An observational study in Critical Illness, Recovery Outcomes and Critical Care, Intensive Care, sponsored by Lisbon Academic Medical Center - Centro Académico de Medicina de Lisboa. Recruiting at 7 sites in Portugal. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-04-13.
Sponsored by Lisbon Academic Medical Center - Centro Académico de Medicina de Lisboa · Observational
Persistent Critical Illness (PCI) is a condition that affects some patients who remain in the Intensive Care Unit (ICU) for a long time, usually more than 10-14 days. It is estimated to occur in 5-20% of critically ill patients. A recent Portuguese study found that more than 14% of ICU patients stayed longer than 14 days. PCI is often associated with ongoing need for life support, such as mechanical ventilation or medications to maintain blood pressure. However, patients may also experience severe muscle weakness, repeated infections, or other complications, which makes this group very diverse.
One of the main risk factors for prolonged ICU stay is sepsis, a severe infection that affects the whole body. Other factors-such as prior health conditions, use of corticosteroids, sedation practices, early versus late mobilization, fluid and antibiotic management, and delirium treatment-may also influence the development and course of PCI.
This study aims to identify different clinical patterns ("clusters") among critically ill patients who remain in the ICU for more than 10 days. Patients will be followed until hospital discharge, and up to one year if data are available. Understanding these different patterns will help develop more personalized and effective care strategies for each patient profile.
The study is a multicenter retrospective cohort including adult patients (≥18 years) admitted to participating ICUs for more than 5 days between 2021 and 2023. Data collected will include demographic, clinical, and laboratory information, details of organ support (such as mechanical ventilation or vasopressors), medications, nutrition, and rehabilitation practices.
Statistical and machine learning methods will be used to identify groups of patients with similar clinical trajectories and to assess how these groups are related to outcomes such as survival, recovery of organ function, or long-term disability.
Expected results are the identification of distinct clinical clusters of PCI that combine clinical and laboratory data, and the development of tailored management strategies to improve recovery and outcomes for patients with PCI.
This study will include adult patients (≥18 years old) who are consecutively admitted to participating intensive care units (ICUs) and remain in the ICU for 5 or more days. The focus will be on patients who survive the early phase of critical illness, allowing the formation of a relatively homogeneous cohort of early ICU survivors.
The population will comprise patients with a wide range of critical illnesses, including sepsis, respiratory failure, cardiovascular instability, and multi-organ dysfunction, who require ongoing organ support such as invasive mechanical ventilation or vasopressors. Patients with prolonged ICU stays exceeding 10 days who continue to require organ support will be further characterized as having Persistent Critical Illness.
Exclusion Criteria:
Adult patients (≥18 years) admitted to participating intensive care units (ICUs) who remained in the ICU for more than 5 days.
Need for one or more continuous organ support treatment at Day 10
Data from patients who remain in the ICU for more than 10 days requiring ongoing organ support, such as invasive mechanical ventilation, renal replacement therapy or vasopressors, will be used to identify those who develop Persistent Critical Illness and to enable subsequent cluster analysis of their clinical trajectories.
Time frame: The first 10 days in the ICU
All cause mortality stratified by Persistent Critical Illness (PCI) clusters
Clinical outcomes will be assessed and reported according to clusters of Persistent Critical Illness (PCI) identified using unsupervised machine learning analysis at Day 10 of ICU stay. Outcome includes: • All-cause mortality, reported as the proportion of participants who die during hospitalization and up to 1 year after cluster identification.
Time frame: From cluster identification (Day 10) until hospital discharge or up to 1-year follow-up if available.
Organ dysfunction stratified by Persistent Critical Illness
Clinical outcomes will be assessed and reported according to clusters of Persistent Critical Illness (PCI) identified using unsupervised machine learning analysis at Day 10 of ICU stay. Outcome includes: • Organ dysfunction, assessed using the Sequential Organ Failure Assessment (SOFA) score, reported as mean (± SD) or median (IQR) values after cluster identification.
Time frame: From cluster identification (Day 10) until hospital discharge or up to 1-year follow-up if available.
ICU mortality
Death occurring at any time during the ICU stay.
Time frame: Through ICU stay (up to 1 year).
Hospital mortality
Death occurring at any time during the hospital admission.
Time frame: Through hospital stay (up to 2 years).
ICU length of stay
Total number of calendar days from ICU admission to ICU discharge.
Time frame: Through ICU stay (up to 1 year).
Incidence of ICU-acquired infections
Number of clinically or microbiologically documented infections acquired ≥48 hours after ICU admission.
Time frame: Through ICU stay (up to 1 year).
Hemoglobin trajectory
Longitudinal assessment of hemoglobin levels using repeated measurements obtained during the intensive care unit (ICU) stay.
Time frame: Through ICU stay (up to 1 year).
C-reactive protein (CRP) trajectory
Longitudinal assessment of C-reactive protein levels using repeated measurements obtained during the intensive care unit stay.
Time frame: Through ICU stay (up to 1 year).
Creatinine trajectory
Longitudinal assessment of creatinine levels using repeated measurements obtained during the intensive care unit stay.
Time frame: Through ICU stay (up to 1 year).
Albumin trajectory
Longitudinal assessment of albumin levels using repeated measurements obtained during the intensive care unit stay.
Time frame: Through ICU stay (up to 1 year).
Lactate trajectory
Longitudinal assessment of lactate levels using repeated measurements obtained during the intensive care unit stay.
Time frame: Through ICU stay (up to 1 year).
Plan to share: Yes — Individual participant data collected in this study will be made available to other researchers. All data will undergo a thorough anonymization process prior to sharing to prevent direct or indirect identification of participants. Each patient will be assigned an internal numeric code, consisting of two digits representing the center of origin and four sequential digits assigned by order of admission. No personal identifiers (e.g., name, national ID number, full date of birth, address) are collected. The anonymized dataset will be accompanied by a data dictionary, describing each variable and its format, to allow full interpretation and reuse of the data. This approach ensures participant confidentiality and complies with ethical and legal requirements, while enabling secondary analyses, replication studies, or meta-analyses by other researchers.
Supporting information: Study protocol, Sap
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Lisbon Academic Medical Center - Centro Académico de Medicina de Lisboa