Dataset Information

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

ABSTRACT:

Background

Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery.

Methods

This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation.

Results

A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65).

Discussion

Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability.

SUBMITTER: STARSurg Collaborative

PROVIDER: S-EPMC6254006 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

BJS open 20180727 6

<h4>Background</h4>Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery.<h4>Methods</h4>This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gas ...[more]

PMID: 30513129

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Project description:BackgroundThe association between malnutrition and postoperative acute kidney injury (AKI) has not been well studied. In this study, the authors examined the association between preoperative nutritional status and postoperative AKI in older patients who underwent major abdominal surgery, as well as the predictive value of malnutrition for AKI.Materials and methodsThe authors retrospectively included patients aged 65 or older who underwent major elective abdominal surgery. The nutritional status of the patient was evaluated using three objective nutritional indices, such as the geriatric nutritional risk index (GNRI), the prognostic nutritional index (PNI), and the controlling nutritional status (CONUT). AKI was determined using the KDIGO criteria. The authors performed logistic regression analysis to investigate the association between preoperative nutritional status and postoperative AKI, as well as the predictive value of nutritional scores for postoperative AKI.ResultsA total of 2775 patients were included in the study, of which 707 (25.5%), 291 (10.5%), and 517 (18.6%) had moderate to severe malnutrition according to GNRI, PNI, and CONUT calculations. After surgery, 144 (5.2%) patients developed AKI, 86.1% at stage 1, 11.1% at stage 2, and 2.8% at stage 3 as determined by KDIGO criteria. After adjustment for traditional risk factors, worse nutritional scores were associated with a higher AKI risk. In addition to traditional risk factors, these nutritional indices improved the predictive ability of AKI prediction models, as demonstrated by significant improvements in integrated discrimination and net reclassification.ConclusionsPoor preoperative nutritional status, as assessed by GNRI, PNI, and CONUT scores, was associated with an increased risk of postoperative AKI. Incorporating these scores into AKI prediction models improved their performance. These findings emphasize the need for screening surgical patients for malnutrition risk. Further research is needed to determine whether preoperative malnutrition assessment and intervention can reduce postoperative AKI incidence.

Project description:Delirium is a common, morbid, and costly postoperative complication. We aimed to identify blood-based postoperative delirium markers in a nested case-control study of older surgical patients using a proteomics approach followed by enzyme-linked immunosorbent assay (ELISA) validation.The Successful Aging after Elective Surgery study enrolled dementia-free adults ?70 years old undergoing major scheduled noncardiac surgery (N = 566; 24% delirium). Plasma was collected at four time points: preoperative, postanesthesia care unit, postoperative day 2, and 1 month postoperative. Matched pairs were selected for the independent discovery (39 pairs) and replication cohorts (36 pairs), which were subsequently combined into the pooled cohort (75 pairs). Isobaric tags for relative and absolute quantitation-based relative quantitation mass spectrometry proteomics were performed to identify the strongest delirium-related protein, which was selected for ELISA validation. Using the ELISA results, statistical analyses using nonparametric signed rank tests were performed in all cohorts examining the association between the identified protein and delirium.C-reactive protein emerged from the proteomics analysis as the strongest delirium-related protein. Validation by ELISA confirmed that compared with controls, cases had significantly higher C-reactive protein levels in the discovery, replication, and pooled cohorts at the preoperative (median paired difference [MPD] 1.97 mg/L [p < .05], 0.29 mg/L, 1.56 mg/L [p < .01]), postanesthesia care unit (MPD 2.83 mg/L, 2.22 mg/L [p < .05], 2.53 mg/L [p < .01]) and postoperative day 2 (MPD 71.97 mg/L [p < .01], 35.18 mg/L [p < .05], 63.76 mg/L [p < .01]) time points, but not 1 month postoperative (MPD 2.72 mg/L, -0.66 mg/L, 1.10 mg/L).Elevated preoperative and postoperative plasma levels of C-reactive protein were associated with delirium, suggesting that a preinflammatory state and heightened inflammatory response to surgery are potential pathophysiologic mechanisms of delirium.

Dataset Information

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background

Methods

Results

Discussion

Publications

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Similar Datasets

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