Evidence map›Paper›PMID 30063769›Full record

ArticlePloS one2018

Evaluation of the SpO2/FiO2 ratio as a predictor of intensive care unit transfers in respiratory ward patients for whom the rapid response system has been activated.

Won Gun Kwack, Dong Seon Lee, Hyunju Min, Yun Young Choi, Miae Yun, Youlim Kim, Sang Hoon Lee, Inae Song, Jong Sun Park, Young-Jae Cho and 5 more

Registry-linked trialAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04361435 (Comparison of Two Methods to Airway Clearance in Patients Admitted to Intensive Care Unit for COVID-19), which is not on this map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

NCT04361435 naunknown statusnot on this mapstarted 2020, after this paper: background citation

Comparison of Two Methods to Airway Clearance in Patients Admitted to Intensive Care Unit for COVID-19: A Pilot Corssover Randomized Controlled Trial

TypeinterventionalSponsorSt. Justine's HospitalRan2020 to 2020Enrolled50ConditionsCOVID-19, PhysiotherapyArmsChest physiotherapy using a non-invasive oscillating device
3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Delta MEWS combined with SpOFrontiers in medicine · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Article
  13. Association between SpOIndian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2021
    Article
  14. Predicting in-hospital mortality for sepsis: a comparison between qSOFA and modified qSOFA in a 2-year single-centre retrospective analysis.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2021
    Observational
  15. Article
  16. Article
  17. Mortality Prediction Using SaOCritical care research and practice · 2021
    Article
  18. Observational
  19. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Won Gun KwackDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Dong Seon LeeInterdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Hyunju MinInterdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Yun Young ChoiInterdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Miae YunInterdepartment of Critical Care Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Youlim KimDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Sang Hoon LeeDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Inae SongDepartment of Anesthesiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID 0000-0002-7814-4253
Jong Sun ParkDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Young-Jae ChoDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
You Hwan JoDepartment of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Ho Il YoonDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Jae Ho LeeDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Choon-Taek LeeDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Yeon Joo LeeDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID 0000-0001-7697-4272

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efforts to detect patient deterioration early have led to the development of early warning score (EWS) models. However, these models are disease-nonspecific and have shown variable accuracy in predicting unexpected critical events. Here, we propose a simpler and more accurate method for predicting risk in respiratory ward patients. This retrospective study analyzed adult patients who were admitted to the respiratory ward and detected using the rapid response system (RRS). Study outcomes included transfer to the intensive care unit (ICU) within 24 hours after RRS activation and in-hospital mortality. Prediction power of existing EWS models including Modified EWS (MEWS), National EWS (NEWS), and VitalPAC EWS (ViEWS) and SpO2/FiO2 (SF) ratio were compared to each other using the area under the receiver operating characteristic curve (AUROC). Overall, 456 patients were included; median age was 75 years (interquartile range: 65-80) and 344 (75.4%) were male. Seventy-three (16.0%) and 79 (17.3%) patients were transferred to the ICU and died. The SF ratio displayed better or comparable predictive accuracy for unexpected ICU transfer (AUROC: 0.744) compared to MEWS (0.744 vs. 0.653, P = 0.03), NEWS (0.744 vs. 0.667, P = 0.04), and ViEWS (0.744 vs. 0.675, P = 0.06). For in-hospital mortality, although there was no statistical difference, the AUROC of the SF ratio (0.660) was higher than that of each of the preexisting EWS models. In comparison with the preexisting EWS models, the SF ratio showed better or comparable predictive accuracy for unexpected ICU transfers in the respiratory wards.

Indexed as

Critical CareNoninvasive VentilationOximetryPatient TransferAgedAged, 80 and overCritical IllnessFemaleHospital MortalityHumansInhalationIntensive Care UnitsMaleOxygen ConsumptionPredictive Value of TestsPrognosis

Identifiers

PMID30063769
PMCPMC6067747

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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.