However, owing to the lack of established criteria for the selection of target sites, the implementation of environmental flow is still in its early stage. This study suggests a simple flowchart to identify the preferential target sites for environmental flow estimation. First, deterioration in the health of aquatic ecosystems is identified by comparing the monitored Fish Assessment Index (FAI) with the standard suggested by the Ministry of Environment. Thereafter, the conditions of discharge and water quality of the instream flows are assessed. In the discharge analysis, linear regression is used for three flow metrics to analyze the interannual variability of discharge. Discharge deficiency is evaluated by comparing the drought flow (Q₃₅₅) and the 10% mean annual flow. The load duration curve (LDC) is used in the water quality analysis. A case study is conducted for the Bokha-cheon Stream to test the flowchart, followed by a nationwide application. From the results, more than 70 sites have been identified as target sites for the estimation of the environmental flow in the five major river basins of Korea.

COVID-19 associated multisystem inflammatory syndrome in children mimicking acute appendicitis - how to differentiate and conduct pediatric patients during the pandemic? - Proposal of a management flowchart

INTRODUCTION

the new coronavirus pandemic has been a reality throughout 2020, and it has brought great challenges. The virus predominantly manifests in the pediatric population with mild symptoms. However, an increase in the incidence of Multisystemic Inflammatory Syndrome in Children (MIS-C) associated with COVID-19 has been described in the literature. MIS-C manifests mainly with fever and gastrointestinal symptoms and may mimic acute abdomen due to acute appendicitis. The objective of this study is to propose a care flowchart for suspected cases of acute appendicitis in the initial phase in pandemic times, considering the possibility of MIS-C. This situation was brought up by a patient treated in a pediatric hospital in Brazil.

DISCUSSION

It was possible to identify common signs and symptoms in the reported patient and those published cases that may serve as alerts for early identification of MIS-C cases. Based on the literature review and on the similarities between the syndrome and the inflammatory acute abdomen in children, we elaborated an initial approach for these cases to facilitate the identification, early diagnosis, and management. The flowchart considers details of the clinical history, physical examination, and complementary exams prior to the indication of appendectomy in patients with initial phase symptoms.

CONCLUSION

MIS-C, although rare and of poorly known pathophysiology, is most often severe and has a high mortality risk. The use of the proposed flowchart can help in the diagnosis and early treatment of MIS-C.

COMETS Analytics: An Online Tool for Analyzing and Meta-Analyzing Metabolomics Data in Large Research Consortia

Consortium-based research is crucial for producing reliable, high-quality findings, but existing tools for consortium studies have important drawbacks with respect to data protection, ease of deployment, and analytical rigor. To address these concerns, we developed COnsortium of METabolomics Studies (COMETS) Analytics to support and streamline consortium-based analyses of metabolomics and other -omics data. The application requires no specialized expertise and can be run locally to guarantee data protection or through a Web-based server for convenience and speed. Unlike other Web-based tools, COMETS Analytics enables standardized analyses to be run across all cohorts, using an algorithmic, reproducible approach to diagnose, document, and fix model issues. This eliminates the time-consuming and potentially error-prone step of manually customizing models by cohort, helping to accelerate consortium-based projects and enhancing analytical reproducibility. We demonstrated that the application scales well by performing 2 data analyses in 45 cohort studies that together comprised measurements of 4,647 metabolites in up to 134,742 participants. COMETS Analytics performed well in this test, as judged by the minimal errors that analysts had in preparing data inputs and the successful execution of all models attempted. As metabolomics gathers momentum among biomedical and epidemiologic researchers, COMETS Analytics may be a useful tool for facilitating large-scale consortium-based research.

Cross-Camera External Validation for Artificial Intelligence Software in Diagnosis of Diabetic Retinopathy

AIMS

To investigate the applicability of deep learning image assessment software VeriSee DR to different color fundus cameras for the screening of diabetic retinopathy (DR).

METHODS

Color fundus images of diabetes patients taken with three different nonmydriatic fundus cameras, including 477 Topcon TRC-NW400, 459 Topcon TRC-NW8 series, and 471 Kowa nonmyd 8 series that were judged as "gradable" by one ophthalmologist were enrolled for validation. VeriSee DR was then used for the diagnosis of referable DR according to the International Clinical Diabetic Retinopathy Disease Severity Scale. Gradability, sensitivity, and specificity were calculated for each camera model.

RESULTS

All images (100%) from the three camera models were gradable for VeriSee DR. The sensitivity for diagnosing referable DR in the TRC-NW400, TRC-NW8, and non-myd 8 series was 89.3%, 94.6%, and 95.7%, respectively, while the specificity was 94.2%, 90.4%, and 89.3%, respectively. Neither the sensitivity nor the specificity differed significantly between these camera models and the original camera model used for VeriSee DR development (p = 0.40, p = 0.065, respectively).

CONCLUSIONS

VeriSee DR was applicable to a variety of color fundus cameras with 100% agreement with ophthalmologists in terms of gradability and good sensitivity and specificity for the diagnosis of referable DR.

A dual mode self-test for a stand alone AES core

Advanced Encryption Standard (AES) is the most secured ciphertext algorithm that is unbreakable in a software platform's reasonable time. AES has been proved to be the most robust symmetric encryption algorithm declared by the USA Government. Its hardware implementation offers much higher speed and physical security than that of its software implementation. The testability and hardware Trojans are two significant concerns that make the AES chip complex and vulnerable. The problem of testability in the complex AES chip is not addressed yet, and also, the hardware Trojan insertion into the chip may be a significant security threat by leaking information to the intruder. The proposed method is a dual-mode self-test architecture that can detect the hardware Trojans at the manufacturing test and perform an online parametric test to identify parametric chip defects. This work contributes to partitioning the AES circuit into small blocks and comparing adjacent blocks to ensure self-referencing. The detection accuracy is sharpened by a comparative power ratio threshold, determined by process variations and the accuracy of the built-in current sensors. This architecture can reduce the delay, power consumption, and area overhead compared to other works.

AIPW: An R Package for Augmented Inverse Probability-Weighted Estimation of Average Causal Effects

An increasing number of recent studies have suggested that doubly robust estimators with cross-fitting should be used when estimating causal effects with machine learning methods. However, not all existing programs that implement doubly robust estimators support machine learning methods and cross-fitting, or provide estimates on multiplicative scales. To address these needs, we developed AIPW, a software package implementing augmented inverse probability weighting (AIPW) estimation of average causal effects in R (R Foundation for Statistical Computing, Vienna, Austria). Key features of the AIPW package include cross-fitting and flexible covariate adjustment for observational studies and randomized controlled trials (RCTs). In this paper, we use a simulated RCT to illustrate implementation of the AIPW estimator. We also perform a simulation study to evaluate the performance of the AIPW package compared with other doubly robust implementations, including CausalGAM, npcausal, tmle, and tmle3. Our simulation showed that the AIPW package yields performance comparable to that of other programs. Furthermore, we also found that cross-fitting substantively decreases the bias and improves the confidence interval coverage for doubly robust estimators fitted with machine learning algorithms. Our findings suggest that the AIPW package can be a useful tool for estimating average causal effects with machine learning methods in RCTs and observational studies.

A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets

Machine learning algorithms, including recent advances in deep learning, are promising for tools for detection and classification of broadband high frequency signals in passive acoustic recordings. However, these methods are generally data-hungry and progress has been limited by challenges related to the lack of labeled datasets adequate for training and testing. Large quantities of known and as yet unidentified broadband signal types mingle in marine recordings, with variability introduced by acoustic propagation, source depths and orientations, and interacting signals. Manual classification of these datasets is unmanageable without an in-depth knowledge of the acoustic context of each recording location. A signal classification pipeline is presented which combines unsupervised and supervised learning phases with opportunities for expert oversight to label signals of interest. The method is illustrated with a case study using unsupervised clustering to identify five toothed whale echolocation click types and two anthropogenic signal categories. These categories are used to train a deep network to classify detected signals in either averaged time bins or as individual detections, in two independent datasets. Bin-level classification achieved higher overall precision (>99%) than click-level classification. However, click-level classification had the advantage of providing a label for every signal, and achieved higher overall recall, with overall precision from 92 to 94%. The results suggest that unsupervised learning is a viable solution for efficiently generating the large, representative training sets needed for applications of deep learning in passive acoustics.

Ten simple rules on writing clean and reliable open-source scientific software

Functional, usable, and maintainable open-source software is increasingly essential to scientific research, but there is a large variation in formal training for software development and maintainability. Here, we propose 10 “rules” centered on 2 best practice components: clean code and testing. These 2 areas are relatively straightforward and provide substantial utility relative to the learning investment. Adopting clean code practices helps to standardize and organize software code in order to enhance readability and reduce cognitive load for both the initial developer and subsequent contributors; this allows developers to concentrate on core functionality and reduce errors. Clean coding styles make software code more amenable to testing, including unit tests that work best with modular and consistent software code. Unit tests interrogate specific and isolated coding behavior to reduce coding errors and ensure intended functionality, especially as code increases in complexity; unit tests also implicitly provide example usages of code. Other forms of testing are geared to discover erroneous behavior arising from unexpected inputs or emerging from the interaction of complex codebases. Although conforming to coding styles and designing tests can add time to the software development project in the short term, these foundational tools can help to improve the correctness, quality, usability, and maintainability of open-source scientific software code. They also advance the principal point of scientific research: producing accurate results in a reproducible way. In addition to suggesting several tips for getting started with clean code and testing practices, we recommend numerous tools for the popular open-source scientific software languages Python, R, and Julia.

From Forensics to Clinical Research: Expanding the Variant Calling Pipeline for the Precision ID mtDNA Whole Genome Panel

Despite a multitude of methods for the sample preparation, sequencing, and data analysis of mitochondrial DNA (mtDNA), the demand for innovation remains, particularly in comparison with nuclear DNA (nDNA) research. The Applied Biosystems™ Precision ID mtDNA Whole Genome Panel (Thermo Fisher Scientific, USA) is an innovative library preparation kit suitable for degraded samples and low DNA input. However, its bioinformatic processing occurs in the enterprise Ion Torrent Suite™ Software (TSS), yielding BAM files aligned to an unorthodox version of the revised Cambridge Reference Sequence (rCRS), with a heteroplasmy threshold level of 10%. Here, we present an alternative customizable pipeline, the PrecisionCallerPipeline (PCP), for processing samples with the correct rCRS output after Ion Torrent sequencing with the Precision ID library kit. Using 18 samples (3 original samples and 15 mixtures) derived from the 1000 Genomes Project, we achieved overall improved performance metrics in comparison with the proprietary TSS, with optimal performance at a 2.5% heteroplasmy threshold. We further validated our findings with 50 samples from an ongoing independent cohort of stroke patients, with PCP finding 98.31% of TSS's variants (TSS found 57.92% of PCP's variants), with a significant correlation between the variant levels of variants found with both pipelines.

Parametric and Nonparametric Methods in Population Pharmacokinetics: Experts' Discussion on Use, Strengths, and Limitations

Population pharmacokinetics consists of analyzing pharmacokinetic (PK) data collected in groups of individuals. Population PK is widely used to guide drug development and to inform dose adjustment via therapeutic drug monitoring and model-informed precision dosing. There are 2 main types of population PK methods: parametric (P) and nonparametric (NP). The characteristics of P and NP population methods have been previously reviewed. The aim of this article is to answer some frequently asked questions that are often raised by scholars, clinicians, and researchers about P and NP population PK methods. The strengths and limitations of both approaches are explained, and the characteristics of the main software programs are presented. We also review the results of studies that compared the results of both approaches in the analysis of real data. This opinion article may be informative for potential users of population methods in PK and guide them in the selection and use of those tools. It also provides insights on future research in this area.

Flowcharts improve periodontal diagnosis by dental and dental hygiene students

BACKGROUND

In 2017, the American Academy of Periodontology and the European Federation of Periodontology updated the classification of periodontal and peri-implant diseases and conditions. The goal of the present crossover study was to develop straightforward, illustrative flowcharts and determine their impact on the accuracy and speed of diagnosing periodontal conditions by predoctoral dental students (DS) and dental hygiene students (DHS).

METHODS

Two flowcharts (a decision-tree flowchart and one based on the periodontal disease/condition entity) were developed using updated diagnostic determinants proposed by the 2017 classification. A total of 26 second-, third-, and fourth-year DS (DS2, DS3, and DS4, respectively) and second-year DHS (DHS2) took a mock examination consisting of 10 periodontal clinical cases. The participants first diagnosed periodontal conditions using only their curricula-based knowledge (control) and then using the flowcharts (test). They also completed an optional post-examination questionnaire to provide feedback on the flowcharts. Statistical significance was detected at p ≤ 0.05.

RESULTS

Combined test groups had significantly higher accuracy in diagnosing periodontal conditions compared to controls (73.5% vs 50.0%, respectively), with the most substantial improvement in DS2 (66.3% vs 30%, respectively) and DHS2 (70.0% vs 41.4%, respectively). Combined test groups also completed the examination more quickly compared to controls (14.92 vs 20.85 minutes, respectively). The participants provided positive feedback and constructive criticism on the flowcharts, and also suggested converting them into application software.

CONCLUSION

The flowcharts significantly improved the accuracy of diagnosing periodontal conditions in academic settings, especially among junior, less experienced participants.

The Comparison of Point Prevalence Survey (PPS) and Gyssens Flowchart Approach on Antimicrobial Use Surveillance in Indonesian National Referral Hospital

The antimicrobial resistance (AMR) rate in Indonesia is steadily rising, despite the existing national action plan in 2014. In line with the Global Action Plan on AMR, proper surveillance on antimicrobial usage and resistance are needed. At present, antimicrobial surveillance (AMS) data in Indonesia is heterogeneous, fragmented, and localized. The common method of antimicrobial surveillance (AMS) in referral hospitals is by implementing Gyssens flowchart during Antimicrobial Resistance Control Program Committee clinical rounds. However, the recent method of AMS with Point Prevalence Survey (PPS) offers many advantages include its concise and simple protocol, large data collection, shorter required time, comprehensive data outcomes, real-time data, and standardized parameters. In low-middle income countries such as Indonesia with its restricted resources in AMS, PPS is superior compared to the 'traditional' hospital clinical round in generating representative and homogenous outcomes that can be compared to data from other centers worldwide.

MitoCellPhe reveals mitochondrial morphologies in single fibroblasts and clustered stem cells

Mitochondria are dynamic organelles that differ significantly in their morphologies across cell types, reflecting specific cellular needs and stages in development. Despite the wide biological significance in disease and in health, delineating mitochondrial morphologies in complex systems remains challenging. Here, we present the Mitochondrial Cellular Phenotype (MitoCellPhe) tool developed for quantifying mitochondrial morphologies and demonstrate its utility in delineating differences in mitochondrial morphologies in a human fibroblast and human induced pluripotent stem cell (hiPSC) line. MitoCellPhe generates 24 parameters, allowing for a comprehensive analysis of mitochondrial structures and importantly allows for quantification to be performed on mitochondria in images containing single cells or clusters of cells. With this tool, we were able to validate previous findings that show networks of mitochondria in healthy fibroblast cell lines and a more fragmented morphology in hiPSCs. Using images generated from control and diseased fibroblasts and hiPSCs, we also demonstrate the efficacy of the toolset in delineating differences in morphologies between healthy and the diseased state in both stem cell (hiPSC) and differentiated fibroblast cells. Our results demonstrate that MitoCellPhe enables high-throughput, sensitive, detailed, and quantitative mitochondrial morphological assessment and thus enables better biological insights into mitochondrial dynamics in health and disease.

Imaging of Cardiac Infections: A Comprehensive Review and Investigation Flowchart for Diagnostic Workup

Infections of the cardiovascular system may present with nonspecific symptoms, and it is common for patients to undergo multiple investigations to arrive at the diagnosis. Echocardiography is central to the diagnosis of endocarditis and pericarditis. However, cardiac computed tomography (CT) and magnetic resonance imaging also play an additive role in these diagnoses; in fact, magnetic resonance imaging is central to the diagnosis of myocarditis. Functional imaging (fluorine-18 fluorodeoxyglucose-positron emission tomography/CT and radiolabeled white blood cell single-photon emission computed tomography/CT) is useful in the diagnosis in prosthesis-related and disseminated infection. This pictorial review will detail the most commonly encountered cardiovascular bacterial and viral infections, including coronavirus disease-2019, in clinical practice and provide an evidence basis for the selection of each imaging modality in the investigation of native tissues and common prostheses.

High-throughput Interpretation of Killer-cell Immunoglobulin-like Receptor Short-read Sequencing Data with PING

The killer-cell immunoglobulin-like receptor (KIR) complex on chromosome 19 encodes receptors that modulate the activity of natural killer cells, and variation in these genes has been linked to infectious and autoimmune disease, as well as having bearing on pregnancy and transplant outcomes. The medical relevance and high variability of KIR genes makes short-read sequencing an attractive technology for interrogating the region, providing a high-throughput, high-fidelity sequencing method that is cost-effective. However, because this gene complex is characterized by extensive nucleotide polymorphism, structural variation including gene fusions and deletions, and a high level of homology between genes, its interrogation at high resolution has been thwarted by bioinformatic challenges, with most studies limited to examining presence or absence of specific genes. Here, we present the PING (Pushing Immunogenetics to the Next Generation) pipeline, which incorporates empirical data, novel alignment strategies and a custom alignment processing workflow to enable high-throughput KIR sequence analysis from short-read data. PING provides KIR gene copy number classification functionality for all KIR genes through use of a comprehensive alignment reference. The gene copy number determined per individual enables an innovative genotype determination workflow using genotype-matched references. Together, these methods address the challenges imposed by the structural complexity and overall homology of the KIR complex. To determine copy number and genotype determination accuracy, we applied PING to European and African validation cohorts and a synthetic dataset. PING demonstrated exceptional copy number determination performance across all datasets and robust genotype determination performance. Finally, an investigation into discordant genotypes for the synthetic dataset provides insight into misaligned reads, advancing our understanding in interpretation of short-read sequencing data in complex genomic regions. PING promises to support a new era of studies of KIR polymorphism, delivering high-resolution KIR genotypes that are highly accurate, enabling high-quality, high-throughput KIR genotyping for disease and population studies.

How is the medical assistance in dying (MAID) process carried out in Nova Scotia, Canada? A qualitative process model flowchart study

OBJECTIVES

The aims of this study are: (1) to create a flowchart process model of how medical assistance in dying (MAID) occurs in Nova Scotia (NS), Canada and (2) to detail how NS healthcare professionals are involved in each stage of MAID. The research questions are: how is the MAID process carried out and which professionals are involved at which points? and which roles and activities do professionals carry out during MAID?

DESIGN

Qualitative process model flowchart study with semistructured interviews.

SETTING

Primary and secondary care in NS, Canada.

PARTICIPANTS

Thirty-two interviewees self-selected to participate (12 physicians, 3 nurse practitioners (NP), 6 nurses, 6 pharmacists and 5 healthcare administrators and advocates). Participants were included if they conduct assessments, provide MAID, fill prescriptions, insert the intravenous lines, organise care and so on.

RESULTS

The flowchart process model details five stages of how MAID occurs in NS: (1) starting the MAID process, (2) MAID assessments, (3) MAID preparation (hospital in-patient, hospital outpatient, non-hospital), (4) day of MAID and (5) post-MAID (hospital in-patient and outpatient, non-hospital, after leaving setting). Nineteen points where the process could stop or be delayed were identified. MAID differs slightly by location and multiple professionals from different organisations are involved at different points. Some physicians and NP provide MAID for free as they cannot be reimbursed or find it too difficult to be reimbursed.

CONCLUSIONS

Our study adds knowledge about the MAID activities and roles of NS professionals, which are not documented in the international literature. Clinicians and pharmacists spend significant additional time to participate, raising questions about MAID's sustainability and uncompensated costs. The process model flowchart identifies where MAID can stop or be delayed, signalling where resources, training and relationship-building may need to occur. Knowing where potential delays can occur can help clinicians, administrators and policymakers in other jurisdictions improve MAID.

Integrating perspectives of patients, healthcare professionals, system developers and academics in the co-design of a digital information tool

Background

Patients diagnosed with cancer who are due to commence radiotherapy, often, despite the provision of a considerable amount of information, report a range of unmet information needs about the treatment process. Factors such as inadequate provision of information, or the stressful situation of having to deal with information about unfamiliar things, may influence the patient’s ability to comprehend the information. There is a need to further advance the format in which such information is presented. The composition of information should be tailored according to the patient’s individual needs and style of learning.

Method and findings

The PD methodology is frequently used when a technology designed artefact is the desired result of the process. This research is descriptive of its kind and provides a transparent description of the co-design process used to develop an innovative digital information tool employing PD methodology where several stakeholders participated as co-designers. Involving different stakeholders in the process in line with recommended PD activities enabled us to develop a digital information tool that has the potential to be relevant and user-friendly for the ultimate consumer.

Conclusions

Facilitating collaboration, structured PD activities can help researchers, healthcare professionals and patients to co-design patient information that meets the end users’ needs. Furthermore, it can enhance the rigor of the process, ensure the relevance of the information, and finally have a potential to employ a positive effect on the reach of the related digital information tool.

Emergency Department Utilization by In-hospital Healthcare Workers after COVID-19 Vaccination

BACKGROUND

This is an observational study to analyze an emergency department (ED) utilization pattern of coronavirus disease 2019 (COVID-19) vaccinated in-hospital healthcare workers (HCWs).

METHODS

We included 4,703 HCWs who were administered the first dose of the COVID-19 vaccine between March 4 and April 2, 2021, in a tertiary hospital in Korea where fast-track and post-vaccination cohort zone (PVCZ) were introduced in ED. We analyzed data of participants' age, sex, occupation, date and type of vaccination, and their clinical information using SPSS v25.0.

RESULTS

The sample comprised HCWs, who received either the ChAdOx1 (n = 4,458) or the BNT162B2 (n = 245) vaccines; most participants were female (73.5%), and 81.1% were under 50 years old. Further, 153 (3.3%) visited the ED and reported experiencing fever (66.9%) and myalgia (56.1%). Additionally, 91 (59.5%) of them were in their 20s, and 106 (67.5%) were assigned to the PVCZ. Lastly, 107 (68.2%) of the patients received parenteral management. No patient required hospitalization.

CONCLUSION

In conclusion, vaccinated HCWs who visited the ED with adverse events had a high incidence of fever and a low likelihood of developing serious illnesses. As the COVID-19 vaccination program for Korean citizens continues to expand, strategies to minimize unnecessary ED overcrowding should be put into effect.

Development of a Method for Clinical Evaluation of Artificial Intelligence-Based Digital Wound Assessment Tools

IMPORTANCE

Accurate assessment of wound area and percentage of granulation tissue (PGT) are important for optimizing wound care and healing outcomes. Artificial intelligence (AI)-based wound assessment tools have the potential to improve the accuracy and consistency of wound area and PGT measurement, while improving efficiency of wound care workflows.

OBJECTIVE

To develop a quantitative and qualitative method to evaluate AI-based wound assessment tools compared with expert human assessments.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study was performed across 2 independent wound centers using deidentified wound photographs collected for routine care (site 1, 110 photographs taken between May 1 and 31, 2018; site 2, 89 photographs taken between January 1 and December 31, 2019). Digital wound photographs of patients were selected chronologically from the electronic medical records from the general population of patients visiting the wound centers. For inclusion in the study, the complete wound edge and a ruler were required to be visible; circumferential ulcers were specifically excluded. Four wound specialists (2 per site) and an AI-based wound assessment service independently traced wound area and granulation tissue.

MAIN OUTCOMES AND MEASURES

The quantitative performance of AI tracings was evaluated by statistically comparing error measure distributions between test AI traces and reference human traces (AI vs human) with error distributions between independent traces by 2 humans (human vs human). Quantitative outcomes included statistically significant differences in error measures of false-negative area (FNA), false-positive area (FPA), and absolute relative error (ARE) between AI vs human and human vs human comparisons of wound area and granulation tissue tracings. Six masked attending physician reviewers (3 per site) viewed randomized area tracings for AI and human annotators and qualitatively assessed them. Qualitative outcomes included statistically significant difference in the absolute difference between AI-based PGT measurements and mean reviewer visual PGT estimates compared with PGT estimate variability measures (ie, range, standard deviation) across reviewers.

RESULTS

A total of 199 photographs were selected for the study across both sites; mean (SD) patient age was 64 (18) years (range, 17-95 years) and 127 (63.8%) were women. The comparisons of AI vs human with human vs human for FPA and ARE were not statistically significant. AI vs human FNA was slightly elevated compared with human vs human FNA (median [IQR], 7.7% [2.7%-21.2%] vs 5.7% [1.6%-14.9%]; P < .001), indicating that AI traces tended to slightly underestimate the human reference wound boundaries compared with human test traces. Two of 6 reviewers had a statistically higher frequency in agreement that human tracings met the standard area definition, but overall agreement was moderate (352 yes responses of 583 total responses [60.4%] for AI and 793 yes responses of 1166 total responses [68.0%] for human tracings). AI PGT measurements fell in the typical range of variation in interreviewer visual PGT estimates; however, visual PGT estimates varied considerably (mean range, 34.8%; mean SD, 19.6%).

CONCLUSIONS AND RELEVANCE

This study provides a framework for evaluating AI-based digital wound assessment tools that can be extended to automated measurements of other wound features or adapted to evaluate other AI-based digital image diagnostic tools. As AI-based wound assessment tools become more common across wound care settings, it will be important to rigorously validate their performance in helping clinicians obtain accurate wound assessments to guide clinical care.

Creating and controlling visual environments using BonVision

Real-time rendering of closed-loop visual environments is important for next-generation understanding of brain function and behaviour, but is often prohibitively difficult for non-experts to implement and is limited to few laboratories worldwide. We developed BonVision as an easy-to-use open-source software for the display of virtual or augmented reality, as well as standard visual stimuli. BonVision has been tested on humans and mice, and is capable of supporting new experimental designs in other animal models of vision. As the architecture is based on the open-source Bonsai graphical programming language, BonVision benefits from native integration with experimental hardware. BonVision therefore enables easy implementation of closed-loop experiments, including real-time interaction with deep neural networks, and communication with behavioural and physiological measurement and manipulation devices.