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Record W4403831654 · doi:10.1681/asn.20246r4yry1n

Prepivotal Study Exploring Safety, Efficacy, and Usability of the Automated Wearable Artificial Kidney (AWAK) PD Device

2024· article· en· W4403831654 on OpenAlexaff
Marjorie Wai Yin Foo, Edwina A. Brown, Arsh K. Jain, Martin Schreiber, Sheena Gow, Sanjay Singh, Mandar Gori, Suresha Belur Venkataraya, Htay Htay

Bibliographic record

VenueJournal of the American Society of Nephrology · 2024
Typearticle
Languageen
FieldComputer Science
TopicIoT and Edge/Fog Computing
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsUsabilityWearable computerComputer scienceMedicineHuman–computer interactionEmbedded system

Abstract

fetched live from OpenAlex

Background: The AWAK PD is an innovative, wearable sorbent-based device providing tidal PD. The device, weighing about 3kg, automates fills and drains, with adjustable glucose for customized ultrafiltration (UF) requirements. Methods: 14 subjects underwent screening (30 days), titration period (up to 21 days), washout (2 days), and a treatment period of at-home use (7 days) with an optional extension (23 days), at a single Singapore hospital. A nomogram and PD prescribing titration guide were developed to determine cartridge type, therapy duration, initial fill tonicity and glucose (absorbed/added) to achieve target UF. The primary aim was to complete at least 70% of sorbent dialysis in each therapy. Other aims included maintaining body weight within 5% of target weight, having stable plasma biochemistry and electrolytes, and assessing patients’ experience using symptom and device usability questionnaires. Illness Intrusiveness Rating Scale (IIRS) was assessed in the 3 subjects using AWAK for 30 days. Results: 11 subjects (10 male, mean±SD age 60±7 years and dialysis vintage 21±9 months) entered the 7-day treatment period, with 1 withdrawal. 3 of these subjects completed 30 days. No device-related serious adverse events occurred. 95% of therapies conducted (76/80) were completed. Optimal UF was achieved by adjusting the dextrose concentrations. All subjects remained within 5% of their target weight. Table 1 depicts plasma biochemistry and UF results. Usability scores were high; 10/11 patients agreed they were confident using the device and 8 felt the device was useful, 3 were neutral. IIRS scores improved in the 3 patients on AWAK for 30 days (average score: 38 at baseline; 20 after AWAK). Conclusion: AWAK PD is safe to use and a reduction in the IIRS is noted after 30 days of use; reasons could range from ease of use of the device to increased flexibility to suit their lifestyle. Minor device modifications can be done to optimize solute clearance. Funding: Commercial Support - AWAK Technologies Pte Ltd Table 1: Summary of analytes and UF - median (IQR). Interim data - database lock in Aug - Measure UF (mL) Weight (kg) Urea (mmol/L) Creatinine (μmol/L) β2-microglobulin (µg/L) Sodium (mmol/L) Potassium (mmol/L) Bicarbonate (mmol/L) Baseline 340 (158-669) 73.7 (64.9 - 88.0) 20.8 (19.9 - 22.9) 866 (761 - 1008) 23787 (20397 - 29819) 138 (136 - 141) 4.2 (3.8 - 4.5) 26.0 (25.0 - 28.1) AWAK 599 (288-829) 73.8 (63.9 - 87.0) 24.3 (21.2 - 28.0)* 987 (835 - 1066)* 23707 (20816 - 33471) 138 (136 - 139) 4.3 (4.1 - 4.5) 24.6 (23.8 - 26.2) *p-value <0.05

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.294
Teacher spread0.256 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2024
Admission routes1
Has abstractyes

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