Frequency of Acute Kidney Injury in Patients Admitted With Acute Stroke at Hayatabad Medical Complex, Peshawar
Bibliographic record
Abstract
Background Patients hospitalized with acute stroke are at risk of developing acute kidney injury (AKI), and when both conditions occur together, patient outcomes are often worse. The relationship between stroke type, patient characteristics, and the development of AKI is not fully understood, particularly in tertiary care settings in Pakistan, where healthcare resources and patient characteristics may differ from Western populations. Objective To determine the frequency of AKI and identify associated risk factors, including stroke type, severity, and comorbidities, in patients presenting with acute stroke at a tertiary care center in Pakistan, the Hayatabad Medical Complex, Peshawar. Methods This cross-sectional study was conducted at Hayatabad Medical Complex, Peshawar, from February to July 2023. A total of 214 patients with acute stroke were enrolled through non-probability consecutive sampling. AKI was defined using Kidney Disease Improving Global Outcomes (KDIGO) criteria as an increase in serum creatinine by ≥0.3 mg/dL within 48 hours or ≥1.5 times baseline within seven days. Chi-square tests and multivariate logistic regression were used for statistical analysis using IBM SPSS Statistics, Version 23 (IBM Corp., Armonk, NY, USA). Results Among 214 stroke patients (mean age 53.08±7.52 years, 59.8% male), AKI occurred in 33 patients (15.4%, 95% CI: 10.8-20.9). Ischemic strokes (n=147, 68.7%) showed lower AKI prevalence compared to hemorrhagic strokes (10.2% vs 26.9%, p<0.005). AKI occurred in all severe stroke cases (26/26, 100%) but none in mild (0/12) or moderate (0/149) cases (p<0.001). Comorbidity distribution showed isolated hypertension in 9.3%, diabetes in 38.3%, and both conditions in 52.3% of patients. Mean baseline creatinine was 0.98±0.24 mg/dL, with peak levels of 1.42±0.38 mg/dL in the AKI group. Conclusions In our tertiary care setting, AKI occurred in 15.4% of acute stroke patients, with significantly higher rates of hemorrhagic strokes and severe cases. While hypertension and diabetes were common comorbidities, stroke type and severity were stronger predictors of AKI development. These findings suggest the need for targeted monitoring strategies, particularly in patients with hemorrhagic or severe strokes, to facilitate early detection and management of AKI in acute stroke settings.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".