Real-time virtual infection prevention and control assessments in skilled nursing homes, New York, March 2020-A pilot project.

OBJECTIVE: To describe a pilot project infection prevention and control (IPC) assessment conducted in skilled nursing facilities (SNFs) in New York State (NYS) during a pivotal 2-week period when the region became the nation's epicenter for coronavirus disease 2019 (COVID-19). DESIGN: A telephone and video assessment of IPC measures in SNFs at high risk or experiencing COVID-19 activity. PARTICIPANTS: SNFs in 14 New York counties, including New York City. INTERVENTION: A 3-component remote IPC assessment: (1) screening tool; (2) telephone IPC checklist; and (3) COVID-19 video IPC assessment (ie, "COVIDeo"). RESULTS: In total, 92 SNFs completed the IPC screening tool and checklist: 52 (57%) were conducted as part COVID-19 investigations, and 40 (43%) were proactive prevention-based assessments. Among the 40 proactive assessments, 14 (35%) identified suspected or confirmed COVID-19 cases. COVIDeo was performed in 26 (28%) of 92 assessments and provided observations that other tools would have missed: personal protective equipment (PPE) that was not easily accessible, redundant, or improperly donned, doffed, or stored and specific challenges implementing IPC in specialty populations. The IPC assessments took ∼1 hour each and reached an estimated 4 times as many SNFs as on-site visits in a similar time frame. CONCLUSIONS: Remote IPC assessments by telephone and video were timely and feasible methods of assessing the extent to which IPC interventions had been implemented in a vulnerable setting and to disseminate real-time recommendations. Remote assessments are now being implemented across New York State and in various healthcare facility types. Similar methods have been adapted nationally by the Centers for Disease Control and Prevention.

A description of the first Candida auris-colonized individuals in New York State, 2016-2017.

Candida auris (C. auris) is a globally emerging multidrug-resistant yeast. New York State (NYS) first detected C. auris in July 2016 and is the state most affected. This brief report describes characteristics of the first 114 individuals colonized with C. auris identified through active surveillance/screening by NYS Department of Health. "Colonized/screened" individuals were old (median age, 74 year), had extensive health care exposures and underlying conditions (multiple health care facility admissions in the 90 days prior with more than 80% requiring mechanical ventilation), and had 30- and 90-day mortality rates of 17.5% and 37.7%, respectively (with approximately 60% expired in the 2-year follow-up period). This description is helpful to inform additional prevention measures and add to the collective understanding of C. auris in the United States.

Design and implementation of a practical quality control program for dual-energy CT.

A novel routine dual-energy computed tomography (DECT) quality control (QC) program was developed to address the current deficiency of routine QC for this technology. The dual-energy quality control (DEQC) program features (1) a practical phantom with clinically relevant materials and concentrations, (2) a clinically relevant acquisition, reconstruction, and postprocessing protocol, and (3) a fully automated analysis software to extract quantitative data for database storage and trend analysis. The phantom, designed for easy set up for standalone or adjacent imaging next to the ACR phantom, was made in collaboration with an industry partner and informed by clinical needs to have four iodine inserts (0.5, 1, 2, and 5 mg/ml) and one calcium insert (100 mg/ml) equally spaced in a cylindrical water-equivalent background. The imaging protocol was based on a clinical DECT abdominal protocol capable of producing material specific concentration maps, virtual unenhanced images, and virtual monochromatic images. The QC automated analysis software uses open-source technologies which integrates well with our current automated CT QC database. The QC program was tested on a GE 750 HD scanner and two Siemens SOMATOM FLASH scanners over a 3-month period. The automated algorithm correctly identified the appropriate region of interest (ROI) locations and stores measured values in a database for monitoring and trend analysis. Slight variations in protocol settings were noted based on manufacturer. Overall, the project proved to provide a convenient and dependable clinical tool for routine oversight of DE CT imaging within the clinic.

Preparing education for the crises of tomorrow: A framework for adaptability.

The COVID-19 crisis has disrupted learning globally, exacerbating regional and global disparities that predated the pandemic. This rupture presents a unique opportunity to reimagine our educational system in times of both calm and crisis. Drawing on the work of political scientist Kathleen Thelen and economist and philosopher Amartya Sen, this article introduces a Framework for adaptability that outlines examples of flexible and equitable adaptation to change. The authors define adaptability as the ability of educational systems to respond to rapidly changing circumstances while maintaining stability, promoting equality, and expanding substantive freedoms and well-being. The key components of educational adaptability are: (1) cooperation, (2) inclusion, and (3) flexibility. This article describes how adaptability in education might be facilitated at individual, community, state and global levels. The authors call attention to a critical need to collectivise our approach to risk at the level of national governance. They suggest that this can be achieved by coordinating various professional, scientific, corporate, community and governmental stakeholders in order to ensure continuity in educational service provision, promoting lifelong learning and overall workforce participation.

Préparer l'éducation aux crises de demain : un cadre d'adaptabilité ­ La crise de la COVID-19 a perturbé l'apprentissage partout dans le monde, exacerbant les disparités régionales et mondiales antérieures à la pandémie. Cette rupture offre une occasion unique de réinventer notre système d'éducation tant en période de calme que de crise. S'inspirant des travaux de la politologue Kathleen Thelen et de l'économiste et philosophe Amartya Sen, cet article présente un cadre d'adaptabilité qui esquisse quelques exemples d'adaptation flexible et équitable au changement. Les auteurs définissent l'adaptabilité comme la capacité des systèmes d'éducation à répondre à des situations qui évoluent rapidement et en même temps à maintenir la stabilité, à promouvoir l'égalité et à accroître des libertés et un bien-être essentiels. Les éléments clés de l'adaptabilité éducative sont : (1) la coopération, (2) l'inclusion et (3) la flexibilité. Cet article décrit comment l'adaptabilité pourrait être facilitée dans l'éducation aux niveaux des individus, de la communauté, de l'État et du monde. Ses auteurs attirent l'attention sur le besoin crucial de collectiviser notre approche du risque à l'échelle de la gouvernance nationale. Ils indiquent que l'on peut y parvenir en coordonnant différents acteurs professionnels, scientifiques, entrepreneuriaux, communautaires et gouvernementaux afin d'assurer la continuité de l'offre des services éducatifs, de la promotion de l'apprentissage tout au long de la vie et de la participation générale de la main-d'œuvre.

Deformable Mapping Method to Relate Lesions in Dedicated Breast CT Images to Those in Automated Breast Ultrasound and Digital Breast Tomosynthesis Images.

This work demonstrates the potential for using a deformable mapping method to register lesions between dedicated breast computed tomography (bCT) and both automated breast ultrasound (ABUS) and digital breast tomosynthesis (DBT) images (craniocaudal [CC] and mediolateral oblique [MLO] views). Two multi-modality breast phantoms with external fiducial markers attached were imaged by the three modalities. The DBT MLO view was excluded for the second phantom. The automated deformable mapping algorithm uses biomechanical modeling to determine corresponding lesions based on distances between their centers of mass (dCOM) in the deformed bCT model and the reference model (DBT or ABUS). For bCT to ABUS, the mean dCOM was 5.2 ± 2.6 mm. For bCT to DBT (CC), the mean dCOM was 5.1 ± 2.4 mm. For bCT to DBT (MLO), the mean dCOM was 4.7 ± 2.5 mm. This application could help improve a radiologist's efficiency and accuracy in breast lesion characterization, using multiple imaging modalities.

Deformable mapping using biomechanical models to relate corresponding lesions in digital breast tomosynthesis and automated breast ultrasound images.

This work investigates the application of a deformable localization/mapping method to register lesions between the digital breast tomosynthesis (DBT) craniocaudal (CC) and mediolateral oblique (MLO) views and automated breast ultrasound (ABUS) images. This method was initially validated using compressible breast phantoms. This methodology was applied to 7 patient data sets containing 9 lesions. The automated deformable mapping algorithm uses finite element modeling and analysis to determine corresponding lesions based on the distance between their centers of mass (dCOM) in the deformed DBT model and the reference ABUS model. This technique shows that location information based on external fiducial markers is helpful in the improvement of registration results. However, use of external markers are not required for deformable registration results described by this methodology. For DBT (CC view) mapped to ABUS, the mean dCOM was 14.9 ±â€¯6.8 mm based on 9 lesions using 6 markers in deformable analysis. For DBT (MLO view) mapped to ABUS, the mean dCOM was 13.7 ±â€¯6.8 mm based on 8 lesions using 6 markers in analysis. Both DBT views registered to ABUS lesions showed statistically significant improvements (p ≤ 0.05) in registration using the deformable technique in comparison to a rigid registration. Application of this methodology could help improve a radiologist's characterization and accuracy in relating corresponding lesions between DBT and ABUS image datasets, especially for cases of high breast densities and multiple masses.

Deformable mapping technique to correlate lesions in digital breast tomosynthesis and automated breast ultrasound images.

PURPOSE: To develop a deformable mapping technique to match corresponding lesions between digital breast tomosynthesis (DBT) and automated breast ultrasound (ABUS) images. METHODS: External fiducial markers were attached to the surface of two CIRS multi-modality compressible breast phantoms (A and B) containing multiple simulated lesions. Both phantoms were imaged with DBT (upright positioning with cranial-caudal compression) and ABUS (supine positioning with anterior-to-chest wall compression). The lesions and markers were manually segmented by three different readers. Reader segmentation similarity and reader reproducibility were assessed using Dice similarity coefficients (DSC) and distances between centers of mass (dCOM ). For deformable mapping between the modalities each reader's segmented dataset was processed with an automated deformable mapping algorithm as follows: First, Morfeus, a finite element (FE) based multi-organ deformable image registration platform, converted segmentations into triangular surface meshes. Second, Altair HyperMesh, a FE pre-processor, created base FE models for the ABUS and DBT data sets. All deformation is performed on the DBT image data; the ABUS image sets remain fixed throughout the process. Deformation was performed on the external skin contour (DBT image set) to match the external skin contour on the ABUS set, and the locations of the external markers were used to morph the skin contours to be within a user-defined distance. Third, the base DBT-FE model was deformed with the FE analysis solver, Optistruct. Deformed DBT lesions were correlated with matching lesions in the base ABUS FE model. Performance (lesion correlation) was assessed with dCOM for all corresponding lesions and lesion overlap. Analysis was performed to determine the minimum number of external fiducial markers needed to create the desired correlation and the improvement of correlation with the use of external markers. RESULTS: Average DSC for reader similarity ranged from 0.88 to 0.91 (ABUS) and 0.57 to 0.83 (DBT). Corresponding dCOM ranged from 0.20 to 0.36 mm (ABUS) and 0.11 to 1.16 mm (DBT). Lesion correlation is maximized when all corresponding markers are within a maximum distance of 5 mm. For deformable mapping of phantom A, without the use of external markers, only two of six correlated lesions showed overlap with an average lesion dCOM of 6.8 ± 2.8 mm. With use of three external fiducial markers, five of six lesions overlapped and average dCOM improved to 4.9 ± 2.4 mm. For deformable mapping of Phantom B without external markers analysis, four lesions were correlated of seven with overlap between only one of seven lesions, and an average lesion dCOM of 9.7 ± 3.5 mm. With three external markers, all seven possible lesions were correlated with overlap between four of seven lesions. The average dCOM was 8.5 ± 4.0 mm. CONCLUSION: This work demonstrates the potential for a deformable mapping technique to relate corresponding lesions in DBT and ABUS images by showing improved lesion correspondence and reduced lesion registration errors with the use of external fiducial markers. The technique should improve radiologists' characterization of breast lesions which can reduce patient callbacks, misdiagnoses and unnecessary biopsies.

Design of Interrogation Protocols for Radiation Dose Measurements Using Optically-Stimulated Luminescent Dosimeters.

Optically-stimulated luminescent dosimeters are capable of being interrogated multiple times post-irradiation. Each interrogation removes a fraction of the signal stored within the optically-stimulated luminescent dosimeter. This signal loss must be corrected to avoid systematic errors in estimating the average signal of a series of optically-stimulated luminescent dosimeter interrogations and requires a minimum number of consecutive readings to determine an average signal that is within a desired accuracy of the true signal with a desired statistical confidence. This paper establishes a technical basis for determining the required number of readings for a particular application of these dosimeters when using certain OSL dosimetry systems.

Politically-motivated torture and child survivors.

It is critical that healthcare providers recognize behaviors common to children who have endured politically-motivated torture in order to create a safe and reliable treatment plan for such children and their families. Three vignettes taken from actual cases illustrate the way child survivors of torture are likely to present in educational, medical, or healthcare settings. Children or youth are resilient and can be helped to process their traumatic experiences and thrive emotionally and physically if providers are observant, competent and responsive. Federally funded resource centers exist to assist in caring for children who have survived torture.