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Record W3148142007 · doi:10.1016/j.xkme.2021.01.007

Telemedicine for Pediatric Nephrology: Perspectives on COVID-19, Future Practices, and Work Flow Changes

2021· review· en· W3148142007 on OpenAlex
Rupesh Raina, Nikhil Nair, Aditya Sharma, Ronith Chakraborty, Sarah Rush, Hui‐Kim Yap, Sidharth Kumar Sethi, Arvind Bagga, Pankaj Hari, Timothy E. Bunchman, Sharon Bartosh, Katherine Twombley, Gaurav Kapur, Mignon McCulloch, Guido Filler, Bradley A. Warady, María Ferris

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueKidney Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
FundersDepartment of Pediatrics, University of FloridaUniversity of North Carolina at Chapel HillSchulich School of Medicine and Dentistry, Western UniversityChildren's Mercy HospitalChildren's Hospital of MichiganJeju National University HospitalSchool of Medicine and Public Health, University of Wisconsin-MadisonAll-India Institute of Medical SciencesNational University of SingaporeUniversity of Cape TownVirginia Commonwealth UniversityUniversity of South Carolina
KeywordsTelemedicineDelphi methodMedicineWork (physics)ModalitiesPopulationIntensive care medicineMedical emergencyFamily medicineHealth careEnvironmental healthComputer scienceEngineeringPolitical science

Abstract

fetched live from OpenAlex

Although the use of telemedicine in rural areas has increased steadily over the years, its use was rapidly implemented during the onset of the coronavirus disease 2019 (COVID-19) crisis. Due to this rapid implementation, there is a lack of standardized work flows to assess and treat for various nephrotic conditions, symptoms, treatment modalities, and transition processes in the pediatric population. To provide a foundation/suggestion for future standardized work flows, the authors of this report have developed standardized work flows using the Delphi method. These work flows were informed based on results from cross-sectional surveys directed to patients and providers. Most patients and providers were satisfied, 87% and 71%, respectively, with their telemedicine visits. Common issues that were raised with the use of telemedicine included difficulty procuring physical laboratory results and a lack of personal warmth during telemedicine visits. The work flows created based on these suggestions will both enhance safety in treating patients and allow for the best possible care. Although the use of telemedicine in rural areas has increased steadily over the years, its use was rapidly implemented during the onset of the coronavirus disease 2019 (COVID-19) crisis. Due to this rapid implementation, there is a lack of standardized work flows to assess and treat for various nephrotic conditions, symptoms, treatment modalities, and transition processes in the pediatric population. To provide a foundation/suggestion for future standardized work flows, the authors of this report have developed standardized work flows using the Delphi method. These work flows were informed based on results from cross-sectional surveys directed to patients and providers. Most patients and providers were satisfied, 87% and 71%, respectively, with their telemedicine visits. Common issues that were raised with the use of telemedicine included difficulty procuring physical laboratory results and a lack of personal warmth during telemedicine visits. The work flows created based on these suggestions will both enhance safety in treating patients and allow for the best possible care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.449
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.116
GPT teacher head0.455
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it