Evidence map›Paper›PMID 39337977›Full record

ArticleLife (Basel, Switzerland)2024

Tracing In-Hospital COVID-19 Outcomes: A Multistate Model Exploration (TRACE).

Hamed Mohammadi, Hamid Reza Marateb, Mohammadreza Momenzadeh, Martin Wolkewitz, Manuel Rubio-Rivas

Abstract read
In one paragraph

Article in Life (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Hamed MohammadiBiomedical Engineering Department, Engineering Faculty, University of Isfahan, Isfahan 81746-73441, Iran.
Hamid Reza MaratebBiomedical Engineering Department, Engineering Faculty, University of Isfahan, Isfahan 81746-73441, Iran.ORCID 0000-0003-4408-2397
Mohammadreza MomenzadehDepartment of Artificial Intelligence, Smart University of Medical Sciences, Tehran 1553-1, Iran.
Martin WolkewitzInstitute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, 79104 Freiburg, Germany.
Manuel Rubio-RivasDepartment of Internal Medicine, Bellvitge University Hospital, Hospitalet de Llobregat, 08907 Barcelona, Spain.ORCID 0000-0002-9548-1374

Funding

Beatriu de Pinós post-doctoral programme from the Office of the Secretary of Universities and Research from the Ministry of Business and Knowledge of the Government of Catalonia 2020 BP 00261
6 · The paper itself

Abstract

This study aims to develop and apply multistate models to estimate, forecast, and manage hospital length of stay during the COVID-19 epidemic without using any external packages. Data from Bellvitge University Hospital in Barcelona, Spain, were analyzed, involving 2285 hospitalized COVID-19 patients with moderate to severe conditions. The implemented multistate model includes transition probabilities and risk rates calculated from transitions between defined states, such as admission, ICU transfer, discharge, and death. In addition to examining key factors like age and gender, diabetes, lymphocyte count, comorbidity burden, symptom duration, and different COVID-19 waves were analyzed. Based on the model, patients hospitalized stay an average of 11.90 days before discharge, 2.84 days before moving to the ICU, or 34.21 days before death. ICU patients remain for about 24.08 days, with subsequent stays of 124.30 days before discharge and 35.44 days before death. These results highlight hospital stays' varying durations and trajectories, providing critical insights into patient flow and healthcare resource utilization. Additionally, it can predict ICU peak loads for specific subgroups, aiding in preparedness. Future work will integrate the developed code into the hospital's Health Information System (HIS) following ISO 13606 EHR standards and implement recursive methods to enhance the model's efficiency and accuracy.

Indexed as

comorbidityCOVID-19diabetes mellitushospital length of staylymphocytesmortalitymultistate modelprognosisrisk factors

Identifiers

PMID39337977
PMCPMC11433282

What OpenQuestion holds

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Registered trials

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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.