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Record W4380354002 · doi:10.1177/20543581231168088

Perspectives of Pediatric Nephrologists, Intensivists and Nurses Regarding AKI Management and Expected Outcomes

2023· article· en· W4380354002 on OpenAlexaffabout
Adrian Che, David D’Arienzo, Allison Dart, Cherry Mammen, Susan Samuel, Todd Alexander, Catherine Morgan, Tom Blydt‐Hansen, Patrícia S. Fontela, Gonzalo Garcia Guerra, Rahul Chanchlani, Stella Wang, Vedran Cockovski, Natasha Jawa, Jasmine Lee, Sophia Nunes, Stéphanie Reynaud, Michael Zappitelli

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsMcMaster UniversityUniversity of AlbertaStollery Children's HospitalAlberta Children's HospitalUniversity of ManitobaChildren's Hospital Research Institute of ManitobaUniversity of CalgaryMcGill UniversityUniversity of British ColumbiaHospital for Sick ChildrenBC Children's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineNephrologyLikert scalePediatric intensive care unitRenal replacement therapyIntensive care medicineIntensive care unitAcute kidney injuryDialysisEmergency medicineInternal medicineFamily medicine

Abstract

fetched live from OpenAlex

Background: Acute kidney injury (AKI) in critically ill children is associated with increased risk for short- and long-term adverse outcomes. Currently, there is no systematic follow-up for children who develop AKI in intensive care unit (ICU). Objective: This study aimed to assess variation regarding management, perceived importance, and follow-up of AKI in the ICU setting within and between healthcare professional (HCP) groups. Design: Anonymous, cross-sectional, web-based surveys were administered nationally to Canadian pediatric nephrologists, pediatric intensive care unit (PICU) physicians, and PICU nurses, via professional listservs. Setting: All Canadian pediatric nephrologists, PICU physicians, and nurses treating children in the ICU were eligible for the survey. Patients: N/A. Measurements: Surveys included multiple choice and Likert scale questions on current practice related to AKI management and long-term follow-up, including institutional and personal practice approaches, and perceived importance of AKI severity with different outcomes. Methods: Descriptive statistics were performed. Categorical responses were compared using Chi-square or Fisher’s exact tests; Likert scale results were compared using Mann-Whitney and Kruskal-Wallis tests. Results: Surveys were completed by 34/64 (53%) pediatric nephrologists, 46/113 (41%) PICU physicians, and 82 PICU nurses (response rate unknown). Over 65% of providers reported hemodialysis to be prescribed by nephrology; a mix of nephrology, ICU, or a shared nephrology-ICU model was reported responsible for peritoneal dialysis and continuous renal replacement therapy (CRRT). Severe hyperkalemia was the most important renal replacement therapy (RRT) indication for both nephrologists and PICU physicians (Likert scale from 0 [not important] to 10 [most important]; median = 10, 10, respectively). Nephrologists reported a lower threshold of AKI for increased mortality risk; 38% believed stage 2 AKI was the minimum compared to 17% of PICU physicians and 14% of nurses. Nephrologists were more likely than PICU physicians and nurses to recommend long-term follow-up for patients who develop any AKI during ICU stay (Likert scale from 0 [none] to 10 [all patients]; mean=6.0, 3.8, 3.7, respectively) ( P < .05). Limitations: Responses from all eligible HCPs in the country could not obtained. There may be differences in opinions between HCPs that completed the survey compared to those that did not. Additionally, the cross-sectional design of our study may not adequately reflect changes in guidelines and knowledge since survey completion, although no specific guidelines have been released in Canada since survey dissemination. Conclusions: Canadian HCP groups have variable perspectives on pediatric AKI management and follow-up. Understanding practice patterns and perspectives will help optimize pediatric AKI follow-up guideline implementation.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.339
Teacher spread0.310 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes2
Has abstractyes

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