Evaluation of anxiety and depression among patients recovered from acute kidney injury
Bibliographic record
Abstract
Abstract Background Acute kidney injury (AKI) is a common clinical condition with high morbidity and mortality. This research aims to assess depression, anxiety, cognitive function, and quality of life (QoL) in patients recovered from AKI and examine their association with recovery status and clinical outcomes. Methods This prospective cohort study included 53 AKI patients and 53 age- and sex-matched healthy controls. Psychiatric assessments included the Hamilton Anxiety Rating Scale (HARS), Hamilton Depression Rating Scale (HAM-D), and Generalized Anxiety Disorder-7 (GAD-7). Cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA), and health-related QoL with the SF-36 questionnaire. Assessments were performed at baseline, 3, and 6 months. Results AKI patients demonstrated significantly elevated HARS, HAM-D, and GAD-7 scores than controls at baseline, 3, and 6 months (all p < 0.001), with progressive worsening during follow-up. QoL scores were significantly diminished in AKI patients as opposed to controls at all time points (baseline: 61.6 ± 6.2 vs. 72.7 ± 8.5; 6 months: 48.3 ± 5.3 vs. 77.4 ± 6.7; p < 0.001). MoCA scores were also reduced in AKI patients (19.1 ± 3.8 vs. 21.1 ± 4.0; p = 0.013). Anxiety and depression correlated with ICU stay, number of dialysis sessions, and serum creatinine, while QoL inversely correlated with age ( r =-0.40, p = 0.003). Patients with incomplete recovery or dialysis dependence had significantly elevated anxiety and depression scores. Conclusions AKI survivors experience persistent psychological distress, cognitive impairment, and reduced QoL, particularly in those with incomplete renal recovery. Early psychiatric assessment and targeted interventions should be integrated into post-AKI care.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".