Onconephrology, an Essential Subspecialty: Experience of a University Hospital Center
Bibliographic record
Abstract
Background: Kidney complications of cancer patients and cancer in renal patients have increased in recent years. This study evaluates the characteristics of the patients referred to the Onco-Nephrology Unit from January 2021 to December 2021, studying the cognitive and mood status of these patients. Methods: This is a prospective observational study of the Onco-Nephrology consultation at our hospital during 2021. Clinical and analytical characteristics of the patients and clinical indication for referral were analyzed. In addition, sleep quality, mood and cognitive status were assessed using validated rating scales(Epsworth, Geriatric Depression Scale and Montreal). Results: Seventy-four patients were evaluated, mean age was 69.6(±11) years, 41(55.4%) men, 47(63.5%) had hypertension, 18(24.3%) diabetics, and 11(14.9%) were affected by heart disease. In addition, creatinine 1.93(±1.1)mg/dl, eGFR 39.97(±20.3) mL/min, proteinuria 187[29-515.9]mg/g, and 4(5.4%) had microhematuria. The most frequent cancers were intestinal, gynecological and mammary with 12.16%(n=9) each. 58.3%(n=42) of patients had metastatic disease. 48.7%(n=36) received chemotherapy and 58.1%(n=43) targeted therapies. Platinum was the most frequently used chemotherapy and anti-VEGF in terms of targeted therapies. The most frequent clinical indication for referral was acute renal failure(n=36;48.7%). Rating scales were obtained in 51 patients: 49%(n=25) were snorers, followed by 17.6%(n=9) with insomnia and 11.8%(n=6) with OSAS. 27 patients(36.5%) had cognitive impairment. Mild depression was detected in 13 cases(25.5%) and moderate depression in 11.6%(n=6). 21 renal biopsies were performed, the most frequent diagnosis was acute interstitial nephritis(71.4%, n=15) followed by thrombotic microangiopathy(19% n=4). A total of 15 patients(20.3%) died during the year. Conclusions: Most patients referred to Onco-Nephrology are affected by advanced oncological disease and consequently had a high mortality. The most frequent indication for referral was acute kidney injury(48.7%). Comprehensive patient care is important, given the prevalence of depressive syndrome. Onco-Nephrology is an example of a comprehensive and multidisciplinary approach to improve the survival and quality of life of patients with advanced cancer and renal disease.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".