FOCUSED REVIEW ON NUTRITIONAL STATUS OF PATIENTS WITH IMMUNOGLOBULIN LIGHT CHAIN AMYLOIDOSIS
Bibliographic record
Abstract
ABSTRACT Background Immunoglobulin light chain (AL) amyloidosis is a complex disease marked by a poor clinical portrait and prognosis generally leading to organ dysfunction and shortened survival. We aimed to review the available evidence on whether AL amyloidosis can lead to malnutrition, thus having a negative impact on quality of life (QoL) and survival. Materials We searched Pubmed with no restrictions to the year of publication or language. Retrospective or prospective, observational, and interventional studies that reported data regarding AL amyloidosis and nutritional status were included. Results From 62 articles retrieved, 23 were included. Malnutrition was prevalent in up to 65% of patients with AL Amyloidosis. Prevalence of weight loss of 10% or more ranged from 6 to 22% of patients, while a body mass index of < 22 kg/m2 was found in 22 to 42%. Weight loss, lower BMI and other indicators of poor nutritional status were negatively associated with quality of life and survival. Only one RCT focused on nutritional counseling was found and reported positive results on patients QoL and survival. Conclusion Despite inconsistencies across assessment criteria, the available data reveal that weight loss and malnutrition are common features in patients with AL amyloidosis. This review reinforces the premise that an impaired nutritional status can be negatively associated with QoL and survival in patients with AL amyloidosis, and therefore should be further investigated.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".