Evidence map›Paper›PMID 41245894›Full record

ArticleComputational and structural biotechnology journal2025

Data-driven modelling of IRCU patient flow during the COVID-19 pandemic.

Ana Carmen Navas-Ortega, José Antonio Sánchez-Martínez, Paula García-Flores, Concepción Morales-García, Rene Fabregas

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Exploring novel kinetics of automated HMicrobiology spectrum · 2026
    Article
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

5 authors.

Ana Carmen Navas-OrtegaDepartment of Pneumology, University Hospital Virgen de Las Nieves, Granada, Spain.
José Antonio Sánchez-MartínezDepartment of Pneumology, University Hospital Virgen de Las Nieves, Granada, Spain.
Paula García-FloresDepartment of Pneumology, University Hospital Virgen de Las Nieves, Granada, Spain.
Concepción Morales-GarcíaDepartment of Pneumology, University Hospital Virgen de Las Nieves, Granada, Spain.
Rene FabregasDepartment of Applied Mathematics and Modeling Nature (MNat) Research Unit, Faculty of Sciences, University of Granada, Granada, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Intermediate Respiratory Care Units (IRCUs) function as vital intermediaries between general wards and Intensive Care Units (ICUs), particularly during crises such as the COVID-19 pandemic. A unit's effectiveness depends on its structure, protocols, and clinical expertise. In this study, we assessed the clinical outcomes and operational dynamics of a new IRCU that implemented a specialist staffing model during the pandemic in Spain. Methods: We conducted a prospective cohort study at the UHVN IRCU (Granada, Spain) from April to August 2021, enrolling 249 adult patients with COVID-19-associated respiratory failure. We collected data on patient demographics, Non-Invasive Ventilation (NIV) use, length of stay (LOS), and outcomes, including ICU transfer, mortality, and recovery. We then analysed these outcomes stratified by NIV status. Furthermore, we developed and calibrated a compartmental Ordinary Differential Equation (ODE) model and an empirical LOS-based convolution model to simulate patient flow dynamics under scenarios of admission surges and varying care efficiency. Results: The cohort's median age was 51 years, and 31 % (n=77) required NIV. Patients requiring NIV were significantly older than those who did not (median 61 vs 42 years, Conclusion: This IRCU, characterised by specialist clinical staffing, demonstrated effective management of severe COVID-19 respiratory failure. We observed high recovery rates, particularly among NIV patients, which eased pressure on ICU resources. Our dynamic modelling confirmed the unit's vulnerability to admission surges but also quantified the positive impact of efficient care. These findings underscore the importance of well-structured and expertly staffed IRCUs in pandemic response and the broader provision of respiratory care.

Indexed as

Clinical outcomesClinical staffCOVID-19Healthcare operationsIntermediate respiratory care unitMathematical modellingNon-invasive ventilationPatient flow dynamicsRespiratory failure

Identifiers

PMID41245894
PMCPMC12613035

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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.