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Mortality and Renal Impairment in Critically Ill Patients across world regions over 2007 to 2024: a nutritionDay descriptive multivariable analysis

This large international multivariable analysis of over 23,000 critically ill patients from 2007 to 2024 identifies renal replacement therapy, advanced age, and illness severity as the strongest independent predictors of 60-day hospital mortality, while highlighting that the association between renal impairment and outcomes varies significantly based on the underlying disease causing ICU admission.

Original authors: Arabella Fischer-Hammerschmied, Peter Bauer, Fiona Trumshi, Silvia Tarantino, Emir Softic, Christian Schuh, Sylvia Ryz, Martin H. Bernardi, Andrea Lassnigg, Johanna Tichy, Sarah Yadavalli, Anna Schran
Published 2026-06-28
📖 5 min read🧠 Deep dive

Original authors: Arabella Fischer-Hammerschmied, Peter Bauer, Fiona Trumshi, Silvia Tarantino, Emir Softic, Christian Schuh, Sylvia Ryz, Martin H. Bernardi, Andrea Lassnigg, Johanna Tichy, Sarah Yadavalli, Anna Schranz, Michael Hiesmayr

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the Intensive Care Unit (ICU) as a massive, global "hospital hotel" where critically ill guests stay. Every year, researchers from the nutritionDay project send out a team of auditors to take a snapshot of every single guest in these hotels on a specific day in November. They aren't just checking if the beds are clean; they are checking the guests' vital signs, their history, and how the hotel staff is treating them.

This paper is the report card from that global audit, covering 23,485 adult patients across 60 countries over a 17-year period (2007–2024). The researchers wanted to answer one big question: How does kidney trouble affect the chances of a patient surviving their stay?

Here is the breakdown of their findings, using simple analogies:

1. The Three Kidney "Checkpoints"

To understand kidney health, the researchers didn't just look at one thing. They used three different tools, like checking a car engine in three ways:

  • Creatinine: A chemical in the blood. If it's too high, it's like the exhaust pipe is clogged.
  • Urine Volume: How much "waste water" the kidneys are pumping out.
  • Renal Replacement Therapy (RRT): This is the "emergency tow truck." It's a machine (dialysis) that does the kidneys' job for them when they completely stop working.

2. The Big Findings: What Kills the Most?

The researchers ran a complex math model (a "recipe" to predict outcomes) to see what factors were the strongest predictors of death within 60 days.

  • The "Tow Truck" (RRT) is a Double-Edged Sword:
    Being on the RRT machine was the strongest link to higher death rates. However, the paper explains this isn't just because the machine is dangerous. It's because needing the machine means your kidneys have already failed. It's like a firefighter arriving at a house fire; the firefighter didn't burn the house down, but their presence means the fire was already raging.

    • Crucial Detail: The risk of death while on the machine depended heavily on why the patient was in the hospital. For example, patients admitted for abdominal issues who needed the machine had a much higher risk of death than those admitted for other reasons.
  • The Age Factor:
    Age is a heavy backpack. Patients over 90 had double the risk of death compared to those in their 60s. Interestingly, the use of the "tow truck" (RRT) was steady until age 70, but then it actually dropped for the oldest patients. The researchers suggest doctors might be less likely to use the machine on the very elderly, perhaps due to the overall frailty of the patient.

  • The "Why" Matters More Than the "What":
    The reason a patient was admitted to the ICU was a huge predictor.

    • High Risk: Patients admitted for brain issues (neurologic), lung problems (pulmonary), or severe infections (sepsis) had higher death rates.
    • Lower Risk: Patients admitted for heart issues or trauma (accidents) had lower death rates, even when adjusting for how sick they were.
  • The "Goldilocks" Weight (BMI):
    Body weight showed a "U-shaped" curve. Being too thin or too heavy increased the risk of death. The "sweet spot" (lowest risk) was for patients with a BMI between 25 and 35. It's like a car: too light and it's unstable; too heavy and the engine struggles. The middle weight was the safest.

  • The "Hotel Stay" Length:
    The longer a patient had already been in the ICU by the time the audit happened, the higher the risk of death. It's like a marathon runner who is already exhausted; the longer they've been running, the harder it is to finish.

3. What About the "Global" Differences?

The study looked at different parts of the world (Europe, North America, Latin America, Asia).

  • North America had the lowest death rates in the study.
  • Latin America had the highest.
  • However, the rules of the game (how age, weight, and kidney failure affect death) were generally the same everywhere. The geography didn't change the biology, even if the outcomes varied.

4. The "Secret Sauce" of the Study

Most previous studies only looked at whether a patient was on a machine or not. This study was unique because it looked at the whole picture:

  • They looked at the blood chemicals (creatinine).
  • They looked at the urine output.
  • They looked at the machine (RRT).
  • They adjusted for the patient's age, weight, and how sick they were before they even got to the ICU.

The Bottom Line

The paper concludes that kidney failure (indicated by the need for the machine), old age, and the severity of the illness are the three biggest drivers of death in the ICU.

The "tow truck" (RRT) is a sign that the kidneys have given up. While it saves lives, the fact that a patient needs it is a very strong warning sign that the patient is in critical danger. The study emphasizes that you cannot look at kidney failure in isolation; you have to look at the whole patient, their age, their weight, and the specific disease that brought them to the hospital to understand their true risk.

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