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

Latent transition analysis for longitudinal studies of post-acute infection syndromes.

Nature communications - 10 Feb 2026

Gusinow Roy, Górska Anna, Canziani Lorenzo Maria, Lopes-Rafegas Iris, Alvarez Garavito Carolina, Tami Adriana, Gentilotti Elisa, Sicuri Elisa, Laouénan Cédric, Ghosn Jade, Florence Aline-Marie, Lahfej Nadhem, Mazzaferri Fulvia, Del Piccolo Lidia, Giannella Maddalena, Toschi Alice, Di Chiara Michela, Caponcello Maria Giulia, Palacios-Baena Zaira R, Wold Karin I, Rossi Elisa, Tacconelli Evelina, Hasenauer Jan

Abstract excerpt

Post-Acute Infectious Syndromes (PAIS) refer to the symptoms persisting months after initial infection. Clinical research studies on this topic often collect rich, multi-modal datasets. Yet, the complexity of the datasets and the lack of a precise clinical case definition pose difficulties in creating comprehensive analyses. Here, we present a generalisable framework for analysing data from longitudinal studies...

Read the complete abstract on PubMed

Topics

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

Share to Aged

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to COVID-19

Share to LTA gene

Share to Longitudinal Studies

Share to Phenotype

Share to SARS-CoV-2

Source

Open in PubMed Open full text

Identifiers

PMID: 41667444
DOI: 10.1038/s41467-026-68650-7
PMCID: PMC13000239

Genes

LTA

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Latent transition analysis for longitudinal studies of post-acute infection syndromes.PMID 41667444Read ↗

Latent Transition Analysis for Longitudinal Studies of Post-Acute Infection Syndromes: A Multinational Investigation of Post-COVID-19 ConditionSemantic proximity Read ↗

Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER ProgramsSemantic proximity Read ↗

Evaluation of post-acute COVID-19 health outcomes (ECHOES) in England: The development of national surveillance system for long- term health outcomes following COVID-19Semantic proximity Read ↗

Natural course of post COVID-19 condition and implications for trial design and outcome selection: A population-based longitudinal cohort studySemantic proximity Read ↗

Longitudinal dynamic clinical phenotypes of in-hospital COVID-19 patients across three dominant virus variants in New York.Semantic proximity Read ↗

Machine Learning Analysis of Post-Acute COVID Symptoms Identifies Distinct Clusters, Severity Groups, and TrajectoriesSemantic proximity Read ↗

COVID-19 pulmonary phenotypes and longitudinal patterns in the first wave of the pandemic.Semantic proximity Read ↗

Identifying Long Covid phenotypes and their association with personal characteristics, healthcare use, and daily life burden: population-based study in Belgium.Semantic proximity Read ↗

Long COVID Longitudinal Symptoms Burden Clusters Within A National Community-Based CohortSemantic proximity Read ↗

Temporal Learning with Dynamic Range (TLDR) for Modeling Recurrent Exposure and Treatment OutcomesSemantic proximity Read ↗

Longitudinal modeling of multimorbidity trajectories using large language modelsSemantic proximity Read ↗

A Data-Driven Identification of People Recovering from Post-Acute Sequelae of SARS-CoV-2 Infection (PASC)Semantic proximity Read ↗

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