AI and iron levels help predict which cancer patients will survive the ICU
NCT ID NCT07408661
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study looked at over 1,100 critically ill cancer patients in the ICU to see if iron levels in the blood could help predict who would survive for 30 days. Researchers used artificial intelligence to combine iron markers with other routine lab results. The goal was to create a more accurate prediction tool, not to test a new treatment.
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Study facts
What this study's own registry entry says, in plain language.
- Participants
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1,137 people
The number who actually took part.
- Started
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Jan 2015
- Finished
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Dec 2025
- Lead sponsor
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Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
The study population consists of adult cancer patients who were critically ill, requiring intensive care unit admission. This retrospective cohort is derived from the MIMIC-IV database, comprising patients with a cancer diagnosis who had their first ICU stay during hospitalization and for whom complete data on the key predictors and outcome are available.
- Ages
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18 to 100 years
- Sex
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Anyone
- Healthy volunteers
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Not accepted
This study is not open to healthy volunteers. The entry requirements below say who it is open to.
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Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
Inclusion Criteria: 1. Adult patients (age ≥ 18 years). 2. Diagnosis of any type of cancer, as recorded in the hospital database. 3. First ICU admission during the hospital stay (only the first ICU stay is considered for patients with multiple admissions). Exclusion Criteria: 1. Length of ICU stay less than 24 hours. 2. Missing or unavailable data for the key study variables, specifically iron metabolism markers (ferritin, serum iron, total iron-binding capacity) or essential clinical parameters needed for analysis.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
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Other studies related to the condition(s) this trial covers.
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