Contrast induced nephropathy in patients of acute coronary syndrome with normal renal functions undergoing percutaneous coronary intervention
Bibliographic record
Abstract
Background: Contrast induced nephropathy is a well-known entity but it is less known that whether cardiac disease is a risk factor for this complication. Contrast induced nephropathy (CIN) is related with increase mortality and morbidity and the chances of this complication rises in patients who have coronary artery disease (CAD). Objective: The objective of the study is to identify the frequency of contrast induced nephropathy in patients undergoing percutaneous coronary intervention who have normal baseline renal functions. Material and methods: This cross sectional study conducted at angiography department of Punjab Institute of Cardiology, Lahore over a period of 2 years from January 2015 to January 2017. Patients regardless of gender with age of 30 - 65 years, diabetic or non-diabetics were included. Patients with renal disease or serum creatinine > 2 mg/dl at presentation or any other co-morbid medical illness, LV ejection fraction <30% were excluded from study. All the patients underwent coronary angioplasty. Renal function tests were checked 48 hours after procedure. The patients who had their creatinine level raised by 0.5mg/dl after 48hrs were labeled as sufferers of contrast induced nephropathy (CIN). RESULTS Results were compiled after studying the specific variables. Out of 5400 patients who underwent coronary angioplasty, 2988 (55.4%) patients were males & 2412 (44.6%) were females. Out of 5400 patients, 936 (17.33 %) suffered from CIN after PCI. Patients suffered from CIN when following volume of contrast was used: <100ml, 36 (3.84%) patients, 100-200 ml, 288 (30.7%) patients and >200ml, 612 (65.3%) patients. According to the age group following patients suffered from CIN: 30-40 years, 72 (8.6%) patients, 41-55 years, 288 (11.2 %) patients and 56-65 years 576 (28.5%) patients. Out of 2988 male patients, 324 (10.8 %) patients suffered from CIN (p=0.06). Similarly, out of 2412 females 612 (25.3 %) patients had CIN (p=0.05). In 936 patients suffering from CIN, 684(73.1%) patients were diabetic and 252 (26.9%) were non-diabetic. � Conclusion: There is a high frequency of contrast induced nephropathy in elderly and diabetic patients who undergo PCI even if they have normal preexisting renal functions, so this complication can be avoided by the minimum use of contrast during the procedure
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".