Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Derivation and validation of new prehospital phenotypes for adults with COVID-19.

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias - 1 Oct 2022

Alberdi-Iglesias Ana, López-Izquierdo Raúl, Ortega Guillermo J, Sanz-García Ancor, Del Pozo Vegas Carlos, Delgado Benito Juan F, Martín-Rodríguez Francisco

Abstract excerpt

OBJECTIVES: To characterize phenotypes of prehospital patients with COVID-19 to facilitate early identification of at-risk groups. MATERIAL AND METHODS: Multicenter observational noninterventional study of a retrospective cohort of 3789 patients, analyzing 52 prehospital variables. The main outcomes were 4 clusters of prehospital variables describing the phenotypes. Secondary outcomes were hospitalization,...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to COVID-19
Share to Phenotype

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Respiration, Artificial

Source

Identifiers

PMID: 36217931

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Derivation and validation of new prehospital phenotypes for adults with COVID-19.PMID 36217931Read ↗

Novel Prehospital Phenotypes and Outcomes in Adult-Patients with Acute Disease.Semantic proximity Read ↗

Identification and validation of clinical phenotypes with prognostic implications in patients admitted to hospital with COVID-19: a multicentre cohort study.Semantic proximity Read ↗

Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2,022 critically ill patients with COVID-19 in SpainSemantic proximity Read ↗

Bedside clinical data subphenotypes of critically ill COVID-19 patients: a cohort study.Semantic proximity Read ↗

Characterizing COVID-19 Clinical Phenotypes and Associated Comorbidities and Complication ProfilesSemantic proximity Read ↗

Identifying COVID-19 phenotypes using cluster analysis and assessing their clinical outcomesSemantic proximity Read ↗

Characterizing COVID-19 clinical phenotypes and associated comorbidities and complication profiles.Semantic proximity Read ↗

Risk factors for severe COVID-19 differ by age: a retrospective study of hospitalized adultsSemantic proximity Read ↗

Phenotypes and Subphenotypes of Patients With COVID-19: A Latent Class Modeling Analysis.Semantic proximity Read ↗

Long COVID's Hidden Complexity: Machine Learning Reveals Why Personalized Care Remains EssentialSemantic proximity Read ↗

COVID-19 Mortality Risk Assessment: An International Multi-Center StudySemantic proximity Read ↗

Establishment of Routine Clinical Indicators-Based Nomograms for Predicting the Mortality in Patients with COVID-19Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.