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Record W4412555958 · doi:10.1177/20503121251356069

Contribution of intravenous medication diluent fluid composition on the development of dyschloremia in intensive care unit patients: A retrospective chart review

2025· article· en· W4412555958 on OpenAlexaff
Mahsa Movahedan, Glen Brown

Bibliographic record

VenueSAGE Open Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsHyperchloremiaMedicineHypochloremiaIntensive care unitRetrospective cohort studySerum chlorideHyponatremiaSalineDiluentIntensive care medicineAnesthesiaEmergency medicineSodiumInternal medicineChemistry

Abstract

fetched live from OpenAlex

Objective: Intravenous solutions such as dextrose 5% in water and 0.9% sodium chloride (normal saline) differ in electrolyte composition from human plasma and may contribute to serum chloride derangements (dyschloremia). This retrospective study aimed to explore the relationship between fluid composition, particularly medication diluents, and dyschloremia development in the intensive care unit. Methods: This was a retrospective chart review of adult intensive care unit patients with normal serum chloride on admission who developed dyschloremia after 48 h of intensive care unit admission. Data were collected on fluid types and volumes administered in the intensive care unit in the 7 days prior to dyschloremia onset. Descriptive statistics and chi-square tests were used to compare characteristics between patients who developed hyperchloremia and hypochloremia. Results: Of 884 screened patients, 85 developed dyschloremia after 48 h (41 hypochloremia, 44 hyperchloremia). There was no significant association between the proportion of normal saline or dextrose 5% in water-containing fluids and the type of dyschloremia. However, dexmedetomidine, typically diluted in normal saline, was associated with hyperchloremia. Conclusion: While total fluid composition was not associated with dyschloremia type, high-volume use of specific diluent-medication combinations may contribute. Strategies to minimize diluent volume could help reduce dyschloremia risk.

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)0.003
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 score0.691
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.330
Teacher spread0.306 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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