Coronavirus Disease 2019 (COVID-19): A Literature Review from a Nursing Perspective
Bibliographic record
Abstract
INTRODUCTION: As the COVID-19 pandemic ravages the world, nursing resources, and capacities play an essential role in disease management. This literature review focuses on the central issues related to the nursing care of patients affected by COVID-19. MATERIAL AND METHODS: This literature review was conducted with an extensive search of databases, including PubMed, Web of Science (WOS), and Scopus, using the keywords "COVID19", "2019-nCoV disease", "2019 novel coronavirus infection", "Nurse", "NursingCare", and" Nursing management." The span of the literature search was between December 01, 2020, and January 12, 2021. A total of 28 original and English-language articles were selected for inclusion in the review. RESULTS: Nursing interventions such as monitoring, oxygen therapy, and the use of Extra Corporeal Membrane Oxygenation (ECMO) in the care of COVID-19 patients, caring for ICU patients with COVID-19, rehabilitation of COVID-19 patients, nurses' experiences and barriers in the care of patients with COVID-19, and also the ethical challenges in the care of patients with COVID-19, were found to be valuable in managing COVID-19 patients. CONCLUSION: Nurses have a pivotal role to play in the care of patients with COVID-19. Therefore, providing comprehensive and quality nursing care supported by experience and research is necessary to successfully reduce the length of hospital stay and decrease the morbidity and mortality rates of COVID-19.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
| grok | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| opus | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | medium |
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".