Preoperative Glucose-to-Lymphocyte Ratio is an Independent Predictor for Acute Kidney Injury After Cardiac Surgery in Patients in Intensive Care Unit

Better prognosis in surgical aortic valve replacement patients with lower red cell distribution width: A MIMIC-IV database study

BACKGROUND

Surgical aortic valve replacement (SAVR) currently stands as a primary surgical intervention for addressing aortic valve disease in patients. This retrospective study focused on the role of the red blood cell distribution width (RDW) in predicting adverse outcomes among SAVR patients.

METHODS

The subjects for this study were exclusively derived from the Medical Information Mart for Intensive Care database (MIMIC IV 2.0). Kaplan‒Meier (K-M) curves and Cox proportional hazards regression models were employed to assess the correlation between RDW, one-year mortality, and postoperative atrial fibrillation (POAF). The smooth-fitting curves were used to observe the relative risk (RR) of RDW in one-year mortality and POAF. Furthermore, time-dependent receiver operating characteristic (ROC) curves, the continuous-net reclassification index (NRI), and integrated discrimination improvement (IDI) were employed for comprehensive assessment of the prognostic value of RDW.

RESULTS

Analysis of RDW revealed a distinctive inverted U-shaped relationship with one-year mortality, while its association with POAF appeared nearly linear. Cox multiple regression models showed that RDW > 14.35%, along with preoperative potassium concentration and perioperative red blood cell transfusion, were significantly linked to one-year mortality (K-M curves, log-rank P < 0.01). Additionally, RDW was associated with both POAF and prolonged hospital stays (P < 0.05). There was no significant difference in length of stay in ICU. Notably, the inclusion of RDW in the predictive models substantially enhanced its performance. This was evidenced by the time-dependent ROC curve (AUC = 0.829), NRI (P< 0.05), IDI (P< 0.05), and K-M curves (log-rank P< 0.01).

CONCLUSIONS

RDW serves as a robust prognostic indicator for SAVR patients, offering a novel means of anticipating adverse postoperative events.

GLR in Colorectal Cancers: An Easily Accessible Prognostic Marker

Background and Objectives

Colorectal cancer remains a significant health concern, necessitating reliable prognostic indicators for effective management. This study explores the preoperative prognostic significance of the Glucose/Lymphocyte Ratio (GLR) in colorectal cancers.

Methods

The study retrospectively analyzed records of patients who underwent surgery for elective colorectal cancers between January 1, 2013, and December 31, 2021, at the Koşuyolu Training and Research Hospital Gastroenterologic Surgery Department. Demographic, clinicopathological, and follow-up data were comprehensively assessed. A cutoff was established from GLR ratios and patients were divided into two groups for prognosis analysis.

Results

The study enrolled 222 eligible patients, examining variables such as age, sex, ASA score, neoadjuvant treatment, lymphovascular and perineural invasion, tumor grade, TNM stage, and GLR. The groups consisted of 128 patients with low GLR and 94 patients with high GLR. Statistical analyses revealed relations between GLR levels (p ≤ 0.001) and various prognostic factors such as age (p = 0.034), Perineural Invasion (PNI) (p = 0.002), tumor grade (p = 0.017), TNM stage (p = 0.003), and surgery time (p = 0.029), individuals with GLR ≥ 3.04 were observed to show higher mortality rates (p = 0.001). Above GLR cutoff point of 3.04 patients showed better overall survival rates. All survival related parameters were related with prognosis in univariant Cox regression tests. In multivariant cox regression tests GLR ≥ 3.04 significantly increased mortality by 2.9 times. (p = 0.003).

Conclusion

This study demonstrates that GLR, calculated from preoperative glucose and lymphocyte values serves as an independent prognostic factor in colorectal cancers. The findings suggest potential applications for GLR in survival analyses, with significant associations identified in age, PNI, tumor grade, TNM stage, and surgery time. Further investigations are warranted in homogeneous patient populations.

Preoperative glucose-to-lymphocyte ratio predicts survival in cancer

Background

Systemic inflammation and glucose metabolism have been closely related to the survival of cancer patients. Therefore, we aimed to evaluate whether preoperative glucose-to-lymphocyte ratio (GLR) can be used to predict the survival of cancer patients.

Methods

We retrospectively examined 2172 cancer patients who underwent surgery from January 1, 2014, to December 31, 2016. There were 240 patients with non-small cell lung cancer (NSCLC), 378 patients with colorectal cancer (CRC), 221 patients with breast cancer (BC), 335 patients with gastric cancer (GC), 270 patients with liver cancer, 233 patients with esophageal cancer (EC), 295 patients with renal cancer, and 200 patients with melanoma. The formula for preoperative GLR calculation was as follows: GLR=glucose/lymphocyte count. The overall survival (OS) was estimated using the Kaplan-Meier method. The predictive factors for OS were determined using multivariate analysis.

Results

The Kaplan-Meier analysis showed that the median survival time in the high-GLR group was much shorter than that of those in the low-GLR group for different cancers. Cox multivariate regression analysis reveals that preoperative GLR was an independent factor for predicting overall survival in different tumor types.

Conclusion

Elevated preoperative GLR was remarkably associated with a poorer prognosis in patients with NSCLC, CRC, breast cancer, gastric cancer, kidney cancer, liver cancer, esophageal cancer, and melanoma. Preoperative GLR promises to be an essential predictor of survival for cancer patients.

Malignant cancer may increase the risk of all-cause in-hospital mortality in patients with acute myocardial infarction: a multicenter retrospective study of two large public databases

BACKGROUND

Acute myocardial infarction (AMI) and cancer are diseases with high morbidity and mortality worldwide, bringing a serious economic burden, and they share some risk factors. The purpose of this study was to determine the effect of cancer on the all-cause in-hospital mortality of patients with AMI.

METHODS

This multicenter retrospective study analyzed patients with AMI from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and eICU Collaborative Research Database (eICU-CRD) in the United States. Patients were divided into two groups based on whether they had concomitant malignant cancer: cancer and noncancer groups. The outcome was all-cause in-hospital mortality. The association between the two groups and their outcomes were analyzed using Kaplan-Meier and Cox proportional-hazards regression models. Propensity score matching (PSM) and propensity score based inverse probability of treatment weighting (IPTW) were used to further adjust for confounding variables to verify the stability of the results.

RESULTS

The study included 3,034 and 5,968 patients with AMI from the MIMIC-IV database and the eICU-CRD, respectively. Kaplan-Meier survival curves indicated that the probability of in-hospital survival was lower in patients with cancer than in those without cancer. After adjusting for potential confounding variables using multivariable Cox proportional hazards regression, the risk of all-cause in-hospital mortality was significantly higher in the cancer than the noncancer group, and the HR (95% CI) values for the cancer group were 1.56(1.22,1.98) and 1.35(1.01,1.79) in the MIMIC-IV database and the eICU-CRD, respectively. The same results were obtained after using PSM and IPTW, which further verified the results.

CONCLUSIONS

Among the patients with AMI, the all-cause in-hospital mortality risk of those with cancer was higher than those without cancer. Therefore, when treating such patients, comprehensive considerations should be made from a multidisciplinary perspective involving cardiology and oncology, with the treatment plan adjusted accordingly.

Prognostic value of glucose to lymphocyte ratio for patients with renal cell carcinoma undergoing laparoscopic nephrectomy: A multi-institutional, propensity score matching cohort study

Background

We evaluated the prognostic value of preoperative blood glucose to lymphocyte ratio (GLR) in renal cell carcinoma (RCC) patients who underwent laparoscopic nephrectomy through a multi-institutional clinical study.

Methods

A total of 420 patients with RCC from three medical centers from 2014 to 2019 were included in this study. The effect of GLR on overall survival (OS) and cancer-specific survival (CSS) in RCC patients was assessed by Kaplan-Meier survival curves, univariate and multivariate Cox regression analysis. Moreover, a 1:1 propensity score matching (PSM) analysis of different GLR groups was utilized to further confirm the prognostic ability of GLR.

Results

The optimal cut-off value for GLR was 6.8. Patients were divided into high GLR and low GLR groups according to the optimal cut-off value. GLR was significant association with diabetes, cardiovascular disease and AJCC stage. High GLR predicted adverse OS (P = 0.002) and CSS (P < 0.01) in RCC patients. Multivariate Cox regression analysis revealed that high GLR was an independent prognostic factor for OS [hazard ratio (HR): 2.389, 95% confidence interval (CI), 1.136–5.027, P = 0.008] and CSS (HR: 3.474, 95% CI, 1.555–7.761, P = 0.002). After PSM analysis of the patients in the high GLR and low GLR groups, high GLR still predicted poor OS (P = 0.021) and CSS (P = 0.037).

Conclusions

High GLR is associated with adverse prognosis in RCC patients, and GLR can serve as an independent prognostic marker for OS and CSS in RCC patients receiving laparoscopic nephrectomy.

Predictive Value of the Transthoracic Echocardiography Index for Acute Kidney Injury after Cardiac Valve Surgery

Background: We aimed to demonstrate whether the preoperative transthoracic echocardiography index (TTEI) could improve the predictive value of clinical parameters for cardiac valve surgery-associated acute kidney injury (CVS−AKI). Methods: A total of 213 patients who underwent surgical CVS at Renmin Hospital of Wuhan University were consecutively recruited in this retrospective study. TTE assessments were performed within 7 days before surgery and logistic regression was used to determine TTEI. A nomogram was constructed by integrating TTEI and clinical features, and the net reclassification index (NRI) and integrated discrimination improvement (IDI) were applied to evaluate the improvement in TTEI for CVS−AKI. Results: Among them, 66 patients (30.9%) developed CVS−AKI. The TTEI was calculated as follows: −6.579 + 0.068 × pulmonary artery systolic pressure (mmHg) −0.742 × LVEF (>55%, yes or no) + 0.346 × left ventricle posterior wall thickness (mm). The nomogram based on the TEEI and other clinical factors possessed excellent performance (C-index = 0.880), had great calibration and discrimination, and was clinically useful. Furthermore, NRI (0.07, 95% confidence interval, 95%CI, 0.01−0.12, p = 0.02) and IDI (0.08, 95%CI, 0.01−0.20, p = 0.02) indicated that TTEI could significantly improve the predictive value of clinical features for CVS−AKI. Conclusions: As a simple access and cost-effective parameter, the preoperative TTEI may be a reliable and useful factor for CVS−AKI.

Association between glucose-to-lymphocyte ratio and in-hospital mortality in intensive care patients with sepsis: A retrospective observational study based on Medical Information Mart for Intensive Care IV

Background

This study aimed to evaluate the association between the glucose-to-lymphocyte ratio (GLR) and in-hospital mortality in intensive care unit (ICUs) patients with sepsis.

Methods

This is a retrospective cohort study. Patients with sepsis from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database had their baseline data and in-hospital prognosis retrieved. Multivariable Cox regression analyses were applied to calculate adjusted hazard ratios (HR) with 95% confidence intervals (CI). Survival curves were plotted, and subgroup analyses were stratified by relevant covariates. To address the non-linearity relationship, curve fitting and a threshold effect analysis were performed.

Results

Of the 23,901 patients, 10,118 patients with sepsis were included. The overall in-hospital mortality rate was 17.1% (1,726/10,118). Adjusted for confounding factors in the multivariable Cox regression analysis models, when GLR was used as a categorical variable, patients in the highest GLR quartile had increased in-hospital mortality compared to patients in the lowest GLR quartile (HR = 1.26, 95% CI: 1.15–1.38). When GLR was used as a continuous variable, each unit increase in GLR was associated with a 2% increase in the prevalence of in-hospital mortality (adjusted HR = 1.02, 95% CI: 1.01–1.03, p = 0.001). Stratified analyses indicated that the correlation between the GLR and in-hospital mortality was stable. The non-linear relationship between GLR and in-hospital mortality was explored in a dose-dependent manner. In-hospital mortality increased by 67% (aHR = 1.67, 95% CI: 1.45–1.92) for every unit GLR increase. When GLR was beyond 1.68, in-hospital mortality did not significantly change (aHR: 1.04, 95% CI: 0.92–1.18).

Conclusion

There is a non-linear relationship between GLR and in-hospital mortality in intensive care patients with sepsis. A higher GLR in ICU patients is associated with in-hospital mortality in the United States. However, further research is needed to confirm the findings.