The Impact of Nutritional Status and Complete Blood Count Parameters on Clinical Outcome in Geriatric Critically Ill Patients
Bibliographic record
Abstract
BACKGROUND: The geriatric population in intensive care units (ICUs) has recently increased. The aim of this study was to analyse the impact of initial complete blood count (CBC)-related parameters and nutritional status on morbidity and mortality in geriatric ICU patients. METHODS: A retrospective analysis was made of geriatric patients admitted to our tertiary adult ICU for 1 year. Patients with a length of stay (LOS) of < 48 h, with hematological malignancy or age < 65 years age were excluded from the study. Initial albumin level was considered to reflect nutritional status. The prevelance and risk factors of mortality and microbiologically documented infection (MDI) were analysed. RESULTS: The study included a total of 243 patients with a mean age of 78.96 ± 6.62 years. The overall mortality rate was 40.7%. The most common cause for admission was acute respiratory failure and sepsis (17.2% vs. 16.8%). The most common MDI sources were lower respiratory tract, bloodstream, and urinary tract infections. Patients with thrombocytopenia on admission had a higher mortality rate than patients with normal platelet count (P = 0.019). The initial albumin level of non-survivors was significantly lower than that of survivors (P = 0.001). There was a significant negative correlation between albumin level and LOS (r = -0.157; P = 0.000). Patients with hypoalbuminemia (albumin < 3.2 g/dL) at the time of diagnosis had higher mortality, LOS and MDI rates than those with normal albumin levels (P < 0.05). There was no significant relationship between any other CBC-related parameter and infection and mortality (P > 0.05). CONCLUSIONS: Thrombocytopenia and hypoalbuminemia may be considered as major risk factors for morbidity and mortality in critically ill elderly patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".