← Volver a resultados
Ficha bibliográfica · Consulta y acceso
Artículo de revista

Optimizing healthcare resources in pyogenic liver abscess: a dual-threshold HDL-CRP model for predicting hospitalization duration across multi-cohorts

Mingzhu Tao et al · Frontiers Media S.A · 2026

Acceso abierto disponible
Lectura rápida. Revisá los datos básicos del recurso y luego accedé al contenido desde el botón principal. En esta ficha solo se muestra la información necesaria para identificar la obra, citarla y abrirla.
Publicación seriada

A combined model of BCVA, TRAb, and NLR predicts response to intravenous methylprednisolone in dysthyroid optic neuropathy

Esta publicación seriada contiene 132 contenidos relacionados.

Acceso al recurso

Entrá al contenido desde la opción principal o elegí otra fuente disponible.

Acceso principal

Acceso abierto disponible

Recurso identificado como acceso abierto, sin confirmar automáticamente si es texto completo directo.
Abrir recurso

Resumen

Descripción general del contenido del recurso.

BackgroundProlonged hospitalization for pyogenic liver abscess (PLA) burdens patients and health systems. We examined whether admission high-density lipoprotein cholesterol (HDL-C) predicts length of stay (LOS) and whether a simple HDL–C-reactive protein (CRP) dual-threshold can flag patients at risk of prolonged stay.MethodsWe analyzed a prospective adult PLA cohort at a tertiary center (2018–2023; n = 138) and validated findings in MIMIC-IV ICU patients with liver abscess (n = 38) and in NHANES 2017–2020 (n = 9,226). Multivariable models related admission HDL-C to log-transformed LOS; model performance and calibration were assessed with internal resampling and external validation. We further evaluated a dual-threshold rule and conducted mediation analysis with CRP.ResultsLower HDL-C independently associated with longer LOS. A nomogram combining HDL-C, abscess size, and sepsis performed well (R2≈0.66; RMSE≈6.4 d) and remained directionally consistent across external datasets. A dual-threshold (HDL-C < 1.03 mmol/L and CRP > 1.0 mg/dL) identified a high-risk subgroup with greater odds of prolonged stay. CRP mediated a small proportion of the HDL-C–LOS association.ConclusionAdmission HDL-C, particularly when interpreted together with CRP, may help identify PLA patients at increased risk of prolonged hospitalization at the time of admission. Patients with low HDL-C and high CRP may warrant closer monitoring, earlier evaluation for source control or drainage, and more proactive inpatient planning. Prospective implementation studies are warranted.

Cómo citar

Elegí el formato que necesitás y copiá la referencia al portapapeles.

APA 7

al, M. T. E. (2026). Optimizing healthcare resources in pyogenic liver abscess: a dual-threshold HDL-CRP model for predicting hospitalization duration across multi-cohorts. https://doi.org/10.3389/fmed.2026.1708360

MLA

al, Mingzhu Tao et. "Optimizing healthcare resources in pyogenic liver abscess: a dual-threshold HDL-CRP model for predicting hospitalization duration across multi-cohorts." 2026. https://doi.org/10.3389/fmed.2026.1708360.

Chicago

al, Mingzhu Tao et. 2026. "Optimizing healthcare resources in pyogenic liver abscess: a dual-threshold HDL-CRP model for predicting hospitalization duration across multi-cohorts.". https://doi.org/10.3389/fmed.2026.1708360.

Harvard

al, M. T. E. 2026, Optimizing healthcare resources in pyogenic liver abscess: a dual-threshold HDL-CRP model for predicting hospitalization duration across multi-cohorts, Frontiers Media S.A, available at: https://doi.org/10.3389/fmed.2026.1708360 [Accessed 29 Jun. 2026].

Compartir e imprimir

Guardá la ficha, copiá su enlace permanente o imprimila como PDF.

Exportar referencia

Si usás un gestor bibliográfico, podés exportar el registro en los formatos más comunes.

Detalles del recurso

Información bibliográfica útil para confirmar que se trata del material correcto.

Título
Optimizing healthcare resources in pyogenic liver abscess: a dual-threshold HDL-CRP model for predicting hospitalization duration across multi-cohorts
Autor / colaboradores
Mingzhu Tao et al
Editorial
Frontiers Media S.A
Año de publicación
2026
ISSN
2296-858X
ISSN
2296-858X
Idioma
eng

Materias

Explorá otros recursos relacionados a partir de estas materias.

Copiado