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Preoperative Red Cell Distribution Width and 30-day mortality in older patients undergoing non-cardiac surgery: a retrospective cohort observational study.

ABSTRACT: Increased red cell distribution width (RDW) is associated with poorer outcomes in various patient populations. We investigated the association between preoperative RDW and anaemia on 30-day postoperative mortality among elderly patients undergoing non-cardiac surgery. Medical records of 24,579 patients aged 65 and older who underwent surgery under anaesthesia between 1 January 2012 and 31 October 2016 were retrospectively analysed. Patients who died within 30 days had higher median RDW (15.0%) than those who were alive (13.4%). Based on multivariate logistic regression, in our cohort of elderly patients undergoing non-cardiac surgery, moderate/severe preoperative anaemia (aOR 1.61, p?=?0.04) and high preoperative RDW levels in the 3rd quartile (>13.4% and ?14.3%) and 4th quartile (>14.3%) were significantly associated with increased odds of 30-day mortality - (aOR 2.12, p?=?0.02) and (aOR 2.85, p?=?0.001) respectively, after adjusting for the effects of transfusion, surgical severity, priority of surgery, and comorbidities. Patients with high RDW, defined as >15.7% (90th centile), and preoperative anaemia have higher odds of 30-day mortality compared to patients with anaemia and normal RDW. Thus, preoperative RDW independently increases risk of 30-day postoperative mortality, and future risk stratification strategies should include RDW as a factor.

SUBMITTER: Abdullah HR

PROVIDER: S-EPMC5906451 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Preoperative Red Cell Distribution Width and 30-day mortality in older patients undergoing non-cardiac surgery: a retrospective cohort observational study.

Abdullah H R HR Sim Y E YE Sim Y T YT Ang A L AL Chan Y H YH Richards T T Ong B C BC

Scientific reports 20180418 1

Increased red cell distribution width (RDW) is associated with poorer outcomes in various patient populations. We investigated the association between preoperative RDW and anaemia on 30-day postoperative mortality among elderly patients undergoing non-cardiac surgery. Medical records of 24,579 patients aged 65 and older who underwent surgery under anaesthesia between 1 January 2012 and 31 October 2016 were retrospectively analysed. Patients who died within 30 days had higher median RDW (15.0%) t ...[more]

PMID: 29670189

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Project description:BackgroundEpidemiological studies have demonstrated an association between red blood cell distribution width (RDW) and the prognosis of pneumonia-associated diseases. However, prognostic value of RDW in patients with ventilator-associated pneumonia (VAP) has yet to be investigated. This study aimed to explore the association between RDW and in-hospital mortality in VAP patients and explore predictive value of RDW for VAP patients.MethodsThis retrospective cohort study included 1,543 VAP patients from the Medical Information Mart for Intensive Care IV database 2008-2019. The primary outcome was considered to 30-day in-hospital mortality of VAP patients in this study. Non-high RDW level group was defined as <15 %, and high RDW level group as ≥15%. The possible confounding factors were screened by least absolute shrinkage and selection operator regression. Univariate and multivariate COX regression analyses were used for the assessment on the association of RDW and 30-day in-hospital mortality in VAP patients. We also performed subgroup analyses. Furthermore, a comparative analysis of RDW and sequential organ failure assessment (SOFA) score and simplified acute physiology score II (SAPS II) were performed by receiver operating characteristic (ROC) curves.ResultsThe 30-day in-hospital mortality of VAP patients was approximately 19.05%. After adjusting all confounding factors, high RDW was associated with 30-day in-hospital mortality among VAP patients by using non-high RDW as the reference [hazard ratio (HR) =1.29, 95% confidence interval (CI): 1.01-1.63]. Additionally, the relationship was also robust in several populations, such as patients were younger than 60 years, or had not a history of congestive heart failure, or had a history of sepsis, or had not received renal replacement therapy, or had a duration of mechanical ventilation for more than 7 days. The result of ROC indicated that RDW had a better prognostic value in predicting 30-day in-hospital mortality for VAP patients than SOFA score and SAPS II score.ConclusionHigh RDW level is associated with an increased 30-day in-hospital mortality. The RDW is a promising biomarker in predicting 30-day in-hospital mortality for patients admitted to the ICU, regardless of VAP.

Project description:Importance:Although wait times for hip fracture surgery have been linked to mortality and are being used as quality-of-care indicators worldwide, controversy exists about the duration of the wait that leads to complications. Objective:To use population-based wait-time data to identify the optimal time window in which to conduct hip fracture surgery before the risk of complications increases. Design, Setting, and Participants:Population-based, retrospective cohort study of adults undergoing hip fracture surgery between April 1, 2009, and March 31, 2014, at 72 hospitals in Ontario, Canada. Risk-adjusted restricted cubic splines modeled the probability of each complication according to wait time. The inflection point (in hours) when complications began to increase was used to define early and delayed surgery. To evaluate the robustness of this definition, outcomes among propensity-score matched early and delayed surgical patients were compared using percent absolute risk differences (RDs, with 95% CIs). Exposure:Time elapsed from hospital arrival to surgery (in hours). Main Outcomes and Measures:Mortality within 30 days. Secondary outcomes included a composite of mortality or other medical complications (myocardial infarction, deep vein thrombosis, pulmonary embolism, and pneumonia). Results:Among 42 230 patients with hip fracture (mean [SD] age, 80.1 years [10.7], 70.5% women) who met study entry criteria, overall mortality at 30 days was 7.0%. The risk of complications increased when wait times were greater than 24 hours, irrespective of the complication considered. Compared with 13 731 propensity-score matched patients who received surgery earlier, 13 731 patients who received surgery after 24 hours had a significantly higher risk of 30-day mortality (898 [6.5%] vs 790 [5.8%]; % absolute RD, 0.79; 95% CI, 0.23-1.35) and the composite outcome (1680 [12.2%]) vs 1383 [10.1%]; % absolute RD, 2.16; 95% CI, 1.43-2.89). Conclusions and Relevance:Among adults undergoing hip fracture surgery, increased wait time was associated with a greater risk of 30-day mortality and other complications. A wait time of 24 hours may represent a threshold defining higher risk.

Project description:ImportanceQuality improvement programs for colorectal cancer surgery have been introduced with benchmarking based on quality indicators, such as mortality. Detailed (pre)operative characteristics may offer relevant information for proper case-mix correction.ObjectiveTo investigate the added value of machine learning to predict quality indicators for colorectal cancer surgery and identify previously unrecognized predictors of 30-day mortality based on a large, nationwide colorectal cancer registry that collected extensive data on comorbidities.Design, setting, and participantsAll patients who underwent resection for primary colorectal cancer registered in the Dutch ColoRectal Audit between January 1, 2011, and December 31, 2016, were included. Multiple machine learning models (multivariable logistic regression, elastic net regression, support vector machine, random forest, and gradient boosting) were made to predict quality indicators. Model performance was compared with conventionally used scores. Risk factors were identified by logistic regression analyses and Shapley additive explanations (ie, SHAP values). Statistical analysis was performed between March 1 and September 30, 2020.Main outcomes and measuresThe primary outcome of this cohort study was 30-day mortality. Prediction models were trained on a training set by performing 5-fold cross-validation, and outcomes were measured by the area under the receiver operating characteristic curve on the test set. Machine learning was further used to identify risk factors, measured by odds ratios and SHAP values.ResultsThis cohort study included 62 501 records, most patients were male (35 116 [56.2%]), were aged 61 to 80 years (41 560 [66.5%]), and had an American Society of Anesthesiology score of II (35 679 [57.1%]). A 30-day mortality rate of 2.7% (n = 1693) was found. The area under the curve of the best machine learning model for 30-day mortality (0.82; 95% CI, 0.79-0.85) was significantly higher than the American Society of Anesthesiology score (0.74; 95% CI, 0.71-0.77; P < .001), Charlson Comorbidity Index (0.66; 95% CI, 0.63-0.70; P < .001), and preoperative score to predict postoperative mortality (0.73; 95% CI, 0.70-0.77; P < .001). Hypertension, myocardial infarction, chronic obstructive pulmonary disease, and asthma were comorbidities with a high risk for increased mortality. Machine learning identified specific risk factors for a complicated course, intensive care unit admission, prolonged hospital stay, and readmission. Laparoscopic surgery was associated with a decreased risk for all adverse outcomes.Conclusions and relevanceThis study found that machine learning methods outperformed conventional scores to predict 30-day mortality after colorectal cancer surgery, identified specific patient groups at risk for adverse outcomes, and provided directions to optimize benchmarking in clinical audits.

Dataset Information

Preoperative Red Cell Distribution Width and 30-day mortality in older patients undergoing non-cardiac surgery: a retrospective cohort observational study.

Publications

Preoperative Red Cell Distribution Width and 30-day mortality in older patients undergoing non-cardiac surgery: a retrospective cohort observational study.

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