Predictive Model of Dynamic Subphenotypes for 30-Day Mortality in Emergency Department Patients with Suspected Infection Using the Vital Signs of the First 24 Hours: An Analytical Cohort Study in a Tertiary Care Clinic

<b>Background/Objectives</b>: To determine and validate the cluster trajectory model by dynamic subphenotypes of vital signs in infecti ons and prediction of 30-day mortality. <b>Methods:</b> We conducted a prospective study in the emergency department of Clínica Colombia with patients with suspected infection. Clinical data, vital signs, and 30-day mortality were collected. Vital signs were measured within the first 24 h of admission, and patients were classified according to a vital signs trajectory model into four groups: A, B, C, and D. <b>Results</b>: The final cohort consisted of 625 patients, and the subphenotypes, according to the vital signs, were as follows: A-2.66% (all vital signs altered), B-9.2% (at least one alteration, predominantly hypertension), C-19% (minimal or no alteration, control), D-69.2% (only arterial hypotension). The primary outcome was mortality. Overall mortality was 8.6%, being higher in group A followed by D, B and C (<i>p</i> = 0.009). The risk increased progressively in groups B (OR = 2.87, CI 95%: 0.62-13.25), D (OR = 4.77, CI 95%: 1.46-15.58), and A (OR = 8.33, CI 95%: 1.54-45.05). Group A presented more frequently with pneumonia (<i>p</i> = 0.002), CNS infections (<i>p</i> = 0.021), mechanical ventilation (<i>p</i> < 0.001), and vasopressor support (<i>p</i> < 0.001). Significant differences among groups were found in leukocytosis (B vs. C <i>p</i> = 0.026), neutrophilia (B vs. C <i>p</i> = 0.001 and B vs. D <i>p</i> = 0.042), lymphocytosis (B vs. D <i>p</i> = 0.002), neutrophil/lymphocyte ratio (A vs. C <i>p</i> = 0. 010), lactate (C vs. D <i>p</i> = 0.044), anemia (B vs. D <i>p</i> = 0.013 and C vs. D <i>p</i> = 0.001), and CRP (A vs. C <i>p</i> = 0.004, B vs. C <i>p</i> < 0.001 and C vs. D <i>p</i> < 0.001). <b>Conclusions</b>: Patients with suspected infection and more altered vital signs have higher mortality (group A) and benefit from earlier interventions by sepsis teams in the emergency department.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Medicine
Published
2026-03-17
DOI
https://doi.org/10.3390/jcm15062264
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive Model of Dynamic Subphenotypes for 30-Day Mortality in Emergency Department Patients with Suspected Infection Using the Vital Signs of the First 24 Hours: An Analytical Cohort Study in a Tertiary Care Clinic

Manuel F. González-Varela, J. M. Barajas Martínez, Alvaro Daniel Patiño-Moncayo, Milciades Ibáñez-Pinilla et al.
Journal of Clinical Medicine
Sepsis Diagnosis and Treatment
article

Predictive Model of Dynamic Subphenotypes for 30-Day Mortality in Emergency Department Patients with Suspected Infection Using the Vital Signs of the First 24 Hours: An Analytical Cohort Study in a Tertiary Care Clinic

Manuel F. González-Varela, J. M. Barajas Martínez, Alvaro Daniel Patiño-Moncayo, Milciades Ibáñez-Pinilla, Luisa Fernanda Patiño-Unibio
article en

Abstract

<b>Background/Objectives</b>: To determine and validate the cluster trajectory model by dynamic subphenotypes of vital signs in infecti ons and prediction of 30-day mortality. <b>Methods:</b> We conducted a prospective study in the emergency department of Clínica Colombia with patients with suspected infection. Clinical data, vital signs, and 30-day mortality were collected. Vital signs were measured within the first 24 h of admission, and patients were classified according to a vital signs trajectory model into four groups: A, B, C, and D. <b>Results</b>: The final cohort consisted of 625 patients, and the subphenotypes, according to the vital signs, were as follows: A-2.66% (all vital signs altered), B-9.2% (at least one alteration, predominantly hypertension), C-19% (minimal or no alteration, control), D-69.2% (only arterial hypotension). The primary outcome was mortality. Overall mortality was 8.6%, being higher in group A followed by D, B and C (<i>p</i> = 0.009). The risk increased progressively in groups B (OR = 2.87, CI 95%: 0.62-13.25), D (OR = 4.77, CI 95%: 1.46-15.58), and A (OR = 8.33, CI 95%: 1.54-45.05). Group A presented more frequently with pneumonia (<i>p</i> = 0.002), CNS infections (<i>p</i> = 0.021), mechanical ventilation (<i>p</i> < 0.001), and vasopressor support (<i>p</i> < 0.001). Significant differences among groups were found in leukocytosis (B vs. C <i>p</i> = 0.026), neutrophilia (B vs. C <i>p</i> = 0.001 and B vs. D <i>p</i> = 0.042), lymphocytosis (B vs. D <i>p</i> = 0.002), neutrophil/lymphocyte ratio (A vs. C <i>p</i> = 0. 010), lactate (C vs. D <i>p</i> = 0.044), anemia (B vs. D <i>p</i> = 0.013 and C vs. D <i>p</i> = 0.001), and CRP (A vs. C <i>p</i> = 0.004, B vs. C <i>p</i> < 0.001 and C vs. D <i>p</i> < 0.001). <b>Conclusions</b>: Patients with suspected infection and more altered vital signs have higher mortality (group A) and benefit from earlier interventions by sepsis teams in the emergency department.

Journal of Clinical MedicineVol. 15(6)
Fundación Universitaria Sanitas (CO)
Good health and well-being
Openalex Percentile: Top 20%
Sepsis Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.