The neutrophil-lymphocyte ratio: A promising predictor of mortality in coronary care unit patients - A cohort study

The relationship of COVID-19 severity with laboratory findings and neutrophil-to-lymphocyte ratio in patients admitted to a large teaching hospital in Iran: A cross-sectional study

Background and Aims

COVID-19 patients might be admitted to the hospital based on their clinical manifestations or to the intensive care unit (ICU) due to the severity of their symptoms or critical situation. Our main objective was to investigate clinical and demographic factors influencing COVID-19 patients' admission to the ICU and length of stay (LOS) using extracted data from the hospital information systems in Iran.

Methods

The data of hospitalized patients with confirmed COVID-19 were retrieved from the health information system of Imam Khomeini Hospital Complex, Tehran, Iran between March 2020 and February 2022. The primary outcome was the ICU admission, and the secondary outcome was the LOS. The correlation analysis between laboratory findings and demographic data with ICU admission and LOS was done using SPSS 21.0, and p < 0.05 was considered significant.

Results

Of all the 4156 patients, 2391 (57.5%) were male and the mean age was 58.69 ± 8.19 years. Of these, 9.5% of patients were admitted to ICU at any time point during their hospital stay. Age and laboratory variables such as neutrophil-to-lymphocyte ratio (NLR), ALT (U/L), albumin (g/dL), plasma glucose (mg/dL), ferritin levels (ng/mL), and phosphorous levels (mg/dL) shown the significant relationship with ICU admission. Also, being a smoker and having hypoxemia had a significant relationship with longer stays in the hospital. In this study, we validated a cut-off value of 4.819 for NLR, calculated at hospitalization, as a useful predictor of disease progression and occurrence of serious clinical outcomes, such as ICU admission.

Conclusion

The study examined various clinical factors associated with ICU admission in COVID-19 patients. The findings suggest that certain factors can increase the risk of ICU admission and influence the length of hospital stay which should be focused in future studies.

Neutrophil-to-Lymphocyte Ratio: A Promising Predictor of Mortality in Patients With Acute Respiratory Distress Syndrome. A Retrospective Analysis of a Single Hospital Center

OBJECTIVES

To examine how the neutrophil-to-lymphocyte ratio (NLR) affects both short-term and long-term mortality in individuals with acute respiratory distress syndrome (ARDS).

DESIGN

A retrospective study.

SETTING

Critical care unit.

PARTICIPANTS

A total of 785 patients with ARDS.

INTERVENTIONS

There were three groups in the NLR study. A Cox proportional hazards regression model was used to calculate the hazard ratio (HR) between the NLR and 30-day, 90-day, and 1-year mortality.

MEASUREMENTS AND MAIN RESULTS

The 785 patients included 329 women (41.9%) and 456 men (58.1%), with a mean age of 63.4 ± 16.7 years and a mean NLR of 14.2 ± 9.8. The study population was divided into 3 groups based on NLR value. In the unadjusted model, compared to group 1 (NLR <6.0), group 2 (NLR 6.0-11.3) and group 3 (NLR >11.3) had HR values of 1.12 (95% confidence interval [CI], 0.83-1.52) and 2.39 (95% CI, 1.87-3.04), respectively, for 30-day all-cause mortality. This association remained significant after adjusting for potential confounding variables (HR, 1.54; 95% CI, 1.18-2.02), with a statistically significant trend (p = 0.0004) in group 3 (NLR >11.3). A similar effect was seen on both 90-day and 1-year all-cause mortality. The R2 value in a 2-piecewise linear regression was 1.25 (95% CI, 1.06-1.48; p < 0.0001) on the left side of the inflection point (NLR 17.1).

CONCLUSIONS

In this retrospective single-center study, the NLR was a potential predictor of both short- and long-term mortality in patients with ARDS and may aid risk stratification.

Prediction of Osteoporotic Hip Fracture Outcome: Comparative Accuracy of 27 Immune-Inflammatory-Metabolic Markers and Related Conceptual Issues

Objectives: This study, based on the concept of immuno-inflammatory-metabolic (IIM) dysregulation, investigated and compared the prognostic impact of 27 indices at admission for prediction of postoperative myocardial injury (PMI) and/or hospital death in hip fracture (HF) patients. Methods: In consecutive HF patient (n = 1273, mean age 82.9 ± 8.7 years, 73.5% females) demographics, medical history, laboratory parameters, and outcomes were recorded prospectively. Multiple logistic regression and receiver-operating characteristic analyses (the area under the curve, AUC) were used to establish the predictive role for each biomarker. Results: Among 27 IIM biomarkers, 10 indices were significantly associated with development of PMI and 16 were indicative of a fatal outcome; in the subset of patients aged >80 years with ischaemic heart disease (IHD, the highest risk group: 90.2% of all deaths), the corresponding figures were 26 and 20. In the latter group, the five strongest preoperative predictors for PMI were anaemia (AUC 0.7879), monocyte/eosinophil ratio > 13.0 (AUC 0.7814), neutrophil/lymphocyte ratio > 7.5 (AUC 0.7784), eosinophil count < 1.1 × 109/L (AUC 0.7780), and neutrophil/albumin × 10 > 2.4 (AUC 0.7732); additionally, sensitivity was 83.1-75.4% and specificity was 82.1-75.0%. The highest predictors of in-hospital death were platelet/lymphocyte ratio > 280.0 (AUC 0.8390), lymphocyte/monocyte ratio < 1.1 (AUC 0.8375), albumin < 33 g/L (AUC 0.7889), red cell distribution width > 14.5% (AUC 0.7739), and anaemia (AUC 0.7604), sensitivity 88.2% and above, and specificity 85.1-79.3%. Internal validation confirmed the predictive value of the models. Conclusions: Comparison of 27 IIM indices in HF patients identified several simple, widely available, and inexpensive parameters highly predictive for PMI and/or in-hospital death. The applicability of IIM biomarkers to diagnose and predict risks for chronic diseases, including OP/OF, in the preclinical stages is discussed.

Impact of obesity on outcomes of patients with acute respiratory distress syndrome: a retrospective analysis of a large clinical database

OBJECTIVE

To evaluate the link between obesity and mortality in patients with acute respiratory distress syndrome (ARDS).

METHODS

We performed a retrospective cohort study of a large clinical database. A Cox proportional hazards regression model was used to calculate the hazard ratio (HR) and 95% confidence interval (CI) for the relationship between body mass index (BMI) and mortality. The primary endpoint was 30-day death rate and the secondary endpoints were 90-day and 1‑year mortality.

RESULTS

Overall, 418 patients with ARDS were enrolled in the study, including 185 women and 233 men (age: 70.7 ± 44.1 years; BMI: 28.7 ± 8.1 kg/m2). Compared with patients with normal weight, obese patients were younger (60.1 ± 13.7, p = 0.003) and a higher percentage of these patients were women (51.3% vs. 49.0%, p = 0.001). The HRs (95% CI) of 30-day mortality in the underweight, overweight, and obese populations were 1.82 (0.85, 3.90), 0.59 (0.29, 1.20), and 3.85 (1.73, 8.57), respectively, after adjustment for other confounding factors. A similar pattern was also seen for death after 90 days and after 1 year. A U-shaped association between BMI and 30-day mortality was discovered by curve fitting.

CONCLUSION

Obesity had a significant impact on the short- and long-term mortality in patients with ARDS. There was a U-shaped relationship between BMI and mortality, while a higher BMI was associated with an increased risk of death in patients with ARDS.

Multimodal data-driven prognostic model for predicting new-onset ST-elevation myocardial infarction following emergency percutaneous coronary intervention

OBJECTIVES

We developed a nomogram model derived from inflammatory indices, clinical data, and imaging data to predict in-hospital major adverse cardiac and cerebrovascular events (MACCEs) following emergency percutaneous coronary intervention (PCI) in patients with new-onset ST-elevation myocardial infarction (STEMI).

METHODS

Patients with new-onset STEMI admitted between June 2020 and November 2022 were retrospectively reviewed. Data pertaining to coronary angiograms, clinical data, biochemical indices, and in-hospital clinical outcomes were derived from electronic medical records. Lasso regression model was employed to screen risk factors and construct a prediction model.

RESULTS

Overall, 547 patients with new-onset STEMI who underwent PCI were included and assigned to the training cohort (n = 384) and independent verification cohort (n = 163). Six clinical features (age, diabetes mellitus, current smoking, hyperuricemia, neutrophil-to-lymphocyte ratio, and Gensini score) were selected by LASSO regression to construct a nomogram to predict the risk of in-hospital MACCEs. The area-under-the-curve (AUC) values for in-hospital MACCEs risk in the training and independent verification cohorts were 0.921 (95% CI 0.881-0.961) and 0.898 (95% CI 0.821-0.976), respectively. It was adequately calibrated in both training cohort and independent verification cohorts, and predictions were correlated with actual outcomes. Decision curve analysis demonstrated that the nomogram was capable of predicting in-hospital MACCEs with good clinical benefit.

CONCLUSIONS

Our prediction nomogram based on multi-modal data (inflammatory indices, clinical and imaging data) reliably predicted in-hospital MACCEs in new-onset STEMI patients with emergency PCI. This prediction nomogram can enable individualized treatment strategies.

Independent and Combined Associations of Blood Manganese, Cadmium and Lead Exposures with the Systemic Immune-Inflammation Index in Adults

Manganese (Mn), cadmium (Cd) and lead (Pb) have toxic effects on the immune system. However, their independent and combined effects on immune-inflammation responses are unclear. In recent years, the systemic immune-inflammation index (SII) has been developed as an integrated and novel inflammatory indicator. A retrospective cross-sectional study of 2174 adults ≥20 years old from the National Health and Nutrition Examination Survey (NHANES) 2015-2016 was conducted. Generalized linear models were used to evaluate the independent and combined associations of SII with blood Mn, Cd and Pb levels. As continuous variables, both blood Cd and Mn showed dose-dependent relationships with the SII before and after adjusting for all potential confounding factors. Metal concentrations were then converted into categorical variables. Compared with the adults in the lowest Cd or Mn tertile, those in the highest tertile had higher risks of elevated SII. Furthermore, co-exposure to Mn and Cd also showed a positive relationship with the SII after adjusting for all confounding factors. However, the single effect of Pb exposure and the joint effect of Pb and other metal exposures on the SII were not observed. This study provides important epidemiological evidence of the associations of SII with single and co-exposure effects of blood Mn, Cd, and Pb.

Changes and Rate of Change in Neutrophil-Lymphocyte Ratio (∆NLR) as an Early Prognostic Marker for the Severity of Outcomes in Patients With COVID-19 and Its Applicability in Other Viral and Bacterial Diseases

INTRODUCTION

COVID-19 is a global pandemic that has spread rapidly and resulted in numerous deaths worldwide. Many inflammatory markers such as neutrophil-lymphocyte ratio (NLR), D-dimer, serum ferritin, C-reactive protein (CRP), and interleukin-6 (IL-6) were used for the diagnosis and prognosis of COVID-19.

METHODS

We have proposed using Delta NLR (0-48 hours) (∆NLR) as an early diagnostic marker for COVID-19 and other inflammatory disorders. We have created a prediction model based on six variables: overall severity, death, shifting to the ICU, length of stay, oxygen requirement, and ventilator support. Prediction models help us prepare for future pandemics through early diagnosis and management.

RESULTS

A total of 1,865 patient records were retrieved from the database. The final sample available for analysis was 461. Change in NLR or ∆NLR was significant for all the models (except for length of stay) created by logistic regression.

CONCLUSION

An independent predictor of the poor prognosis of COVID-19 is the severity of the disease in the initial one or two days. ∆NLR is a unique marker, and its scope of use in other disorders' prognoses must be further researched. The prediction models also help us in decision-making strategies and also prepare us for future pandemics.

The association between sedentary behavior, exercise, and sleep disturbance: A mediation analysis of inflammatory biomarkers

Background

Two related lifestyle behaviors associated with sleep disturbance are sedentary behavior and physical exercise participation. We aimed to use a population-based study to disentangle the relationships between sedentary behavior, exercise, and sleep disturbance based on blood-cell-based inflammatory biomarkers.

Methods

A total of 22,599 participants from the National Health and Nutrition Examination Survey (NHANES) were included in the analyses. Sleep disturbance was assessed according to the NHANES questionnaire. Exercise participation ansd sedentary behavior were evaluated by the global physical activity questionnaire. The inflammatory biomarkers in the examination were white blood cell (WBC) count, neutrophil count (NEU), neutrophil-to-lymphocyte ratio (NLR), and systemic immune inflammation index (SII). A complex multistage sampling design and weighted multivariable logistic regression were applied for further analysis. Mediation models were constructed to figure out the mediating role of inflammatory biomarkers.

Results

The weighted prevalence of sleep disturbance was 24.17%. Sedentary behavior and exercise were associated with sleep disturbance after full adjustment [for sedentary behavior, OR (95% CI): 1.261 (1.154, 1.377); for exercise, OR (95% CI): 0.849 (0.757, 0.953)]. In severe sedentary behavior groups, the mitigation effect of exercise on sleep disturbance was observed [OR (95% CI): 0.687 (0.551, 0.857)]. For the mechanism, strong associations were detected between inflammatory biomarkers and sleep disturbance. Mediation analysis showed that WBC, NEU, NLR, and SII mediated the statistical association between sedentary behavior and sleep disturbance with proportions (%) of 2.09, 2.27, 1.76, and 0.82, respectively.

Conclusions

Our data suggested that sedentary behavior was a risk factor for sleep disturbance. Blood-cell-based inflammatory biomarkers were an easily accessible and cost-effective strategy for identifying sleep disturbance and also significantly mediated the association between sedentary behavior and sleep disturbance. Exercise was proved to be effective in severe sedentary behavior groups to improve sleep disturbance symptoms, while the internal mechanism needed further exploration.

The Ratio of Red Blood Cell Distribution Width to Albumin Is Correlated With All-Cause Mortality of Patients After Percutaneous Coronary Intervention – A Retrospective Cohort Study

Objectives

The purpose of this study was to investigate the independent effect of the ratio of red blood cell distribution width (RDW) to albumin (RA) on all-cause mortality in patients after percutaneous coronary intervention (PCI).

Methods

Clinical data were obtained from the Multiparameter Intelligent Monitoring in Intensive Care-III (MIMIC-III) database version 1.4 and the database of Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University. We used the MIMIC-III database for model training, and data collected from the Second Affiliated Hospital of Wenzhou Medical University for validation. The primary outcome of our study was 90-day mortality. Cox proportional hazards regression model was used to estimate hazard ratio (HR) for the association between RA and all-cause mortality in patients after PCI. Pearson correlation analysis was conducted to assess the relationship between RA and Gensini score or cardiac troponin I (cTnI).

Results

A total of 707 patients were eligible in MIMIC-III database, including 432 males, with a mean age of 70.29 years. For 90-day all-cause mortality, in the adjusted multivariable model, the adjusted HRs [95% confidence intervals (CIs)] for the second (RA: 3.7–4.5 ml/g) and third (RA >4.5 ml/g) tertiles were 2.27 (1.11, 4.64) and 3.67 (1.82, 7.40), respectively, compared to the reference group (RA <3.7 ml/g) (p < 0.05). A similar relationship was also observed for 30-day all-cause mortality and 1-year all-cause mortality. No significant interaction was observed in subgroup analysis. Receiver operating characteristic (ROC) curve analysis proved that the ability of RA to predict the 90-day mortality was better than that of RDW or albumin alone. The correlation coefficient between Gensini score and RA was 0.254, and that between cTnI and RA was 0.323.

Conclusion

RA is an independent risk factor for all-cause mortality in patients after PCI. The higher the RA, the higher the mortality. RA has a good predictive ability for all-cause mortality in patients after PCI, which is better than RDW or albumin alone. RA may be positively correlated with the severity of coronary artery disease (CAD) in patients with CAD.

Clinical Value of the Prognostic Nutrition Index in the Assessment of Prognosis in Critically Ill Patients with Stroke: A Retrospective Analysis

Purpose

The purpose of study was to evaluate the association between prognostic nutritional index (PNI) and all-cause mortality of critically ill patients with stroke.

Methods

Clinical data derived from Multiparameter Intelligent Monitoring in Intensive Care were analyzed. The primary endpoint was 30-day all-cause mortality; secondary endpoints were 90-day mortality and one-year cause mortality. The potential prognostic roles of PNI were analyzed by Cox proportional hazard models. The independent prognostic roles of PNI in the cases were analyzed by smooth curve fitting.

Results

Concerning 30-day mortality, the HR (95% CI) for a high PNI (≥39.7) was 0.700 (0.544, 0.900; P = 0.00539), compared to a low PNI (<39.7). After adjusting for multiple confounders, the HR (95% CI) for a high PNI (≥39.7) was 0.732 (0.547, 0.978; P = 0.03514), compared to a low PNI (<39.7). Regarding 90-day and one-year mortality, a similar trend was observed. In addition, a nonlinear association between PNI and 30-day mortality was found. Using recursive algorithm and two-piecewise linear regression model, inflection point (IP) was calculated, which was 49.4. On the right side of the IP, there was a positive relationship between PNI and 30-day mortality, and the effect size, 95% CI, and P value were 1.04 (1.01, 1.07), P = 0.0429, respectively. On the left of the IP, the effect size, 95% CI, and P value were 0.97 (0.96, 0.99) and 0.0011, respectively.

Conclusions

The PNI was an independent predicting factor of 30-day, 90-day, and 1-year mortality of the critically ill patients with stroke. In addition, there was a U-shaped relationship between PNI and all-cause mortality of stroke patients. PNI was a risk factor for the outcome of stroke when PNI was >49.4, while PNI was a protective factor for outcome of stroke when PNI was <49.4.

Red blood cell distribution width-to-albumin ratio is associated with all-cause mortality in cancer patients

Background

Cancer causes a serious health burden on patients worldwide. Chronic low‐level inflammation plays a key role in tumorigenesis and prognosis. However, the role of the red blood cell distribution width (RDW)‐to‐albumin (RA) ratio in cancer mortality remains unclear.

Methods

In this retrospective cohort study, we collected clinical information from cancer patients from the Medical Information Mart for Intensive Care III (MIMIC‐III) version 1.4 database and then calculated RA by dividing RDW by albumin concentration. The primary outcome was 30 days mortality, while secondary outcomes were 90 days and 1 year mortality. Next, we adopted Cox regression models to calculate hazard ratios (HR) together with 95% confidence intervals (CI) for all‐cause mortalities associated with the RA ratio.

Results

For 30 days mortality, the HR (95% CI) for the high RA ratio (≥5.51) was 2.17 [95CI% (1.87–2.51); p = <0.0001], compared with the low RA ratio (<5.51). In Model 2, we adjusted sex and age and obtained HR (95% CI) of 2.17 [95CI% (1.87–2.52); p = <0.0001] for the high RA ratio (≥5.51) group, compared to that in the low RA ratio (<5.51). In Model 3, adjusting for age, sex, anion gap, hematocrit, white blood cell count, congestive heart failure, SOFA, liver disease, and renal failure resulted in HR (95% CI) of 1.74 [95CI% (1.48–2.04); p = <0.0001] for the high RA ratio (≥5.51) relative to the low RA ratio (<5.51). We also analyzed common diseases in cancer patients but found no significant association.

Conclusion

To the best of our knowledge, this is the first study demonstrating that increased RA ratio is independently associated with increased all‐cause mortality in cancer patients.

Prognostic value of glucose-to-lymphocyte ratio in critically ill patients with acute respiratory distress syndrome: A retrospective cohort study

Background

There is need to identify biomarkers for prognosis of acute respiratory distress syndrome (ADRS). This may allow early and accurate identification of patients with high‐risk ARDS to guide adjustment of clinical treatment and nursing intervention, which would ultimately improve prognosis of patients with ARDS. Biomarkers based on a combination of fasting glucose and lymphocyte counts to predict prognosis in critically ill patients with ARDS remain undefined. In this study, we investigated the association between glucose‐to‐lymphocyte ratio (GLR) and in‐hospital mortality.

Methods

The study obtained data from Medical Information Mart for Intensive Care‐IV (MIMIC‐IV Version 1.0) database. We defined the GLR as fasting glucose/lymphocyte count and the patient in‐hospital mortality was considered as the outcome. In addition, we employed linear and logistic regression models for analysis.

Results

In total, 1,085 patients with ARDS were included in this study. The eligible participants included 498 female and 587 males, with a mean age of 64.2 ± 17.5 years. Logistic regression analysis demonstrated that higher GLR was an independent risk factor for all‐cause mortality (OR =1.67, 95% CI: 1.26–2.22) after adjusting for age, sex, anion gap, white blood cell count, congestive heart failure, sequential organ failure assessment (SOFA), SBP, DBP, and respiratory rate in both the dichotomized group and subgroups. We also analyzed the in‐hospital mortality to ROC curves by comparing the value between SOFA + GLR and SOFA. The area under the curve (AUC) was 0.6991 for the SOFA + GLR (95% CI: 0.6634–0.7348), and 0.6613 for the SOFA (95% CI: 0.6238–0.6988).

Conclusion

Our data showed that the GLR was an independent predictor of in‐hospital mortality for patients with ARDS. The GLR is an integrated, readily available clinical biomarker for mortality in patients with ARDS.

Association of platelet count with all-cause mortality from acute respiratory distress syndrome: A cohort study

Background

The purpose of this study was to investigate whether platelet count was associated with mortality in acute respiratory distress syndrome (ARDS) patients.

Methods

We analyzed patients with ARDS from Multi‐parameter Intelligent Monitoring in Intensive Care Database III (MIMIC‐III). Platelet count was measured at the time of intensive care unit (ICU) admission. The cox proportional hazard model and subgroup analysis were used to determine the relationship between the platelet count and mortality of ARDS, as well as the consistency of its association. The primary outcome of this study was 365‐day mortality from the date of ICU admission.

Result

This study enrolled a total of 395 critically ill patients with ARDS. After adjustment for age, gender and ethnicity, the multivariate cox regression model showed that the hazard ratios (HRs) (95% confidence intervals [CIs]) of platelet count <192 × 10⁹/L and >296 × 10⁹/L were 2.08 (1.43, 3.04) and 1.35 (0.91, 2.01), respectively, compared with the reference (192–296 ×10⁹/L). After adjusting for confounding factors, lower platelet count (<192 × 10⁹/L) was associated with increased mortality (adjusted HR, 1.71; 95% CI 1.06–2.76, p = 0.0284). However, there was no similar trend in the 30‐day (adjusted HR,1.02; 95% CI 0.54–1.94) or 90‐day (adjusted HR, 1.65; 95% CI 0.94–2.89) mortality. In the subgroup analysis, lower platelet count showed significant interactions with specific populations (p interaction = 0.0413), especially in patients with atrial fibrillation.

Conclusion

Taken together, our analysis showed that platelet count is an independent predictor of mortality in critically ill patients with ARDS.

Prognostic nutrition index is associated with the all‐cause mortality in sepsis patients: A retrospective cohort study

Background

The study aimed at evaluating the prognostic utility of the prognostic nutritional index (PNI) for patients with sepsis.

Methods

Data in the present study were obtained from the Multiparameter Intelligent Monitoring in Intensive Care Database III. The calculation for PNI was as follows: serum albumin concentration (g/L) +0.005 × total lymphocyte count. 30‐day mortality was considered as the primary outcome, while 90‐day mortality and one‐year mortality were the secondary outcomes. Cox proportional risk models and propensity score matching (PSM) analyses were used to analyze the association between PNI and clinical outcomes in patients with sepsis. To assess the predictive value of PNI for 30‐day mortality, receiver operator characteristic (ROC) curve analysis was performed.

Results

A total of 2669 patients were in the study. After the confounding factors were adjusted, PNI ≥ 29.3 was identified as an independent predictive prognostic factor for the 30‐day all‐cause mortality (hazard ratio [HR]: 0.65; 95% confidence interval [CI]: 0.56–0.76; p < 0.00001). Moreover, PSM analysis further validated the prognostic predictive value of PNI for patients with sepsis. The AUC of the PNI was 0.6436 (95% CI: 0.6204–0.6625) which was significantly high than the AUC of NLR (0.5962, 95% CI: 0.5717–0.6206) (p = 0.0031), the RDW (0.5878, 95% CI: 0.5629–0.6127) (p < 0.0001), and PLR (0.4979, 95% CI: 0.4722–0.5235) (p < 0.0001).

Conclusion

The findings suggested that PNI was also a significant risk factor for sepsis.

Platelet-lymphocyte ratio as a new predictor of in-hospital mortality in cardiac intensive care unit patients

It has been discovered that both inflammation and platelet aggregation could cause crucial effect on the occurrence and development of cardiovascular diseases. As a combination of platelet and lymphocyte, platelet-lymphocyte ratio (PLR) was proved to be correlated with the severity as well as prognosis of cardiovascular diseases. Exploring the relationship between PLR and in-hospital mortality in cardiac intensive care unit (CICU) patients was the purpose of this study. PLR was calculated by dividing platelet count by lymphocyte count. All patients were grouped by PLR quartiles and the primary outcome was in-hospital mortality. The independent effect of PLR was determined by binary logistic regression analysis. The curve in line with overall trend was drawn by local weighted regression (Lowess). Subgroup analysis was used to determine the relationship between PLR and in-hospital mortality in different subgroups. We included 5577 CICU patients. As PLR quartiles increased, in-hospital mortality increased significantly (Quartile 4 vs. Quartile 1: 13.9 vs. 8.3, P < 0.001). After adjusting for confounding variables, PLR was proved to be independently associated with increased risk of in-hospital mortality (Quartile 4 vs. Quartile 1: OR 95% CI 1.55, 1.08–2.21, P = 0.016, P for trend < 0.001). The Lowess curves showed a positive relationship between PLR and in-hospital mortality. The subgroup analysis revealed that patients with low Acute Physiology and Chronic Health Evaluation IV (APACHE IV) or with less comorbidities had higher risk of mortality for PLR. Further, PLR quartiles had positive relation with length of CICU stay (Quartile 4 vs. Quartile 1: 2.7, 1.6–5.2 vs. 2.1, 1.3–3.9, P < 0.001), and the length of hospital stay (Quartile 4 vs. Quartile 1: 7.9, 4.6–13.1 vs. 5.8, 3.3–9.8, P < 0.001). PLR was independently associated with in-hospital mortality in CICU patients.

Low-Density Lipoprotein Cholesterol is Inversely Associated with All-Cause Mortality of Patients in the Coronary Care Unit

Objective

The aims of this study were to investigate the relationship between low-density lipoprotein cholesterol (LDL-C) levels and all-cause mortality in coronary care unit (CCU) patients, adjusting for a wide range of potential confounding factors, to examine the potential of LDL-C in predicting the prognostic value of CCU patients.

Methods

Clinical data were extracted from Medical Information Mart for Intensive Care-III database (MIMIC-III database version v.1.4). Baseline data were collected within 24 hours after the patient was first admitted to the hospital. The primary endpoint of our study is 30-day all-cause mortality. The secondary endpoints are 90-day and one-year all-cause mortality and infections. Cox proportional hazard regression and propensity score-matched (PSM) analysis were used to analyze the association between LDL-C levels and prognostic value of CCU patients.

Results

We included a total of 1476 patients with an average age of 66.7 ± 14.1 years (66% male). For 30-day all-cause mortality, the hazard ratio (95% confidence interval) of high LDL-C level group (≥ 55 mg/dl) was 0.42 (0.29, 0.62), which was compared with low LDL-C level group (< 55 mg/dl) in unadjusted model. After adjusting for age, gender and race, the association still existed (P < 0.05), and the HR (95% CI) was 0.49 (0.33, 0.72). Further adjustment of possible covariates showed similar correlation (P < 0.05), and HR (95% CI) was 0.65 (0.43, 0.97). Similar correlations were observed for 90-day and one-year all-cause mortality. The relationship between all-cause mortality and LDL-C levels in CCU patients was further verified by propensity score-matched (PSM) analysis. In addition, the higher the LDL-C level, the lower the risk of infection, odds ratio (OR) values in the three models were less than 1 (P < 0.05).

Conclusion

Our data suggest that high LDL-C level is associated with a reduced risk of 30-day, 90-day, and one-year mortality of patients in the CCU. And this result is still stable in the PSM model. The results need to be verified in prospective trials.

Neutrophil-to-lymphocyte ratio as a predictor of mortality in intensive care unit patients: a retrospective analysis of the Medical Information Mart for Intensive Care III Database

OBJECTIVES

Identifying high-risk patients in the intensive care unit (ICU) is important given the high mortality rate. However, existing scoring systems lack easily accessible, low-cost and effective inflammatory markers. We aimed to identify inflammatory markers in routine blood tests to predict mortality in ICU patients and evaluate their predictive power.

DESIGN

Retrospective case-control study.

SETTING

Single secondary care centre.

PARTICIPANTS

We analysed data from the Medical Information Mart for Intensive Care III database. A total of 21 822 ICU patients were enrolled and divided into survival and death groups based on in-hospital mortality.

PRIMARY AND SECONDARY OUTCOME MEASURES

The predictive values of potential inflammatory markers were evaluated and compared using receiver operating characteristic curve analysis. After identifying the neutrophil-to-lymphocyte ratio (NLR) as having the best predictive ability, patients were redivided into low (≤1), medium (1-6) and high (>6) NLR groups. Univariate and multivariate logistic regression analyses were performed to evaluate the association between the NLR and mortality. The area under the curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to assess whether incorporating the NLR could improve the predictive power of existing scoring systems.

RESULTS

The NLR had the best predictive ability (AUC: 0.609; p<0.001). In-hospital mortality rates were significantly higher in the low (OR (OR): 2.09; 95% CI 1.64 to 2.66) and high (OR 1.64; 95% CI 1.50 to 1.80) NLR groups than in the medium NLR group. Adding the NLR to the Simplified Acute Physiology Score II improved the AUC from 0.789 to 0.798, with an NRI and IDI of 16.64% and 0.27%, respectively.

CONCLUSIONS

The NLR predicted mortality in ICU patients well. Both low and high NLRs were associated with elevated mortality rates, including the NLR may improve the predictive power of the Simplified Acute Physiology Score II.

Value of the Neutrophil-Lymphocyte Ratio in Predicting COVID-19 Severity: A Meta-analysis

Background

Coronavirus disease 2019 (COVID-19) is highly contagious and continues to spread rapidly. However, there are no simple and timely laboratory techniques to determine the severity of COVID-19. In this meta-analysis, we assessed the potential of the neutrophil-lymphocyte ratio (NLR) as an indicator of severe versus nonsevere COVID-19 cases.

Methods

A search for studies on the NLR in severe and nonsevere COVID-19 cases published from January 1, 2020, to July 1, 2021, was conducted on the PubMed, EMBASE, and Cochrane Library databases. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and area under the curve (AUC) analyses were done on Stata 14.0 and Meta-disc 1.4 to assess the performance of the NLR.

Results

Thirty studies, including 5570 patients, were analyzed. Of these, 1603 and 3967 patients had severe and nonsevere COVID-19, respectively. The overall sensitivity and specificity were 0.82 (95% confidence interval (CI), 0.77-0.87) and 0.77 (95% CI, 0.70-0.83), respectively; positive and negative correlation ratios were 3.6 (95% CI, 2.7-4.7) and 0.23 (95% CI, 0.17-0.30), respectively; DOR was 16 (95% CI, 10-24), and the AUC was 0.87 (95% CI, 0.84-0.90).

Conclusion

The NLR could accurately determine the severity of COVID-19 and can be used to identify patients with severe disease to guide clinical decision-making.

Association Between the Neutrophil Percentage-to-Albumin Ratio and Outcomes in Cardiac Intensive Care Unit Patients

Background

The neutrophil percentage-to-albumin ratio (NPAR) is a systemic inflammation-based predictor associated with many diseases' outcomes. Nevertheless, there are few studies on the relationship between NPAR and inflammatory markers, and more importantly, the prognostic value of NPAR in critically ill patients with cardiovascular disease (CVD) remains unknown.

Methods

The data of this retrospective cohort study were from the Medical Information Mart data for Intensive Care III database (MIMIC-III) and the Second Affiliated Hospital of Wenzhou Medical University. Linear regression, logistic regression model, and Cox regression model were used to assess the associations between NPAR levels and length of stay, renal replacement therapy (RRT) use, and 30-day, 90-day and one-year mortality, respectively. The Pearson correlation coefficient was used to present the correlation between NPAR and C-reactive protein (CRP).

Results

Our study included 1599 patients in MIMIC-III and 143 patients in the Second Affiliated Hospital of Wenzhou Medical University. The elevated NPAR was independently associated with increased 30-day, 90-day, and one-year all-cause mortality (adjusted HR, 95% CI:1.51 (1.02-2.24); 1.61 (1.14-2.28); 1.53 (1.15-2.03); P trend = 0.0297; 0.0053; 0.0023; respectively), and it was also associated with increase the length of stay in hospital and ICU (β, 95% CI: 2.76 (1.26-4.27); 1.54 (0.62-2.47), respectively, both P trend <0.001). We found that patients with higher NPAR were more likely to receive RRT (OR, 95% CI: 2.50 (1.28-4.89), P trend =0.0023). Moreover, we confirmed that NPAR was statistically positively correlated with CRP (correlation coefficient r = 0.406, P < 0.0001).

Conclusion

Elevated NPAR on admission was independently associated with increased all-cause mortality and length of stay among CICU patients. The results showed that CICU patients with higher NPAR were more likely to receive RRT. Besides, we also provided the evidence that there is a positive correlation between NPAR and inflammatory indicators (ie, CRP).

The Red Blood Cell Distribution Width-Albumin Ratio: A Promising Predictor of Mortality in Stroke Patients

Objective

Within this study we attempt to express a correlation between the mortality of stroke and stroke related infection to a novel biomarker represented by the red blood cell width-albumin levels ratio within the patient. We hypothesize that this novel biomarker could be utilized as better predictive tool for stroke associated infections.

Methods

Patient data sets were obtained via the Medical Information Mart for Intensive Care Database iii V1.4 (MIMIC-iii). Data from 1480 patients were obtained to serve the testing for the RA biomarker tests. Clinical endpoints of 30-, 60-, and 365-day all-cause mortality in stroke patients were used as subgroups within the analyzed population. Estimation of hazard ratios (HR) were obtained from Cox regression models for stroke-associated infection and all-cause mortality in relation to RA values.

Results

A high-RA was associated with increased mortality in ICU patients suffering from a stroke. After adjusting for age and sex, compared to the reference group (the first quartile), the high-RA group had the highest 30-day (HR, 95% CI: 1.88 (1.36, 2.58)), 90-day (HR, 95% CI: 2.12 (1.59, 2.82)), and one-year (HR, 95% CI: 2.15 (1.65, 2.80)) all-cause mortality. The RA values were independently associated with an increased risk of stroke-associated infection when adjusting for confounders.

Conclusions

Our data suggest RA may be an easily accessible, reproducible, and low-cost biomarker for predicting stroke-associated infections and mortality in patients who have suffered from a stroke.

Impact of obesity on outcomes in patients with acute respiratory syndrome

Objectives

We assessed the relationship between obesity and all-cause mortality in patients with acute respiratory distress syndrome (ARDS).

Methods

In this retrospective cohort study, patient data were extracted from the eICU Collaborative Research Database and the Medical Information Mart for Intensive Care Database III. Body mass index (BMI) was grouped according to World Health Organization classifications: underweight, normal weight, overweight, obese. Cox regression models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) of all-cause mortality related to obesity.

Results

Participants included 185 women and 233 men, mean age 70.7 ± 44.1 years and mean BMI 28.7 ± 8.1 kg/m². Compared with normal weight patients, obese patients tended to be younger (60.1 ± 13.7 years) and included more women (51.3% vs. 49.0%). In the unadjusted model, HRs (95% CIs) of 30-day mortality for underweight, overweight, and obesity were 1.57 (0.76, 3.27), 0.64 (0.39, 1.08), and 4.83 (2.25, 10.35), respectively, compared with those for normal weight. After adjustment, HRs (95% CIs) of 30-day mortality for underweight, overweight, and obesity were 1.82 (0.85, 3.90), 0.59 (0.29, 1.20), and 3.85 (1.73, 8.57), respectively, compared with the reference group; 90-day and 1-year all-cause mortalities showed similar trends.

Conclusions

Obesity was associated with increased all-cause mortality in patients with ARDS.

Association of monocyte-lymphocyte ratio with in-hospital mortality in cardiac intensive care unit patients

BACKGROUND

Inflammatory cell plays a very important part in the occurrence and development of cardiovascular disease. As a combination of lymphocyte and monocyte, monocyte-lymphocyte ratio (MLR) was proved to be related to the severity and prognosis of cardiovascular diseases. Our objective was to explore the association between MLR and in-hospital mortality in cardiac intensive care unit (CICU) patients.

METHOD

MLR was obtained by dividing monocyte percentage by lymphocyte percentage. All patients were grouped by MLR quartiles. Primary outcome was in-hospital mortality. Binary logistic regression analysis was performed to determine the independent effect of MLR.

RESULT

5512 CICU patients were included. In-hospital mortality increased as MLR quartiles increased (Quartile 4 vs Quartile 1: 16.3 vs 7.8, P < 0.001). After adjusting for confounding variables, MLR was proved to be independently associated with increased risk of in-hospital mortality (Quartile 4 vs Quartile 1: OR, 95% CI: 1.87, 1.38-2.56, P < 0.001, P for trend < 0.001). Subgroup analysis revealed that patients with low Acute Physiology and Chronic Health Evaluation IV (APACHE IV) or with less comorbidities had higher risk of mortality for MLR. As MLR quartiles increased, length of CICU stay (Quartile 4 vs Quartile 1: 2.8, 1.7-5.4 vs 2.1, 1.2-3.7, P < 0.001) and hospital stay (Quartile 4 vs Quartile 1: 8.3, 4.8-11.1 vs 5.3, 3.1-9.3, P < 0.001) were prolonged.

CONCLUSION

MLR was independently correlated with in-hospital mortality in CICU patients.

Red cell distribution width is associated with all-cause mortality in patients with acute stroke: a retrospective analysis of a large clinical database

Objectives

This study aimed to evaluate the association between the red blood cell distribution width (RDW) and mortality in patients with stroke.

Methods

We conducted a retrospective cohort study on patients with stroke in the Medical Information Mart for Intensive Care Database III. Cox proportional hazards regression models were used to estimate hazard ratios of 30-day, 90-day, and 1-year mortality in relation to the RDW level.

Results

A total of 4134 patients were enrolled, including 2646 patients with ischemic stroke and 1668 with hemorrhagic stroke. After adjustment for potential confounders, the hazard ratio (95% confidence interval) of 30-day mortality for the second (RDW: 13.4%–14.3%) and third (>14.3%) tertiles was 1.15 (0.96, 1.37) and 1.40 (1.17, 1.68), respectively, compared with the reference group (<13.4%). A two-piecewise linear regression model was established and the inflection point of RDW was 16.7%. When RDW was >16.7%, an increase in RDW did not increase stroke mortality.

Conclusions

The RDW is a prognostic factor of patients with stroke. This finding needs to be confirmed in future prospective studies.

Red cell distribution width is correlated with all-cause mortality of patients in the coronary care unit

Objective

The predictive value of red blood cell distribution width (RDW) in patients in the coronary care unit (CCU) remains unknown. This study aimed to examine the prognostic value of RDW in these patients.

Methods

Clinical data were extracted from the Medical Information Mart for Intensive Care-III database. Baseline data were collected within 24 hours after patients’ first admission to the CCU. The outcomes of our study were 30-day and 90-day mortality.

Results

A total of 8254 patients were included and their mean age was 66.9 ± 15.8 years (56% were men). For 30-day all-cause mortality, the hazard ratios (95% confidence interval) of the medium RDW (13.7–15.3) and high-RDW groups > 15.3) were 1.72 (1.55, 1.91) and 2.57 (2.33, 2.85), respectively, compared with the reference group in an unadjusted model. This association remained similar in multivariate models. Similar correlations were observed for 90-day all-cause mortality. The areas under the curve of RDW and the Sequential Organ Failure Assessment (SOFA) score were 0.625 and 0.692, respectively.

Conclusions

RDW is correlated with an increased risk of 30-day and 90-day mortality of patients in the CCU. The predictive value of RDW is not as good as that of the SOFA score.

Association Between Systemic Immune-Inflammation Index and Diabetic Depression

Background

Depression is highly prevalent in patients with diabetes mellitus (DM). Diabetic depression has been shown to be associated with low-grade systemic inflammation. In recent years, the systemic immune-inflammation (SII) index has been developed as an integrated and novel inflammatory indicator. The aims of this study were to investigate the relationship between diabetic depression and SII levels, adjusting for a wide range of potential confounding factors, to examine the potential of SII in predicting diabetic depression.

Methods

The present cross-sectional study was conducted among adults with DM in the National Health and Nutrition Examination Survey between 2009 and 2016, the SII level was calculated as the platelet counts × neutrophil counts/lymphocyte counts. Patient Health Questionnaire‐9 was used to measure depression in patients with DM. Multivariable logistic regression and propensity score-matched analysis were used to analyze the association between SII levels and depression.

Results

A total of 2566 patients with DM were included in the study, of which 370 (13.3%) were diagnosed with depression. Multivariable logistic regression showed that high SII level was an independent risk factor for diabetic depression (OR = 1.347, 95% CI: 1.031–1.760, P = 0.02882) after adjusting for covariates. The relationship between SII and diabetic depression was further verified by propensity score-matched analysis.

Conclusion

Our data suggest that SII is a risk factor for depression in patients with DM. The SII may be an easily accessible and cost-effective strategy for identifying depression in patients with DM. More studies are warranted to further analyze the role of SII in depression in diabetic patients.

Predictive efficacy of neutrophil-to-lymphocyte ratio for long-term prognosis in new onset acute coronary syndrome: a retrospective cohort study

BACKGROUND

Inflammation is involved in the pathogenesis and progression of coronary artery diseases (CADs), including acute coronary syndrome. The neutrophil-to-lymphocyte ratio (NLR) has been identified as a novel marker of the pro-inflammatory state. We aimed to evaluate the predictive efficacy of the NLR for the prognosis of patients with new-onset ACS.

METHODS

We retrospectively included consecutive patients with new-onset ACS treated with emergency coronary angiography. NLR was measured at baseline and analyzed by tertiles. The severity of coronary lesions was evaluated by the Gensini score. Correlations of NLR with the severity of CAD and the incidence of major adverse cardiovascular diseases (MACEs) during follow-up were determined.

RESULTS

Overall, 737 patients were included. The NLR was positively correlated with the severity of coronary lesions as assessed by Gensini score (P < 0.05). During the follow-up period (mean, 43.49 ± 23.97 months), 65 MACEs occurred. No significant association was detected between baseline NLR and the risk of MACEs during follow-up by either Kaplan-Meier or Cox regression analysis. Multivariable logistic regression analysis showed that a higher NLR was independently associated with coronary lesion severity as measured by the Gensini score (1st tertile vs. 3rd tertile hazard ratio [HR]: 0.527, P < 0.001, and 2nd tertile vs. 3rd tertile HR: 0.474, P = 0.025).

CONCLUSIONS

The NLR may be associated with coronary disease severity at baseline but is not associated with adverse outcomes in patients with new-onset ACS.

ETHICS APPROVAL NUMBER

2019XE0208.

The Association between Neutrophil-to-Lymphocyte Ratio and Diabetic Depression in U.S. Adults with Diabetes: Findings from the 2009-2016 National Health and Nutrition Examination Survey (NHANES)

Objective

To determine the association between neutrophil-to-lymphocyte ratio (NLR) and clinically relevant depressive symptoms in people with diabetes.

Methods

This cross-sectional study was conducted among adults (age >18) with diabetes in the National Health and Nutrition Examination Survey (NHANES) between 2009 and 2016. NLR was calculated from complete blood count. Nine-item Patient Health Questionnaire (PHQ-9) was used to measure depression, with scores ≥10 indicating the presence of clinically relevant symptoms. Multivariable logistic regression was used to calculate the odds ratio (OR) with 95% confidence interval (CI) of clinically relevant depressive symptoms in relation to the NLR. We performed the smooth curve fitting and established a weighted generalized additive model to identify the nonlinearity of NLR and depression in diabetes patients. To account for the nonlinear relationship between NLR and depression in diabetes patients, weighted two-piecewise linear model was applied.

Results

We included 2,820 eligible participants, of which 371 (12.4%) had clinically relevant depressive symptoms. In the unadjusted model, the OR (95% CI) of clinically relevant depressive symptoms for the second (NLR 1.75-2.57) and third (NLR >2.57) were 1.24 (0.90, 1.70) and 1.68 (1.23, 2.30), respectively, compared to the reference group (NLR < 1.75). After controlling for potential confounding factors, NLR was significantly associated with clinically relevant symptoms (odds ratio = 1.57, 95% confidence interval: 1.13–1.87; P for trend = .0078). Nonlinear relationships were observed, and a two-piecewise linear regression model was established. The inflection point of NLR was 2.87. To the left of the inflection point (NLR ≤ 2.87), the OR (95% CIs) was 1.33 (1.07–1.66) (P < .031).

Conclusions

Elevated levels of NLR are independently associated with increased odds of clinically relevant depressive symptoms in people with diabetes. Prospective study is needed to further analyze the role of NLR in depression in diabetic patients.

Positive association between systemic immune-inflammatory index and mortality of cardiogenic shock

BACKGROUND

Cardiogenic shock (CGS) is not only a state of hypoperfusion, but also related to inflammation. The prognostic value of systemic immune-inflammatory index (SII), an innovate biomarker of inflammation, in CGS patients has not been assessed. This study aims to explore the associations between SII and mortality in patients with CGS.

METHODS

Data on patients diagnosed with CGS were extracted from MIMIC-III database version 1.4. The follow-up started on the patients' first admission to ICU. The primary outcome was 30-day mortality. 90-day and 365-day mortality were the secondary outcomes. Cox proportional hazards models were used to investigate the associations between SII and mortality of CGS patients.

RESULTS

707 patients with CGS were included in our study (59.8% male, 67.5% the white, 70.27 ± 14.56 years). For 30-day mortality, the HR (95% CI) value of high-SII group was 2.17 (1.60, 2.93) compared with the reference of low-SII group (P < 0.0001). The HR value of mid-SII group, however, showed none statistical significance (HR: 1.03, 95% CI: 0.74-1.43, P = 0.8516). When adjusted for age, gender and ethnicity in Model I, the adjusted HR (95% CI) value of high-SII group was 2.28 (1.69, 3.09). When further adjusted for heart rate, SBP, serum potassium, PTT, INR and ECI in Model II, the adjusted HR value of high-SII group was still statistically significant (HR: 2.08, 95% CI: 1.52-2.86, P < 0.0001). Similar results were also shown in the secondary outcomes of 90-day and 365-day mortality.

CONCLUSIONS

High level of SII is associated with increased short- and long-term mortality of patients with CGS. SII, a readily available biomarker, can independently predict the prognosis of CGS patients.

Prognostic Value of Neutrophil-Lymphocyte Ratio in Cardiogenic Shock: A Cohort Study

BACKGROUND Inflammation plays an important part in the pathogenesis of cardiogenic shock (CGS). Whether the neutrophil-lymphocyte ratio (NLR), an integrated biomarker of inflammation, is associated with the outcome of CGS patients remains unknown. This retrospective cohort study was performed to identify the utility of using NLR among patients with CGS. MATERIAL AND METHODS Data were extracted from the MIMIC database. We applied smooth curve fitting to define the NLR cutoff values. The primary outcome was 30-day mortality. Cox proportional hazards models, subgroup analysis, and receiver operator characteristic (ROC) curve analysis were performed. RESULTS A total of 1470 CGS patients were extracted, among which 801 (54.5%) were men. The mean age of the population was 70.37 years. An inverse U-shaped relationship was observed between NLR and mortality in CGS patients, with the highest risk being at values ranging from 9.4 to 15. For the primary outcome of 30-day mortality, the adjusted HR (95% CI) values of the middle tertile (NLR 9.4-15) and the upper tertile (NLR >15) were 1.47 (1.14, 1.88) and 1.22 (0.94, 1.57) compared with the reference of lower tertile (NLR <9.4). ROC curve analysis showed that NLR had a more sensitive prognostic value in predicting 30-day mortality of CGS than the neutrophil or lymphocyte percentage alone (0.660 vs. 0.540, 0.549). CONCLUSIONS An inverse U-shaped curve was presented between NLR and the mortality of CGS. NLR seemed to be a readily available and independent prognostic biomarker for patients with CGS. The prognostic value of NLR was more sensitive than the neutrophil or lymphocyte percentage alone, but not as good as SOFA or SAPSII score.

Monocyte lymphocyte ratio predicts the new-onset of chronic kidney disease: A cohort study

BACKGROUND AND AIMS

The role of monocyte lymphocyte ratio (MLR) in predicting the risk of chronic kidney disease (CKD) is unclear, although inflammation contributes to the development of CKD. This study aimed to investigate whether elevated MLR predicts new-onset CKD.

METHODS

This study enrolled 14,033 consecutively Chinese participants. The primary outcome was the new-onset CKD defined as an estimated glomerular filtration rate <60 mL/min/1.73 m² or the presence of proteinuria after follow-up. After the descriptive analyses of baseline data, Univariate and multivariate Cox proportional models were used to evaluate the independent relationship between MLR and new-onset CKD.

RESULTS

11,280 participants were included in the final analysis, and 58.44% (n = 6592) of them were male. The mean age was 44.67 ± 12.85 years. After a median follow-up of 1.94 years, 2.55% (n = 288) of participants developed new-onset CKD. MLR was associated with the increased risk of CKD (HR = 16.12, 95% CI = 4.52-57.56, p < 0.0001). After adjustment for age, gender, body mass index, history of hypertension, systolic blood pressure, high-density lipoprotein cholesterol, triglyceride, fasting plasma glucose, uric acid and estimated glomerular filtration rate, MLR remained an independent risk factor for CKD (HR = 8.89, 95%CI = 2.18-36.27, p = 0.0023).

CONCLUSION

MLR is an independent predictor of the risk of CKD, which might be expected to better guide early prevention and treatment interventions.