ArticleAnesthesiology and pain medicine2022
Evaluating the Efficacy of the National Early Warning Score in Predicting the Mortality of Stroke Patients Admitted to Intensive Care Units.
Article in Anesthesiology and pain medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 6 citations in OpenAlex.
- Article
- An explainable artificial intelligence framework for clinical decision support in stroke discharge planning.PloS one · 2026Article
- Investigating the Predictive Power of the National Early Warning Score in Predicting Outcomes Among Intensive Care Unit Patients.Critical care research and practice · 2026Article
- Assessing the relationship between supervisor knowledge sharing and innovative behaviors among clinical nurses: the mediating role of organizational learning.BMC nursing · 2025Article
- Nurses' care coordination competence in mechanically ventilated patients in intensive care units: a cross-sectional study.BMC health services research · 2025Article
- Assessing employee silence about patient safety and its association with environmental factors among nurses in Ardabil: a cross-sectional study.BMC health services research · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: National Early Warning Score (NEWS) is a tool used to identify patients at risk. Scores are based on initial clinical observations, including heart rate, respiration rate, systolic blood pressure, oxygen saturation, level of consciousness, body temperature, and oxygen support. To date, few studies have been conducted on NEWS evaluation worldwide, and no study has been conducted in Iran. Objectives: This study aims to evaluate the efficacy of the NEWS in predicting the mortality of stroke patients admitted to intensive care units (ICU). Methods: The present cross-sectional study included 90 patients with a definitive diagnosis of cerebrovascular accident (CVA) based on symptoms and para-clinical evidence. At the beginning of admission to the ICU and up to first 24 hours of admission, all NEWS parameters were measured and evaluated. Results: There was a significant relationship between systolic blood pressure, respiratory support, heart rate, and level of consciousness with patients' discharge status. Also, there was no significant relationship between age, sex, respiratory rate, SPO2, and fever with discharge status. In addition, there was a significant relationship between clinical risk based on NEWS scoring system and patients' status. Conclusions: Our results showed a significant relationship between clinical risk based on NEWS scoring and patients' discharge status so that there was a significant increase in mortality in patients with higher NEWS.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.