Predictability of Neutrophil to Lymphocyte Ratio in preoperative elderly hip fracture patients for post-operative short-term complications: a retrospective study

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.

Complete Blood Count Ratios Predict Adverse Events After Total Joint Arthroplasty

INTRODUCTION

Complete blood count-based ratios (CBRs), including neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) are biomarkers associated with the proinflammatory surgical stress response. This study sought to determine whether preoperative CBRs are associated with postoperative complications, protracted hospital length of stay (LOS), and mortality after total joint arthroplasty, as well as establish threshold values for these outcomes for use in future investigations.

METHODS

The Premier Healthcare Database was retrospectively queried for adult patients who underwent primary elective total hip arthroplasty or total knee arthroplasty (TKA). Approximate cut-point values for CBRs were identified by bootstrap simulation using the Youden index. Multivariable adjusted restricted cubic spline models using the predicted cut-point value as the threshold for odds of outcomes were created to identify a final threshold value associated with increased adjusted odds ratio (aOR) of study outcomes.

RESULTS

A total of 32,868 total joint arthroplasties (THA: 12,807, TKA: 20,061) were identified. All measures predicted odds of aggregate postoperative complications (THA: NLR TV: 4.60 [aOR = 2.35], PLR TV: 163.4 [aOR = 1.32], MLR TV: 0.40 [aOR = 2.02], SII TV: 977.00 [aOR = 1.54]; TKA: NLR TV: 3.7 [aOR = 1.69], MLR TV: 0.41 [aOR = 1.62], PLR TV: 205.10 [aOR = 1.43], SII TV: 1,013.10 [aOR = 1.62]; all P < 0.05). A MLR > 0.40 [aOR = 1.54] P < 0.001) was associated with LOS ≥3 days after total hip arthroplasty while an NLR > 13.1 [aOR = 1.38] and an MLR > 0.41[aOR = 1.29] were associated with LOS ≥3 days after total knee arthroplasty (both P < 0.001). No association between inflammatory markers and inpatient mortality was observed.

CONCLUSION

Given CBRs' ability to both predict outcomes and identify patients with a proinflammatory phenotype, the findings of this study provide a framework for future investigations aimed at identifying and treating high-risk patients with immune-modulating therapies. Continued work to validate these findings by applying TVs to interventional clinical trials is needed before wide clinical adoption.

Association of neutrophil-lymphocyte ratio with all-cause and cardiovascular mortality in US adults with diabetes and prediabetes: a prospective cohort study

BACKGROUND

The neutrophil-lymphocyte ratio (NLR) is a novel hematological parameter to assess systemic inflammation. Prior investigations have indicated that an increased NLR may serve as a potential marker for pathological states such as cancer and atherosclerosis. However, there exists a dearth of research investigating the correlation between NLR levels and mortality in individuals with diabetes and prediabetes. Consequently, this study aims to examine the connection between NLR and all-cause as well as cardiovascular mortality in the population of the United States (US) with hyperglycemia status.

METHODS

Data were collected from a total of 20,270 eligible individuals enrolled for analysis, spanning ten cycles of the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. The subjects were categorized into three groups based on tertiles of NLR levels. The association of NLR with both all-cause and cardiovascular mortality was evaluated using Kaplan-Meier curves and Cox proportional hazards regression models. Restricted cubic splines were used to visualize the nonlinear relationship between NLR levels and all-cause and cardiovascular mortality in subjects with diabetes after accounting for all relevant factors.

RESULTS

Over a median follow-up period of 8.6 years, a total of 1909 subjects with diabetes died, with 671 deaths attributed to cardiovascular disease (CVD). And over a period of 8.46 years, 1974 subjects with prediabetes died, with 616 cases due to CVD. The multivariable-adjusted hazard ratios (HRs) comparing high to low tertile of NLR in diabetes subjects were found to be 1.37 (95% CI, 1.19-1.58) for all-cause mortality and 1.63 (95% CI, 1.29-2.05) for CVD mortality. And the correlation between high to low NLR tertile and heightened susceptibility to mortality from any cause (HR, 1.21; 95% CI, 1.03-1.43) and CVD mortality (HR, 1.49; 95% CI, 1.08-2.04) remained statistically significant (both p-values for trend < 0.05) in prediabetes subjects. The 10-year cumulative survival probability was determined to be 70.34%, 84.65% for all-cause events, and 86.21%, 94.54% for cardiovascular events in top NLR tertile of diabetes and prediabetes individuals, respectively. Furthermore, each incremental unit in the absolute value of NLR was associated with a 16%, 12% increase in all-cause mortality and a 25%, 24% increase in cardiovascular mortality among diabetes and prediabetes individuals, respectively.

CONCLUSIONS

The findings of this prospective cohort study conducted in the US indicate a positive association of elevated NLR levels with heightened risks of overall and cardiovascular mortality among adults with diabetes and prediabetes. However, potential confounding factors for NLR and the challenge of monitoring NLR's fluctuations over time should be further focused.

A Linear Regression Equation for Predicting the Residual Volume of Chronic Subdural Hematoma 1 Week After Surgery

Objective

The outcome of chronic subdural hematoma (CSDH) is influenced not only by the choice of treatment but also by various baseline characteristics. The main objective of this study is to identify the risk factors that can affect the prognosis of CSDH and develop a regression equation based on these risk factors.

Methods

A total of 212 patients with CSDH were included in the study. We collected clinical data including age, gender, and so on, and radiological data including preoperative hematoma volume (V1), effusion volume 1 day after surgery (V2), gas volume 1 day after surgery (V3), and so on. These were considered independent variables, while residual volume 1 week after surgery (V4) was the dependent variable. Univariate linear regression analysis was performed to identify factors that were significantly related. Subsequently, multivariate linear regression analysis was conducted to determine the relationship between each independent variable and the dependent variable. Multiple linear regression analysis was used to obtain a regression equation predicting V4.

Results

We have found that age (t = 3.109, P = 0.002), aspirin (t = 2.762, P = 0.006), hemostatic agents (haemocoagulase, t = 3.731, P < 0.001; vitamin K, t = 2.824, P = 0.005 < 0.05), V2 (t = 8.73, P < 0.001), and V3 (t = 5.968, P < 0.001) are significantly associated with V4. Furthermore, we have developed a regression equation that can predict this volume with CSDH. The fit of the model is robust with an R-squared value of 65.2% > 50%.

Conclusion

Age, aspirin, hemostatic agent, V2, and V3 are significantly associated with V4. We developed a regression equation to predict this volume with CSDH.

A Novel Approach to Staging and Detection of Colorectal Cancer in Early Stages

Colorectal cancer (CRC) is a significant problem affecting patients all over the world. Since it is the fourth most common cause of cancer-related deaths, many scientists aim to expand their knowledge on the detection in early stages and treatment of this disease. Chemokines, as protein parameters involved in many processes accompanying the development of cancer, constitute a group of potential biomarkers that could also be useful in the detection of CRC. For this purpose, our research team used the results of thirteen parameters (nine chemokines, one chemokine receptor and three comparative markers, i.e., CEA, CA19-9 and CRP) to calculate one hundred and fifty indexes. Moreover, for the first time, the relationship between these parameters during the ongoing cancer process and in comparison to a control group are presented. As a result of statistical analyses using patients' clinical data and the obtained indexes, it was established that several of the indexes have a diagnostic utility that is much higher than the tumor marker that is currently the most commonly used (CEA) currently. Furthermore, two of the indexes (CXCL14/CEA and CXCL16/CEA) showed not only extremely high usefulness in the detection of CRC in its early stages, but also the ability to determine whether the stage is low (stage I and II) or high (stage III and IV).