Prognostic value of systemic immune-inflammation index, neutrophil-lymphocyte ratio, and thrombocyte-lymphocyte ratio in critically ill patients with moderate to severe traumatic brain injury.

Traumatic brain injury (TBI) is a significant health problem with a high mortality rate. Inflammatory markers can predict the prognosis of TBI where neuroinflammation is essential. In this study, the prognostic value of the systemic immune-inflammation index (SII), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) at admission in patients with critical TBI was investigated. Patients with moderately severe TBI in the intensive care unit (ICU) of a tertiary center between June 2020 and June 2022 were retrospectively reviewed. Patients were classified into survivor and mortality groups. The predictive performance of SII, PLR, and NLR levels calculated from blood results at admission and 28-day mortality and patient outcomes were analyzed. One hundred sixty-one patients were included in this study. The median age of the entire population was 41 (18-90) years, and 80.7% (n = 130) of the patients were male. Falls (42.2%) and traffic accidents (40.4%) were the most common causes of TBI. The most common primary diagnoses in patients with TBI were acute subdural hematoma (30.4%) and subarachnoid hemorrhage (26.1%). The SII and NLR levels were significantly higher in the mortality group, and PLR levels were significantly lower (P = .004, P < .001, P < .001, respectively). In multivariate regression analysis, SII and PLR were independent predictors of mortality (P = .031 and P < .001, respectively). In the receiver operating characteristics (ROC) curve analysis, the cutoff value for SII was ≥ 2951, and the area under the curve (AUC) was 0.662 (95% CI, 0.540-0.784). The cutoff value for NLR was ≥ 9.85, AUC was 0.717 (95% CI, 0.600-0.834), and the cutoff value for PLR was ≤ 130.4, AUC was 0.871 (95% CI, 0.796-0.947). 28-day mortality was 21.1%. Neuroinflammation is essential in patients with critical TBI, and inflammatory markers SII, NLR, and PLR have prognostic importance. SII and PLR are independent predictors of mortality. Early detection of those with a poor prognosis in critically ill TBI patients and planning aggressive treatments may contribute to reducing mortality.

Arslan K ，Sahin AS 《-》

Predictive role of neutrophil percentage-to-albumin ratio, neutrophil-to-lymphocyte ratio, and systemic immune-inflammation index for mortality in patients with MASLD.

There are no studies discussing the significance of neutrophil-to-lymphocyte ratio (NLR), neutrophil-percentage-to-albumin ratio (NPAR), and systemic immune-inflammation index (SII) in predicting poor prognosis in patients with metabolic dysfunction associated steatotic liver disease (MASLD); this study aimed to investigate the relationship between these three inflammatory markers and all-cause mortality and cardiovascular disease (CVD) mortality in patients with MASLD. Survival data for 3970 participants were obtained from National Death Index (NDI) records associated with the National Health and Nutrition Examination Survey (NHANES) dataset, the associations of NPAR, NLR, and SII with all-cause and CVD mortality were analyzed using multivariate COX regression modeling, restricted cubic spline (RCS) was used to explore nonlinear relationships and to determine the inflection point, regrouping was done according to the nonlinear inflection point, using multivariate COX regression modeling, subgroup analysis, and the Kaplan-Meier survival curves to evaluate differences in risk of death between the two groups. Time-dependent receiver operating characteristic curve (ROC) analysis was conducted to assess the predictive efficacy of NPAR, NLR, and SII on survival outcomes. Multivariate COX regression and RCS analyses revealed a positive linear correlation between NLR and all-cause and CVD mortality, whereas a nonlinear relationship was found between NPAR and SII and all-cause and CVD mortality. Further reclassified into two groups according to the inflection point, multivariate COX regression analyses showed a significant difference in the risk of death between the two NPAR groups (HR 1.37, 95% CI = (1.01, 1.86) for all-cause mortality and HR 2.03, 95% CI = (1.24, 3.32) for CVD mortality ) and no difference in the risk of death between the two SII groups (HR 1.11, 95% CI = (0.87, 1.42) for all-cause mortality and HR 1.35, 95% CI = (0.86, 2.12) for CVD mortality), and Kaplan-Meier survival curves showed that both all-cause and CVD mortality rates were higher in patients with MASLD above the NPAR inflection point (log-rank P < 0.05). Subgroup analyses showed that the associations between high levels of NPAR and all-cause mortality were generally consistent across populations (P interaction > 0.05). Also, COPD subgroups had a significant effect on the correlation between high levels of NPAR and CVD mortality (P interaction < 0.05). Time-dependent ROC show the predictive value of NPAR, NLR, and SII for all-cause and CVD mortality in MASLD patients. The correlation between NPAR and mortality was nonlinear, and NLR was linearly and positively correlated with mortality, Measuring NPAR and NLR may be useful in assessing risk and predicting prognosis in populations of patients with MASLD.

Dong K ，Zheng Y ，Wang Y ，Guo Q ... -  《Scientific Reports》

Systemic immune-inflammation index and serum glucose-potassium ratio predict poor prognosis in patients with spontaneous cerebral hemorrhage: An observational study.

Recent studies have shown systemic inflammatory response, serum glucose, and serum potassium are associated with poor prognosis in spontaneous intracerebral hemorrhage (SICH). This retrospective study aimed to investigate the association of systemic immune-inflammatory index (SII) and serum glucose-potassium ratio (GPR) with the severity of disease and the poor prognosis of patients with SICH at 3 months after hospital discharge. We reviewed the clinical data of 105 patients with SICH, assessed the extent of their disease using Glasgow Coma Scale score, National Institutes of Health Stroke Scale (NIHSS) score, and hematoma volume, and categorized them into a good prognosis group (0-3 scores) and a poor prognosis group (4-6 scores) based on their mRS scores at 3 months after hospital discharge. Demographic characteristics, clinical, laboratory, and imaging data at admission were compared between the 2 groups, bivariate correlations were analyzed using Spearman's correlation coefficients, multivariate logistic regression analysis was used to determine the independent risk factors for poor prognosis of patients with SICH, and finally, SII, GPR, and platelet/lymphocyte ratio (PLR) were examined using the subject's work characteristics (ROC) curve, lymphocyte/monocyte ratio (LMR), and neutrophil/lymphocyte ratio (NLR) for their predictive efficacy for poor prognosis. Patients in the poor prognosis group had significantly higher SII and serum GPR than those in the good prognosis group, and Spearman analysis showed that SII and serum GPR were significantly correlated with the admission Glasgow Coma Scale score as well as the NIHSS score and that SII and GPR increased with the increase in mRS score. Multivariate logistic regression analysis showed that admission NIHSS score, hematoma volume SII, GPR, NLR, and PLR were independently associated with poor patient prognosis. Analysis of the subjects' work characteristic curves showed that the areas under the SII, GPR, NLR, PLR, LMR, and coSII-GPR curves were 0.838, 0.837, 0.825, 0.718, 0.616, and 0.883. SII and GRP were significantly associated with disease severity and short-term prognosis in SICH patients 3 months after discharge, and SII and GPR had better predictive value compared with NLR, PLR, and LMR. In addition, coSII-GPR, a joint indicator based on SII and GPR, can improve the predictive accuracy of poor prognosis 3 months after discharge in patients with SICH.

Liu Y ，Qiu T ，Fu Z ，Wang K ，Zheng H ，Li M ，Yu G ... -  《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》

Prognostic role of Neutrophil-Lymphocyte Ratio and Platelet-Lymphocyte Ratio in critically ill COVID-19 patients: A retrospective study.

Wulandari W ，Syahrul MZ ，Ermayanti S ，Rofinda ZD ，Usman E ，Kurnia D ，Lailani M ... -  《-》