Bioavailability of Orally Administered Drugs in Critically Ill Patients
Bibliographic record
Abstract
Critically ill patients managed in the Intensive Care Unit (ICU) suffer from several pathophysiological alterations due to critical illness resulting in potential changes in the pharmacokinetics of drugs including systemic absorption. Nevertheless, these patients are still given some medications in unadjusted doses thereby putting the patients at a risk for therapy failure. The objective for this study was to summarize the available evidence regarding oral drug absorption in the ICU. A literature search of the databases MEDLINE, EMBASE, and PubMed was conducted on (February 24, 2020). Articles discussing the rate and/or extent of orally administered drugs in critically ill patients were included. A total of 58 studies were found: 17 interventional studies, 33 observational studies (30 prospective, 3 retrospective) and 8 case reports. A total of 43 articles reported altered drug absorption in critically ill patients suggesting the need for alternative measures to facilitate treatment success. The absorption of orally administered drugs may be altered in critically ill patients. Measures for altered drug absorption in critically ill patients were suggested such as holding tube feeding before and after medication administration, increasing doses of orally administrated drugs and using alternate routes of administration.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".