Fluctuation in red cell distribution width predicts disseminated intravascular coagulation morbidity and mortality in sepsis: a retrospective single-center study

Predictive factors for disseminated intravascular coagulation following colorectal perforation

PURPOSE

To determine the relationship between postoperative disseminated intravascular coagulation (DIC) and patient prognosis after surgery for colorectal perforation and to identify preoperative predictive factors for DIC.

METHODS

We included 112 patients who underwent emergency surgery for colorectal perforation between April 2014 and September 2023. We performed a Kaplan-Meier analysis to assess 30-day postoperative survival with and without postoperative DIC, log-rank test to compare survival curves, and logistic regression analysis to identify preoperative predictive factors for postoperative DIC.

RESULTS

The postoperative DIC and 30-day mortality rates were 37.5 ​% and 8 ​%, respectively. The 30-day postoperative mortality rates significantly differed between patients with postoperative DIC and those without (16.7 ​% vs. 2.9 ​%). The preoperative Sequential Organ Failure Assessment (SOFA) score was an independent predictive factor for postoperative DIC.

CONCLUSION

Evaluating preoperative SOFA scores may help assess postoperative DIC risk and enable early initiation of anticoagulant therapy in patients undergoing surgery for colorectal perforation.

Association analysis of sepsis progression to sepsis-induced coagulopathy: a study based on the MIMIC-IV database

BACKGROUND

Sepsis-induced coagulopathy (SIC) is a severe complication of sepsis, characterized by poor prognosis and high mortality. However, the predictive factors for the development of SIC in sepsis patients remain to be determined. The aim of this study was to develop an easy-to-use and efficient nomogram for predicting the risk of sepsis patients developing SIC in the intensive care unit (ICU), based on common indicators and complications observed at admission.

METHODS

A total of 12, 455 sepsis patients from the MIMIC database were screened and randomly divided into training and validation cohorts. In the training cohort, LASSO regression was used for variable selection and regularization. The selected variables were then incorporated into a multivariable logistic regression model to construct the nomogram for predicting the risk of sepsis patients developing sepsis-induced coagulopathy (SIC). The model's predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC), and its calibration was assessed through a calibration curve. Additionally, decision curve analysis (DCA) was performed to evaluate the clinical applicability of the model. External validation was conducted using data from the ICU database of Xingtai People's Hospital.

RESULTS

Among the 12, 455 sepsis patients, 5, 145 (41. 3%) developed SIC. The occurrence of SIC was significantly associated with the SOFA score, red blood cell count, red cell distribution width (RDW), white blood cell count, platelet count, INR, and lactate levels. Additionally, hypertension was identified as a potential protective factor. A nomogram was developed to predict the risk of SIC, which showed an AUC of 0. 81 (95% CI: 0. 79-0. 83) in the training set, 0. 83 (95% CI: 0. 82-0. 84) in the validation set, and 0. 79 (95% CI: 0. 74-0. 84) in the external validation. The calibration curve of the nomogram showed good consistency between the observed and predicted probabilities of SIC.

CONCLUSIONS

The novel nomogram demonstrates excellent predictive performance for the incidence of SIC in ICU patients with sepsis and holds promise for assisting clinicians in early identification and intervention of SIC.

CLINICAL TRIAL

Not applicable.

Diagnostic Value of RDW-Albumin Ratio for the Prediction of Mortality in Sepsis Associated Nonthyroidal Illness Syndrome Patients: A Retrospective Cohort Study

Background

The correlation between RAR is linked to negative outcomes in sepsis, but it remains uncertain if RAR is connected to prognosis in patients with sepsis-related NTIS. So we investigated it in this study.

Methods

Patients with sepsis-associated NTIS admitted to Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, between March 2013 and April 2017 were included in the study. Participants were divided into two groups according to the optimal threshold value for RAR determined by the receiver operating characteristic curve. Cox proportional hazards regression and graphed with Kaplan-Meier curves examined the relationship between RAR and survival in patients with sepsis-associated NTIS. To account for potential confounding variables, a propensity score matching method was conducted to verify the relationship. Subgroup analysis was performed for different sex, age, comorbidities, infection location and other scores.

Results

A total of 328 patients with sepsis-related NTIS were analyzed in our study. The univariate and multivariate regression analysis indicated that RAR was a significant risk factor for 30-day mortality (HR 1.039(1.012, 1.067), p = 0.004). However, subgroup analysis suggested that RAR may not be an independent risk factor for 30-day mortality in sepsis patients with NTIS combined with tumor or urogenital infection. ROC analysis demonstrated that RAR had a high discriminatory ability for predicting 30-day mortality (AUC 0.751, p < 0.001). Kaplan-Meier curve analysis indicated increased 30-day mortality in the higher RAR group. Following PSM, 108 pairs of patients with matched scores were created. The multivariate regression model demonstrated that RAR was an independent factor associated with 30-day mortality risk (HR 1.049 (1.015, 1.085), p = 0.005). ROC analysis revealed that RAR was a strong discriminator for the 30d-mortality (AUC: 0.695, 95% CI: (0.598-0.792)).

Conclusion

A strong correlation was found between RAR and unfavorable clinical results in sepsis-related NTIS, where a greater RAR was linked to increased 30-day and in-hospital death rates.

Red blood cell distribution width to albumin ratio as a predictor of mortality in ICU patients with community acquired bacteremia

Bloodstream infections are globally occurring life-threatening diseases that impose significant societal and economic burdens. This study explored the red cell distribution width (RDW) to albumin ratio (RAR), a novel index derived from RDW, to investigate its relationship with prognosis of bacteremia using propensity score matching (PSM). This retrospective observational cohort study included patients with bacteremia admitted to Yantai Yuhuangding Hospital's intensive care units from June 2019 to December 2022. PSM was performed to adjust for confounding factors. The relationship between RAR and mortality was assessed using receiver operating characteristic curves, multivariate, and Kaplan-Meier analyses. A total of 411 patients were included. The RAR threshold of 5.824% /g/dL was determined by maximizing the Youden index; the study population was divided into two groups based on this cutoff value. After PSM, 125 pairs of score-matched patients were generated. Using logistic regression analysis, patients with RAR ≥ 5.824% /g/dL exhibited significantly higher mortality than did those with RAR ＜ 5.824% /g/dL in the entire cohort (OR = 3.926, 95% confidence interval (CI): 2.408-6.400, p < 0.001) and the PSM subset (OR = 2.460, 95% CI: 1.411-4.289, p = 0.040). RAR results were consistent when treated as continuous or four-categorical variables (based on quartiles). Similar outcomes were found for 28- and 90-day mortality and septic shock. The areas under the curves of RAR were 0.735, significantly higher than those of albumin or RAR alone. RAR emerges as an independent risk factor for mortality and septic shock in critically ill patients with community-acquired bacteremia, whether considered a continuous or categorized variable, irrespective of PSM adjustment.

Serum Anion Gap Level Predicts All-Cause Mortality in Septic Patients: A Retrospective Study Based on the MIMIC III Database

PURPOSE

Sepsis is a significant threat in the intensive care unit (ICU) worldwide because it has high morbidity and mortality rates. Early recognition and diagnosis of sepsis are essential for the prevention of adverse outcomes. The present study aimed to quantitatively assess the association between serum anion gap (AG) levels and 30- and 90-day all-cause mortality among sepsis patients.

METHODS

Clinical data of patients diagnosed with sepsis were extracted from the Medical Information Mart for Intensive Care III (MIMIC III) database. Kaplan-Meier curves and Cox proportional hazards models were used to evaluate the association between serum AG levels and all-cause mortality. A receiver operating characteristic (ROC) curve was drawn to quantify the efficacy of using the serum AG level to predict all-cause mortality.

RESULTS

A total of 3811 patients were included in the study. The Kaplan-Meier curves showed that patients with higher serum AG levels had a shorter survival time than those with lower levels. Serum AG levels were found to be highly effective in predicting all-cause mortality secondary to sepsis (30-day: AUROC = 0.703; 90-day: AUROC = 0.696). The Cox regression model further indicated that the serum AG level was an independent risk factor for 30- and 90-day mortality in sepsis (HR 3.44, 95% CI 2.97-3.99 for 30-day; HR 3.17, 95% CI 2.76-3.65 for 90-day, P < 0.001 for both).

CONCLUSIONS

High serum AG may be considered as an alternative parameter for predicting the death risk in sepsis when other variables are not immediately available. Prospective large-scale studies are needed to support its predictive value in the clinic.

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.

Establishment and Effectiveness Evaluation of a Scoring System-RAAS (RDW, AGE, APACHE II, SOFA) for Sepsis by a Retrospective Analysis

Background

Methods

Results

Conclusion

ΔRDW: A Novel Indicator with Predictive Value for the Diagnosis and Treatment of Multiple Diseases

Elevated red blood cell distribution width (RDW) is a powerful predictor of poor prognosis in a variety of diseases, but a single measurement of RDW cannot reflect the dynamic change of diseases. ΔRDW, as a risk stratification tool, can be used to record changes in RDW before and after treatment; also, it allows investigators to name the unit change of RDW in the studied population. So far, there have been few relevant studies on the predictive value of ΔRDW for different diseases; this article aims to review the studies and summaries of the current understandings on the correlation between ΔRDW and disease outcomes.

The Value of a Complete Blood Count (CBC) for Sepsis Diagnosis and Prognosis

Sepsis represents an important global health burden due to its high mortality and morbidity. The rapid detection of sepsis is crucial in order to prevent adverse outcomes and reduce mortality. However, the diagnosis of sepsis is still challenging and many efforts have been made to identify reliable biomarkers. Unfortunately, many investigated biomarkers have several limitations that do not support their introduction in clinical practice, such as moderate diagnostic and prognostic accuracy, long turn-around time, and high-costs. Complete blood count represents instead a precious test that provides a wealth of information on individual health status. It can guide clinicians to early-identify patients at high risk of developing sepsis and to predict adverse outcomes. It has several advantages, being cheap, easy-to-perform, and available in all wards, from the emergency department to the intensive care unit. Noteworthy, it represents a first-level test and an alteration of its parameters must always be considered within the clinical context, and the eventual suspect of sepsis must be confirmed by more specific investigations. In this review, we describe the usefulness of basic and new complete blood count parameters as diagnostic and prognostic biomarkers of sepsis.