Prevalence of preoperative anemia, abnormal mean corpuscular volume and red cell distribution width among surgical patients in Singapore, and their influence on one year mortality

Abstract

IntroductionPreoperative anemia and high red cell distribution width (RDW) are associated with higher perioperative mortality. Conditions with high RDW levels can be categorized by mean corpuscular volume (MCV). The relationship between RDW, anemia and MCV may explain causality between high RDW levels and outcomes. We aim to establish the prevalence of preoperative anemia and distribution of RDW and MCV among pre-surgical patients in Singapore. In addition, we aim to investigate the association between preoperative anemia, RDW and MCV levels with one-year mortality after surgery.MethodsRetrospective review of 97,443 patients aged > = 18 years who underwent cardiac and non-cardiac surgeries under anesthesia between January 2012 and October 2016. Patient demographics, comorbidities, priority of surgery, surgical risk classification, perioperative transfusion, preoperative hemoglobin, RDW, MCV were collected. WHO anemia classification was used. High RDW was defined as >15.7%. Multivariate regression analyses were done to identify independent risk factors for mild or moderate/severe anemia and high RDW (>15.7). Multivariate cox regression analysis was done to determine the effect of preoperative anemia, abnormal RDW and MCV values on 1-year mortality.ResultsOur cohort comprised of 94.7% non-cardiac and 5.3% cardiac surgeries. 88.7% of patients achieved 1 year follow-up. Anemia prevalence was 27.8%—mild anemia 15.3%, moderate anemia 12.0% and severe anemia 0.5%. One-year mortality was 3.5%. Anemia increased with age in males, while in females, anemia was more prevalent between 18–49 years and > = 70 years. Most anemics were normocytic. Normocytosis and macrocytosis increased with age, while microcytosis decreased with age. Older age, male gender, higher ASA-PS score, anemia (mild- aHR 1.98; moderate/severe aHR 2.86), macrocytosis (aHR 1.47), high RDW (aHR 2.34), moderate-high risk surgery and emergency surgery were associated with higher hazard ratios of one-year mortality.DiscussionPreoperative anemia is common. Anemia, macrocytosis and high RDW increases one year mortality.

Distribution of hemoglobin levels and prevalence of anemia according to sex, age group, and region in 13 Korean cities

“…Sex differences in the prevalence of anemia across different age groups were also found, with the prevalence being higher in females than in males aged <70 years, which reversed in those aged ≥70 years. This trend among those aged ≥70 years has also been demonstrated in other studies, 8,16 in which age was associated with both Hb and anemia and with a stronger effect in males than in females and an even higher prevalence of anemia in males aged 71-74 years.…”

“…Several studies of the prevalence of anemia have been reported, but large‐scale general population‐based study are rare. Moreover, there are regional variations in anemia prevalence due to differences in race, diet, endemic diseases, and epigenetic influences .…”

Atopic Disease and Anemia in Korean Patients: Cross-Sectional Study with Propensity Score Analysis

“…In children, anemia is associated with reduced quality of life and cognitive abnormalities [3,4]. Anemia is also associated with increased post-operative mortality in adults and overall mortality in older adults [5,6]. Atopic diseases such as atopic dermatitis, allergic rhinitis, and asthma also have a high and increasing prevalence in the general population [7,8], and they have been associated with other medical conditions, such as rheumatoid arthritis, inflammatory bowel disease, and anxiety or depression [9][10][11].…”

Estimated Glomerular Filtration Rate and Postoperative Mortality in Patients Undergoing Non-Cardiac Surgery: A Single-Center Retrospective Study.

“…Based on analytical principles mentioned above, univariate and multiple linear regression models were used to assess relationships with preop-eGFR and postoperative thirty-day mortality. Three models(an unadjusted model, a demographically adjusted model, and a fully-adjusted model) were constructed according to the STROBE statement [24].As for the fully-adjusted model, those adjusted variables, reported in previous studies, are related covariates that may affect preop-eGFR and/or thirty-day mortality [22] [20].Moreover, subgroup analyses were performed by stratified linear regression models. Subgroup interaction test was performed to verity the effect modification by subgroup and then a likelihood ratio test was conducted.…”

“…Variables of the database file included: demographic information; preoperative comorbidities;preoperative laboratory perioperative blood transfusion data; anesthesia type ;priority of surgery ; surgical risk classification( based on the 2014 ESC/ESA guidelines on non-cardiac surgery [18] [19]);and postoperative thirty-day prognosis. Preoperative comorbidities were consist of anemia,CKD, and medical history [cerebrovascular accidents (CVA), ischemic heart disease (IHD), congestive heart failure (CHF),type1 diabetes].Those medical histories mentioned above were also associated with Revised Cardiac Risk Index (RCRI) score [17].The latest results of preoperative laboratory test were mainly about eGFR, red blood cell distribution width (RDW)(Levels above 15.7% were defined as high RDW ,as the normal reference range was 10.9-15.7% [22]), hemoglobin.We listed in detail the covariates used in this study. In short, their reasons for inclusion included as follows: (1) demographic data; (2) variables that can affect preop-eGFR or thirty-day mortality reported by previous literature [20]; (4) based on our clinical experiences.…”