This study showed that hig
h RDW was significantly associated with higher risks of postoperative 30-day mortality in non-cardiac surgery patients over 18 years of age compared to the non-high group. A number of statistical analyses confirmed this finding, including the doubly robust estimation method, the propensity score-based IPW model, the propensity score-based patient-matching model, the logistic regression based multivariate analysis model and the sensitivity analysis model. According to the study, an uncontrolled high RDW before surgery increased the risk of death rather than critical complications within 30 days of the surgery.
RDW is a well-known independent predictor of mortality and incidence rate in patients undergoing cardiac surgery (30–32). However, in non-cardiac surgery, the impact of RDW on postoperative mortality is still controversial. In a prospective observation of 229 patients undergoing high-risk gastrointestinal surgery, it was confirmed that RDW can predict postoperative mortality(OR RDW-SD = 1.21; P < 0.001, OR RDW-CV = 1.62; P = 0.01 (33). An analysis of non-cardiac surgery patients at the Icelandic National University Hospital was carried out in a retrospective cohort study, in accordance with the preoperative RDW (≤ 13.3%, 13.4–14.0%, 14.1–14.7%, 14.8–15.8%, and > 15.8%), patients were grouped into five predefined groups. All-cause long-term mortality was the primary outcome, with secondary outcomes including 30-day mortality, length of stay, and readmissions within 30 days compared with propensity score matching (PSM) cohort from patients with RDW ≤ 13.3%. Patients with RDW between 14.8% and 15.8%(HR = 1.33; 95%CI, 1.15–1.59; P < 0.001) and above 15.8%(HR = 1.66; 95% CI, 1.4–1.95; P < 0.001) had a higher hazard of mortality, compared with matched controls with RDW ≤ 13.3%. This is basically consistent with our research results. Domestic scholars's study also supports the above conclusion. A propensity matching analysis conducted by Kung-Chuan Cheng et al. (34) on 5315 patients with stage I-II colorectal cancer who underwent inpatient surgery at Chang Gung Memorial Hospital from 2001 to 2018 showed that high RDW remained a negative predictor of overall survival (OS) (HR = 1.49, 95% CI: 1.25–1.78) and disease-free survival (DFS) and cancer-specific survival (CSS) after early colorectal cancer radical surgery. In another study on gastric cancer patients undergoing radical surgery (35), it was found that a high preoperative RDW value was an important predictor of 60 day mortality (17.9 ± 4.3 vs 16.0 ± 3.2; P = 0.015). In patients with RDW ≥ 16%, the disease-free and overall survival rates of advanced gastric cancer decreased (P = 0.04). We found a significant association between RDW and postoperative mortality using the doubly robust estimation method in the propensity-score matched cohort. High RDW increased the risk of 30-day mortality after surgery by 114.6.0%. And the figure dropped to 86.7% after adjusting the propensity score. Thus the results better showed the relationship between RDW and he risk of 30-day mortality after surgery in the real world. Furthermore, we adjusted for different covariates. Several biochemical parameters were adjusted, including eGFR, CVA, DM, IHD, CHF, the RCRI score, ASA status, and hemoglobin. Additionally, our sample size is larger (90,785), and the participants represent four races in Singapore, making it a more representative sample of Asians. The results of our study indicates a correlation between high RDW and a higher risk of 30-day mortality after surgery. Understanding high RDW as a potential risk factor for perioperative period will allow us to communicate risk better with patients and provide more personalized prevention approach and management protocols. The findings of our study are helpful for promoting propensity score methods in correlation studies.
Nevertheless, some people opposed the above view. Xingchen Li et al. (36) retrospectively analyzed 157 patients who underwent radical resection of the liver and found that low preoperative RDW levels were associated with lower survival rates after radical resection of cholangiocarcinoma (ICC), meaning that patients with higher RDW values had better prognosis. Not come singly but in pairs, a retrospective study involving 380 patients with colorectal cancer liver metastasis (CRLM) who underwent liver resection revealed a significant correlation between preoperative, red blood cell distribution width- coefficient of variation(RDW-CV) elevation and better postoperative progression free survival (PFS) through univariate and multivariate Cox regression analysis (mPFS: 5.0 vs. 8.9 months, P = 0.007; mOS: 59.0 vs. 42.0 months, P = 0.041) (37). Pedrazzani C et al. (15) analyzed 591 patients who underwent colorectal cancer surgery and found that patients with a value higher than 14.1% (H-RDW) did not show a shorter cancer-related survival period. Meanwhile, according to Tumor Node Metastasis(TNM) staging, H-RDW is only associated with a decrease in postoperative survival rate in stageⅠ(p = 0.001), but H-RDW does not seem to affect survival rates in stages II-IV.
Inconsistent findings may be caused by the following factors: (1) Study participants are diverse in terms of their racial, gender, nationality, age, and other characteristics. (2) The sample size of different studies varies greatly. (3) There were various confounding variables taken into account in these studies to adjust for the relationship between RDW and postoperative mortality. (4) Results vary greatly depending on the time between follow-ups.(5)There are different ways to handle confounding factors. As a result of our findings, the existing literature supports the hypothesis that high RDW increases 30-day mortality after surgery, highlighting the importance of reducing RDW before surgery.
There is still some uncertainty regarding whether high RDW is directly related to postoperative mortality. The increase of RDW reflects the changes of erythrocyte homeostasis, including erythropoiesis disorder, abnormal erythrocyte metabolism and survival, which may be caused by various abnormal conditions in the body, including inflammation, oxidative stress, malnutrition, erythrocyte fragmentation, hypertension, dyslipidemia and erythropoietin abnormality (38–41). Patients with high RDW often have more significant inflammatory reactions and malnutrition before surgery, inhibiting the proliferation of bone marrow primitive cells, allowing immature red blood cells to enter the bloodstream. At the same time, aging red blood cells in the bloodstream are reduced, resulting in smaller or larger red blood cells present in the bloodstream, ultimately leading to an increase in RDW (42). Perlstein et al. (43)found that the increase in RDW is closely related to certain inflammatory response markers such as CRP, erythrocyte sedimentation rate, IL-6, etc. RDW may be a comprehensive response of a series of inflammatory factors acting on the body during sepsis, that is, the oxidative stress response caused by the action of inflammatory factors on the body. Inflammation leads to changes in the nervous and endocrine systems in the body, activates the related renin angiotensin aldosterone system, promotes the production of erythropoietin (EPO), and stimulates red blood cell proliferation (44);Inflammation, in turn, affects bone marrow hematopoietic function and iron metabolism (45). A series of inflammatory factors inhibit the maturation of red blood cells, leading to obstacles and ineffective generation of mature red blood cells, increased heterogeneity of red blood cells, and an increase in RDW (46).Therefore, RDW can reflect the general health status, subclinical and clinical disease status, and provide valuable information for predicting the prognosis of patients with various common acute and chronic diseases, such as diabetes (47), traumatic brain injury (TBI) (48); and oxidative stress (49) association.
Study strengths and limitations
Strengths of this study include the following. As far as we know, patients undergoing noncardiac surgery have fewer cohort studies using propensity score matching to explore the relationship between preoperative RDW and postoperative 30-day mortality. First, a cross-sectional study was conducted to investigate the relationship between RDW and postoperative prognosis using the PSM. Observational studies have increasingly used PSM methods in recent years. With the PSM method, a wide range of data requirements can be satisfied, including reducing inter-group differences, balancing confounding variables, and achieving the effect of“similar randomization”. Second, to reduce treatment selection bias inherent in retrospective studies, in order to minimize baseline differences between groups, we employ the doubly robust estimation method. Third, using a sensitivity analysis, we validated the data's reliability. As part of this study, IPTW was primarily used to establish a weighted cohort and further investigate the relationship between RDW and postoperative 30-day mortality rate. Fourth, unlike previous retrospective cohort studies, this study included a larger sample size of participants. Additionally, this clinical database contained detailed information about demographics, preexisting comorbidities, and risk assessment methods that can affect morbidity and mortality independently.
However, there are several limitations to the present stud. First, the study population consisted of only Asian patients. In order to enhance the reliability of the data, multicenter research can be conducted to expand the study population. And the raw data did not provide information on surgical intervention during patient follow-up. This limits the exploration of this study, in the future, we can consider designing our studies or collaborating with other researchers to collect as many variables as possible, including information on surgical intervention during patient follow-up, the investigators must have homogenous groups. Second, in this study, published data were analyzed secondary, it was not possible to eliminate residual and/or unmeasured confounding factors from the evaluated associations(e.g. inflammatory markers and socioeconomic factors) and investigate the long-term relationship between RDW and health outcomes. Third, although the PSM tried to balance known confounding variables to the best of its ability, it did not ensure that all measures of baseline characteristics matched, nor did it account for the influence of unknown variables. As a measure of reducing interference from variables, we set the calliper width to 0.01. Fourth, in addition, other diseases, as well as fat and carbohydrate metabolism, can also affect RDW (50, 51). Therefore, RDW should be evaluated in combination with other morphological and clinical parameters. Fifth, it discharged patients with high-risk injuries, such as nerve injuries, burns, and serious infections, despite the fact that it was originally aimed at non-cardiac surgery populations. Sixth, our research objective is to explore the impact of baseline RDW on mortality occurring within 90 days, the time span in the raw data is indeed very large. This might lead to selection bias.