Perspectives and Experiences of Patients with AKI
Bibliographic record
Abstract
Key Points Six themes have been identified reflecting the perspectives and experiences of adults with AKI. Patients are unaware of AKI diagnosis and prognosis, feel that care is fragmented, and are burdened by treatment. Providing education, reducing treatment burden, and ensuring excellence in care may help to address patients' needs and improve AKI management. Background AKI is associated with higher risk of mortality and progression to CKD. The challenges and uncertainty in the diagnosis, self-management, and prevention of AKI can be distressing for patients. We aimed to perform a systematic review of qualitative studies/surveys that reported the perspectives and experiences of adults with AKI. Methods We searched MEDLINE, Embase, PsycINFO, and CINAHL from inception to January 17, 2024. Thematic textual analysis was used to synthesize the findings. Results We included 20 studies (ten qualitative studies, ten surveys) involving 867 participants. We identified six themes: navigating the unknown (an unexpected and unfamiliar diagnosis, tossed about in a fragmented system, and dismissed and vulnerable at discharge); impaired life participation, relationships, and well-being (limiting ability to do daily activities and straining relationships); unbearable and unsustainable treatment burden (adding strain on family members, financial pressure because of medical expenses, and cumulative stress of ongoing monitoring); uncertain whether recovery is attainable (possible permanence of kidney damage, fear about nephrotoxic medications, and terrified about the need for dialysis); less consequential than other health priorities (short term and reversible and prioritizing other comorbidities and conditions); and empowered in managing own health (focusing on optimizing kidney health, gaining confidence in self-management, and reassured with social and clinical support). Conclusions Patients may be unaware of their AKI diagnosis and prognosis, feel that care is fragmented, and be burdened by treatment. Providing education, alleviating treatment burden, and implementing a comprehensive model of care may help to address the needs of patients with AKI leading to better outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".