Adult, Critical Illness, ICU
Conditions
Keywords
prealbumin, Critically Ill Patients, Prognosis
Brief summary
Nutritional support therapy is a crucial part of ICU patient care, as both malnutrition and overnutrition can lead to adverse clinical outcomes. Meticulous monitoring of nutritional support is essential. Unfortunately, to date, there are no biomarkers available to assess the appropriateness of nutritional support in the ICU setting. However, mounting evidence suggests that phenotypic analysis of patients using nutritional biomarkers or risk screening scores for adaptation may enhance our ability to characterize patients in terms of prognosis and likelihood of treatment response. This study aims to identify the trajectory patterns of prealbumin changes based on dynamic monitoring data of prealbumin during hospitalization of critically ill patients, and to analyze the Association between different trajectory groups and patient prognosis. In addition, this study will further analyze its Association with nutritional intake and nutritional indicators, thereby assessing the potential value of prealbumin change trajectories in terms of the adequacy and effectiveness of nutritional support for critically ill patients.
Detailed description
Elevated prealbumin is a good predictor of positive nitrogen balance. Compared to albumin's half-life of 19-21 days, prealbumin is advantageous in assessing short-term nutritional changes and has been widely recognized as a biomarker for nutritional status and recovery of eating ability. However, prealbumin levels vary considerably depending on patient characteristics, degree of inflammation, and stage of critical illness. In acute inflammation, infection, or trauma, prealbumin concentrations decrease due to various factors, including cytokine-induced downregulation of synthesis, extravasation into the vascular system, blood dilution, and increased consumption. Multiple studies have shown that prealbumin is associated with poor prognosis. Furthermore, the short half-life of prealbumin means that in the acute phase, PAB levels fluctuate over time. The trajectory of PAB level changes, rather than a single point, may provide a promising approach for dynamically assessing the adequacy and effectiveness of nutritional support in malnourished patients. This could help researchers more accurately describe and understand the heterogeneity and similarities within and between individual patients. Therefore, its dynamic changes may better reflect the severity of the patient's condition and the recovery of nutritional status. Previous studies have shown that for critically ill trauma patients, lower-than-normal total respiratory rate (TTR) levels upon admission are independently associated with poorer prognosis, while increased TTR levels over time are associated with better prognosis. Other studies have indicated that for every unit increase in CRP, TTR decreases by 0.024 units. This means that a 0.024-unit increase in CRP followed by a TTR decrease of more than 1 unit may be due to ineffective nutritional support. However, some researchers argue that prealbumin and the effectiveness of nutritional support are not related to outcome. Therefore, changes in prealbumin levels in the early stages of critical illness pose a diagnostic challenge in distinguishing between the resolution of inflammation, the adequacy of nutritional support, and the shift towards anabolism. This is an observational clinical study that will be conducted strictly in accordance with the STROBE guidelines. The first phase will utilize database analysis to track the dynamic trends of prealbumin levels, revealing the relationship between different trajectories and nutritional status and patient prognosis. The second phase will prospectively validate this study using similar patients treated at the Intensive Care Unit of Jilin University First Hospital, aiming to clarify the potential value of prealbumin in nutritional support and prognosis for critically ill patients.
Interventions
OTHERNo Intervention: Observational Cohort
No study-specific intervention is assigned. Participants receive usual clinical care as determined by the treating team
Sponsors
The First Hospital of Jilin University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. age \> 18 years, 2. SOFA score ≥ 2 3. at least three prealbumin data points within the previous 14 days.
Exclusion criteria
1. patients with liver failure 2. patients with kidney failure, 3. hereditary amyloidosis and Alzheimer's disease 4. long-term use of hormones or NSAIDs. -
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| ICU mortality | From ICU admission (Day 1) through ICU discharge or death, whichever occurs first (up to 28 days). | Death from any cause occurring during the index ICU stay |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| In-hospital mortality | From ICU admission (Day 1) through hospital discharge or death, whichever occurs first (up to 28 days). | Death from any cause occurring during the index hospitalization. |
| ICU-acquired infection | From ICU admission (Day 1) through ICU discharge or death, whichever occurs first (up to 28 days). | New-onset infection occurring during the ICU stay (not present or incubating at ICU admission), diagnosed according to prespecified clinical and/or microbiological criteria. |
| ICU length of stay | From ICU admission (Day 1) through ICU discharge or death, whichever occurs first (up to 28 days). | Number of days from ICU admission to ICU discharge (or death in ICU), calculated in days. |
| Ventilator-free days through Day 28 | 28 days after ICU admission | Number of days alive and free from invasive mechanical ventilation from ICU admission through Day 28; patients who die before Day 28 are assigned 0 ventilator-free days. |
| Vasopressor-free days during ICU stay | From ICU admission (Day 1) through ICU discharge or death, whichever occurs first (up to 28 days). | Vasopressor-free days, defined as the number of days alive and free of vasopressor therapy from ICU admission until ICU discharge; patients who die before ICU discharge are assigned 0 vasopressor-free days. |
| Survival time up to Day 28 | 28 days after ICU admission | Time from ICU admission to death from any cause; participants alive at Day 28 will be censored at Day 28 |
| Energy/Protein intake (weight-adjusted) | Days 1-14 after ICU admission. | Average daily delivered energy /Protein normalized to body weight (kcal or g/kg/day) from enteral and parenteral nutrition (and other calorie sources if captured) over ICU Days 1-14. |
| Longitudinal IL-6 levels during ICU Days 1-14 | During the first 14 days after ICU admission (ICU days 1-14). | Interleukin-6 (IL-6) concentration was measured daily (or as clinically obtained) from ICU Day 1 through Day 14; longitudinal change will be evaluated using repeated-measures analysis across ICU Days 1-14. |
| Longitudinal change in albumin during ICU Days 1-14 | During the first 14 days after ICU admission (ICU days 1-14). | Albumin was measured daily (or as clinically obtained) from ICU Day 1 through Day 14; longitudinal change will be evaluated using repeated-measures analysis across ICU Days 1-14. |
| Longitudinal change in CRP during ICU Days 1-14 | During the first 14 days after ICU admission (ICU days 1-14). | CRP was measured daily (or as clinically obtained) from ICU Day 1 through Day 14; longitudinal change will be evaluated using repeated-measures analysis across ICU Days 1-14. |
| Longitudinal lymphocyte count during ICU Days 1-14 | During the first 14 days after ICU admission (ICU days 1-14). | lymphocyte count was measured daily (or as clinically obtained) from ICU Day 1 through Day 14; longitudinal change will be evaluated using repeated-measures analysis across ICU Days 1-14. |
| Longitudinal change in White blood cell count during ICU Days 1-14 | During the first 14 days after ICU admission (ICU days 1-14). | White blood cell count was measured daily (or as clinically obtained) from ICU Day 1 through Day 14; longitudinal change will be evaluated using repeated-measures analysis across ICU Days 1-14. |
| Longitudinal change in neutrophil count during ICU Days 1-14 | During the first 14 days after ICU admission (ICU days 1-14). | Neutrophil count was measured daily (or as clinically obtained) from ICU Day 1 through Day 14; longitudinal change will be evaluated using repeated-measures analysis across ICU Days 1-14. |
| Creatinine longitudinal change in IL-6 during ICU Days 1-14 | During the first 14 days after ICU admission (ICU days 1-14). | Creatinine was measured daily (or as clinically obtained) from ICU Day 1 through Day 14; longitudinal change will be evaluated using repeated-measures analysis across ICU Days 1-14. |
| Blood urea nitrogen Longitudinal change in IL-6 during ICU Days 1-14 | During the first 14 days after ICU admission (ICU days 1-14). | Blood urea nitrogen was measured daily (or as clinically obtained) from ICU Day 1 through Day 14; longitudinal change will be evaluated using repeated-measures analysis across ICU Days 1-14. |
| BUN/prealbumin ratio | During the first 14 days after ICU admission (ICU days 1-14). | BUN/prealbumin ratio was measured daily (or as clinically obtained) from ICU Day 1 through Day 14; longitudinal change will be evaluated using repeated-measures analysis across ICU Days 1-14. |
Contacts
CONTACTYanhua Li
STUDY_CHAIRdong zhang
The First Hospital of Jilin University
Outcome results
None listed