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Record W4388787284

The Impact of Intravenous Fluid Therapy on Acid-Base Status of Critically Ill Adults: A Stewart Approach-Based Perspective

2020· article· en· W4388787284 on OpenAlexaboutno aff
Gültekin Yücel, Selçuk Yazıcı

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsnot available
Fundersnot available
KeywordsCritically illPerspective (graphical)MedicineIntensive care medicineCritical illnessIntravenous fluidSurgeryComputer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Ozgur Kilic,1 Yucel Gultekin,2 Selcuk Yazici1 1Siyami Ersek Thoracic and Cardiovascular Surgery Center, Cardiology Department, Cardiac Intensive Care Unit, Istanbul, Turkey; 2Mersin University Hospital, General Surgery Department, Mersin, TurkeyCorrespondence: Ozgur KilicSiyami Ersek Thoracic and Cardiovascular Surgery Center, Cardiology Department, Cardiac Intensive Care Unit, Istanbul, TurkeyTel +90 505 826 09 12Email Rugzo63@hotmail.comAbstract: One of the most important tasks of physicians working in intensive care units (ICUs) is to arrange intravenous fluid therapy. The primary indications of the need for intravenous fluid therapy in ICUs are in cases of resuscitation, maintenance, or replacement, but we also load intravenous fluid for purposes such as fluid creep (including drug dilution and keeping venous lines patent) as well as nutrition. However, in doing so, some facts are ignored or overlooked, resulting in an acid-base disturbance. Regardless of the type and content of the fluid entering the body through an intravenous route, it may impair the acid-base balance depending on the rate, volume, and duration of the administration. The mechanism involved in acid-base disturbances induced by intravenous fluid therapy is easier to understand with the help of the physical-chemical approach proposed by Canadian physiologist, Peter Stewart. It is possible to establish a quantitative link between fluid therapy and acid–base disturbance using the Stewart principles. However, it is not possible to accomplish this with the traditional approach; moreover, it may not be noticed sometimes due to the normalization of pH or standard base excess induced by compensatory mechanisms. The clinical significance of fluid-induced acid-base disturbances has not been completely clarified yet. Nevertheless, as fluid therapy may be the cause of unexplained acid-base disorders that may lead to confusion and elicit unnecessary investigation, more attention must be paid to understand this issue. Therefore, the aim of this paper is to address the effects of different types of fluid therapies on acid-base balance using the simplified perspective of Stewart principles. Overall, the paper intends to help recognize fluid-induced acid-base disturbance through bedside evaluation and choose an appropriate fluid by considering the acid-base status of a patient.Keywords: Stewart approach, fluid therapy, acid-base disturbance, strong ion difference, total weak acid concentration

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.163
GPT teacher head0.511
Teacher spread0.347 · 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 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
Published2020
Admission routes1
Has abstractyes

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