Inflammatory Biomarkers as Prognostic Factors of Acute Deep Vein Thrombosis Following the Total Knee Arthroplasty

Introduction Total hip arthroplasty (THA) is a standard orthopedic procedure. Deep vein thrombosis (DVT) and pulmonary embolism are potential life-threatening postoperative complications. Aim of the study This study aimed to assess the prognostic value of systemic inflammatory indices [monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelets-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI)] and their potential association with acute postoperative DVT. Materials and methods We designed a multicentric, retrospective, observational cohort study, including adult patients undergoing elective HTA. Patients were divided into two groups, the DVT and non-DVT groups. We investigated the development of acute DVT early, and at 4 weeks after surgery and also registered length of hospital stay and mortality. All demographic data and laboratory data, hematological indices were extracted from patients files. Results 199 patients were included. Of those, 12 (6.03%) developed DVT and 187 (93.97%) did not. There was no statistically significant difference between patient age, gender, BMI, smoking status or comorbidities. No difference was founds between the two groups regarding median values of MLR (0.31 vs 0.27, p=0.12), NLR (3.16 vs 2.42, p=0.27), PLR (163.39 vs 123.01, p=0.27), SII (660.26 vs 568.52, p=0.33), SIRI (67.5 vs 65.26, p=0.89) and AISI (302.35 vs 290.48, p=0.85). Length of hospital stay was not significantly different (median 9 days in the DVT group vs 7 days in the non-DVT group, p=0.38), but mortality was significantly higher in the DVT group (3 deaths vs none in the non-DVT group, p<0.001). Conclusion MLR, NLR, PRL, SII, SIRI and AISI were not associated with the development of acute DVT following HTA in our study population.

Immunoinflammatory response can participate in the development of cancer. To investigate the relationship between pretreatment systemic immune inflammatory response index (SII), systemic inflammatory response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR) and lymph node metastasis in patients with papillary thyroid carcinoma (PTC). A retrospective analysis was performed on 547 PTC patients treated in Meizhou People's Hospital from January 2018 to December 2021. Clinicopathological data were collected, including gender, age, Hashimoto's thyroiditis, maximum tumor diameter, extra-membrane infiltration, disease stage, BRAF V600E mutation, pretreatment inflammatory index levels, and lymph node metastasis. The optimal cutoff values of SII, SIRI, NLR, PLR and LMR were calculated by receiver operating characteristic (ROC) curve, and the relationship between inflammatory indexes and other clinicopathological features and lymph node metastasis was analyzed. There were 303 (55.4%) PTC patients with lymph node metastasis. The levels of SII, SIRI, NLR, and PLR in patients with lymph node metastasis were significantly higher than those in patients without lymph node metastasis, while the levels of LMR were significantly lower than those in patients without lymph node metastasis (all p<0.05). When lymph node metastasis was taken as the endpoint, the critical value of SII was 625.375, the SIRI cutoff value was 0.705, the NLR cutoff value was 1.915 (all area under the ROC curve >0.6). The results of regression logistic analysis showed that age <55 years old (OR: 1.626, 95% CI: 1.009-2.623, p=0.046), maximum tumor diameter >1cm (OR: 2.681, 95% CI: 1.819-3.952, p<0.001), BRAF V600E mutation (OR: 2.709, 95% CI: 1.542-4.759, p=0.001), SII positive (≥625.375/<625.375, OR: 2.663, 95% CI: 1.560-4.546, p<0.001), and NLR positive (≥1.915/<1.915, OR: 1.808, 95% CI: 1.118-2.923, p=0.016) were independent risk factors for lymph node metastasis of PTC. Age <55 years old, maximum tumor diameter >1cm, BRAF V600E mutation, SII positive, and NLR positive were independent risk factors for lymph node metastasis in PTC.

Is to assess the diagnostic and prognostic role of different inflammatory indices in patients with benign and malignant thyroid nodules. The neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR), derived NLR (dNLR), systemic inflammation index (SII), neutrophil to lymphocyte, platelet ratio (NLPR), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) were assessed in150 thyroid cancer (TC) patients, 75 benign nodule patients, compared to 70 healthy controls. There was a significant difference among TC patients and control group regarding the PLR, LMR, SII, NLPR, SIRI, and AISI (p = 0.006, p < 0.001, p = 0.043,p < 0.001 p < 0.001, and p < 0.001; respectively). LMR and SIRI could efficiently differentiate malignant versus benign thyroid nodules at a cutoff of 5.2 and 0.597; respectively. LMR, PLR, SIRI, and AISI were notably associated with high-risk stratification of TC patients (p = 0.011, p = 0.035, p = 0.036, and p = 0.034; respectively). Moreover, PLR was significantly elevated in TC patients with lymph node (LN) metastasis (p = 0.010). The LMR (OR = 0.318, p < 0.001), SIRI (OR = 2.293, p = 0.001), AISI (OR = 2.714, p < 0.001), and FT4 (OR = 0.250, p < 0.001) could differentiate TC against non-TC groups. LMR, SIRI, AISI, and FT4 are independent risk factors for TC (p < 0.001, p = 0.030, p = 0.026, and p < 0.001; respectively). There was no significant impact of the assessed inflammatory indices on the disease-free survival of the patients. LMR, PLR, SII, NLPR, SIRI, and AISI could be potential supportive markers for TC diagnosis. LMR and SIRI could help in differentiating malignant versus benign thyroid nodules.

The study aimed to evaluate the accuracy with which various nutritional and inflammatory indicators, including Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), Systemic Immune-Inflammation Index (SII), Monocyte-to-Lymphocyte Ratio (MLR), Systemic Inflammatory Response Index (SIRI), and Prognostic Nutritional Index (PNI), can predict the severity of acute calculus cholecystitis. 109 cases of chronic calculus cholecystitis (CCC) and 130 cases of acute calculus cholecystitis (ACC), including 62 cases of acute simple cholecystitis (ASC), 35 cases of acute purulent cholecystitis (APC), and 33 cases of acute gangrenous cholecystitis (AGC), were encompassed in the retrospective cohort study. The patients' clinical information and inflammatory-immune markers were collected for analysis. The optimal cut-off values for NLR, SIRI, SII, MLR, PLR, and PNI in distinguishing ACC from CCC were determined to be 2.499, 0.964, 593.5, 0.230, 148.0, and 141.3, respectively. NLR > 2.499 demonstrated the highest predictive capability, with an AUC of 0.896. Multivariate analysis indicated that NLR > 2.499 (OR: 4.69, p = 0.006) was the dominant factor in differentiating ACC from CCC. The optimal cut-off values for SII, SIRI, MLR, NLR, PLR, and PNI in distinguishing ASC from APC were 1098, 2.092, 0.304, 4.082, 191.1, and 135.3, respectively. SII > 1098 exhibited the highest predictive capability, with an AUC of 0.73. The optimal cut-off values for NLR, SIRI, MLR, SII, and PLR in differentiating APC from AGC were 7.232, 4.773, 0.557, 2417, and 221.5, respectively. NLR > 7.232 demonstrated the highest predictive capability, with an AUC of 0.826. Systemic inflammatory index and nutritional marker can serve as valuable indicators for predicting acute calculus cholecystitis and its severity. An elevated systemic inflammatory index and a declining nutritional marker suggest an increased risk of severe cholecystitis, warranting prompt and appropriate interventions.

The aim of this study was to explore the relationship between functional prognosis and the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR) and systemic inflammatory response index (SIRI) in patients with acute ischemic stroke (AIS) at discharge. A total of 861 patients with AIS were enrolled between January 2019 and December 2021. Blood cell counts were collected on admission. Logistic regression analysis was performed to assess the relationship between NLR, PLR, LMR, SIRI and adverse functional outcomes (modified Rankin scale score of 3-6) at discharge. We also used receiver operating characteristic (ROC) curves to estimate the overall ability of NLR, PLR, LMR and SIRI to judge short-term functional outcomes. Associations between NLR, PLR, LMR, and SIRI with length of hospital stay were analyzed by Spearman correlation test. A total of 194 patients (22.5%) had poor functional outcomes at discharge. Multivariate logistic regression analysis showed that NLR (odds ratio [OR], 1.060; 95% confidence interval [CI] 1.004-1.120, P=0.037), PLR (OR, 1.003; 95% CI 1.000-1.005, P=0.018), LMR (OR, 0.872; 95% CI 0.774-0.981, P=0.023) and SIRI (OR, 1.099; 95% CI 1.020-1.184, P=0.013) were independent factors for poor functional outcome. The odds ratios of the highest versus lowest quartiles of NLR, PLR and SIRI were 2.495 (95% CI 1.394-4.466), 1.959 (95% CI 1.138-3.373) and 1.866 (95% CI 1.106-3.146), respectively. The odds ratio of the lowest versus highest quartile of LMR was 2.300 (95% CI 1.331-3.975). The areas under the curve (AUCs) of the NLR, PLR, LMR, and SIRI to discriminate poor functional prognosis were 0.644, 0.587, 0.628, and 0.651, respectively. NLR, LMR, and SIRI were related with the length of hospital stay (P<0.05). NLR, PLR, LMR, and SIRI were associated with functional outcome at discharge in AIS patients. NLR, LMR and SIRI were related to hospitalization days in patients with AIS.

PurposeStroke is a disease associated with high mortality. Many inflammatory indicators such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR) and red blood cell distribution width (RDW) have been documented to predict stroke prognosis, their predictive power is limited. A novel inflammatory indicator called systemic inflammatory response index (SIRI) has been advocated to have an essential role in the prognostic assessment of cancer and infectious diseases. In this study, we attempted to assess the prognosis of stroke by SIRI. Moreover, we compared SIRI with other clinical parameters, including NLR, PLR, LMR and RDW.MethodsThis was a retrospective cohort study. We obtained data of 2450 stroke patients from the Multiparametric Intelligent Monitoring in Intensive Care III database. We used the Cox proportional hazards models to evaluate the relationship between SIRI and all-cause mortality and sepsis. Receiver operating curve (ROC) analysis was used to assess the predictive power of SIRI compared to NLR, PLR, LMR and RDW for the prognosis of stroke. We collected data of 180 patients from the First Affiliated Hospital of Wenzhou Medical University, which used the Pearson’s correlation coefficient to assess the relationship between SIRI and the National Institute of Health stroke scale (NIHSS).ResultsAfter adjusting multiple covariates, we found that SIRI was associated with all-cause mortality in stroke patients. Rising SIRI accompanied by rising mortality. Besides, ROC analysis showed that the area under the curve of SIRI was significantly greater than for NLR, PLR, LMR and RDW. Besides, Pearson’s correlation test confirmed a significant positive correlation between SIRI and NIHSS.ConclusionElevated SIRI was associated with higher risk of mortality and sepsis and higher stroke severity. Therefore, SIRI is a promising low-grade inflammatory factor for predicting stroke prognosis that outperformed NLR, PLR, LMR, and RDW in predictive power.

Objective: To analyze the comprehensive blood inflammation index of the patients with stage I pneumoconiosis complicated with pulmonary infection, and to explore its value in predicting the patients' disease. Methods: In September 2023, 83 patients with stage I pneumoconiosis who were treated in Tianjin Occupational Diseases Precaution and Therapeutic Hospital from November 2021 to August 2023 were selected and divided into non-infected group (56 cases) and infected group (27 cases) according to whether they were combined with lung infection. Workers with a history of dust exposure but diagnosed without pneumoconiosis during the same period were selected as the control group (65 cases) . By referring to medical records and collecting clinical data such as gender, age, occupational history, past medical history, hematology testing, the differences in the comprehensive blood inflammation indexes among the three groups were compared, ROC curve was drawn, and the relationship between comprehensive blood inflammation indexes and stage I pneumoconiosis and its combined lung infection was analyzed. Results: There were significtant differences in the number of neutrophils (N) , the number of lymphocytes (L) , the number of monocytes (M) , C-reactive protein (CRP) , the neutrophil to lymphocyte ratio (NLR) , the monocyte to lymphocyte ratio (MLR) , the platelet to lymphocyte ratio (PLR) , the systemic immune-inflammatory index (SII) , the systemic inflammation response index (SIRI) , the aggregate index of systemic inflammation (AISI) , the derived neutrophil to lymphocyte ratio (dNLR) , the neutrophil to lymphocyte and platelet ratio (NLPR) , and the C-reactive protein to lymphocyte ratio (CLR) (P<0.05) . Compared with the control group, MLR, SIRI and AISI in the non-infected group were significantly increased (P<0.05) . NLR, MLR, PLR, SII, SIRI, AISI, dNLR, NLPR, CLR were significantly increased (P<0.05) . Compared with the non-infected group, NLR, PLR, SII, SIRI, AISI, dNLR, NLPR and CLR were significantly increased in the infected group (P<0.05) . ROC analysis showed that NLR, MLR, PLR, SII, SIRI and AISI had a certain predictive capability for stage I pneumoconiosis (P<0.05) , among which MLR had the highest efficacy, with an AUC of 0.791 (95% CI: 0.710-0.873) , the cut-off value was 0.18, the sensitivity was 71.4%, and the specificity was 78.5%. NLR, MLR, PLR, SII, SIRI, AISI, dNLR, NLPR and CLR all had a certain predictive capability forstage I pneumoconiosis combined lung infection (P<0.05) , among which CLR had the highest efficacy, with an AUC of 0.904 (95%CI: 0.824~0.985) , the cut-off value was 5.33, sensitivity was 77.8%, specificity was 98.2%. Conclusion: The comprehensive blood inflammation index may be an auxiliary predictor of stage I pneumoconiosis and its combined lung infections.

AimPeriprosthetic joint infection (PJI) is a devastating complication that develops after total joint arthroplasty (TJA) whose incidence is expected to increase over the years. Traditionally, surgical treatment of PJI has been based on algorithms, where early infections are preferably treated with debridement, antibiotics, and implant retention (DAIR), while late infections with two-stage revision surgery. Two-stage revision is considered the “gold standard” for treatment of chronic PJI. In this observational retrospective study, we investigated the potential role of inflammatory blood markers (neutrophil-to- lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII)], systemic inflammatory response index (SIRI), and aggregate index of systemic inflammation (AISI)) as prognostic factors in two-stage exchange arthroplasty for PJI.MethodA single-center retrospective analysis was conducted, collecting clinical data and laboratory parameters from patients submitted to prosthetic explantation for chronic PJI. Laboratory parameters (PCR, NLR, MLR, PLR, SIRI, SII and AISI) were evaluated at the explantation time, at 4, 6, 8 weeks after surgery and at reimplantation time. Correlation between laboratory parameters and surgery success was evaluated, defined as infection absence/resolution at the last follow upResults57 patients with PJI were evaluated (62% males; average age 70 years, SD 12.14). Fifty-three patients with chronic PJI were included. Nineteen patients completed the two-stage revision process. Among them, none showed signs of re-infection or persistence of infection at the last available follow up. The other twenty-three patients did not replant due to persistent infection: among them, some (the most) underwent spacer retention; others were submitted to Girdlestone technique or chronic suppressive antibiotic therapy. Of the patients who concluded the two-stage revision, the ones with high SIRI values (mean 3.08 SD 1.7, p-value 0.04) and MLR values (mean 0.4 SD 0.2, p-value 0.02) at the explantation time were associated with a higher probability of infection resolution. Moreover, higher variation of SIRI and PCR, also defined respectively delta-SIRI (mean −2.3 SD 1.8, p-value 0.03) and delta-PCR (mean −46 SD 35.7, p-value 0.03), were associated with favorable outcomesConclusionsThe results of our study suggest that, in patients with PJI undergoing two-stage, SIRI and MLR values and delta-SIRI and delta-PCR values could be predictive of favorable outcome. The evaluation of these laboratory indices, especially their determination at 4 weeks after removal, could therefore help to determine which patients could be successfully replanted and to identify the best time to replant.

Background: Numerous tools, including nutritional and inflammatory markers, have been evaluated as the predictors of poor outcomes in COVID-19 patients. This study aims to verify the predictive role of the prognostic nutritional index (PNI), CONUT Score, and inflammatory markers (monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)) in cases of deep vein thrombosis (DVT) and acute pulmonary embolism (APE) risk, as well as mortality, in COVID-19 patients. Methods: The present study was designed as an observational, analytical, retrospective cohort study, and included 899 patients over the age of 18 who had a COVID-19 infection, confirmed through real time-polymerase chain reaction (RT-PCR), and were admitted to the County Emergency Clinical Hospital and Modular Intensive Care Unit of UMFST “George Emil Palade” of Targu Mures, Romania between January 2020 and March 20212. Results: Non-Surviving patients were associated with a higher incidence of chronic kidney disease (p = 0.01), cardiovascular disease (atrial fibrillation (AF) p = 0.01; myocardial infarction (MI) p = 0.02; peripheral arterial disease (PAD) p = 0.0003), malignancy (p = 0.0001), tobacco (p = 0.0001), obesity (p = 0.01), dyslipidemia (p = 0.004), and malnutrition (p < 0.0001). Multivariate analysis showed that both nutritional and inflammatory markers had a high baseline value and were all independent predictors of adverse outcomes for all enrolled patients (for all p < 0.0001). The presence of PAD, malignancy, and tobacco, were also independent predictors of all outcomes. Conclusions: According to our findings, higher MLR, NLR, PLR, SII, SIRI, AISI, CONUT Score, and lower PNI values at admission strongly predict DVT risk, APE risk, and mortality in COVID-19 patients. Moreover, PAD, malignancy, and tobacco, all predicted all outcomes, while CKD predicts APE risk and mortality, but not the DVT risk.

Objectives:To uncover the predictive value of systemic immune-inflammatory index (SII) and systemic inflammatory response index (SIRI) on early pregnancy loss.Methods:A total of 535 individuals were enrolled in this retrospective analysis. The early pregnancy losses (EPL) group included patients between 18-35 years old who experienced EPL. The control group comprised healthy pregnant women who gave birth at ≥37 weeks.Results:The EPL group had significantly lower plateletcrit (p=0.04), platelet distribution width (PDW, p<0.0001), and RDW (p<0.0001) and higher monocyte (p<0.0001) and SIRI (p<0.0001) values than the control group. The hemoglobin, white blood cells, platelet count, neutrophil count, lymphocyte count, mean platelet volume, neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and SII values were not significantly different between the EPL and control groups (p>0.05). The cut-off value for the SIRI that offers the best sensitivity/specificity balance was 1.48 (sensitivity of 63%; specificity of 63%) in the receiver operating characteristics curve. Among the inflammatory parameters for predicting EPL, PDW had highest specificity (84%), and RDW had the highest sensitivity (80%).Conclusion:This study provides compelling evidence that various inflammatory pathways may significantly contribute to EPL pathogenesis. Moreover, our findings suggest that SIRI could be a more effective marker than NLR, PLR, MLR, and SII in predicting EPL in an ongoing pregnancy, thereby potentially revolutionizing early pregnancy loss diagnostics.

IntroductionWe analyzed the correlation between systemic immune inflammatory index (SII), systemic inflammatory response index (SIRI), systemic inflammatory index (AISI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and mortality in patients with bloodstream infection to determine their application potential in predicting the prognosis of bloodstream infection.MethodsWe calculated SII, SIRI, AISI, NLR, PLR, and MLR in 469 patients with bloodstream infections. Logistic regression modeling, generalized additive modeling (GAM), and smoothed curve fitting were used to investigate the correlation of SII and other inflammatory markers with mortality in patients with bloodstream infections. Area under the curve (AUC) of ROC was used to assess the predictive effect of SII and other inflammatory markers.ResultsLevels of SII, SIRI, AISI, NLR, PLR, and MLR were significantly higher in the mortality group of this study (P < 0.05). There were significant differences in gender, age, diabetes, cardiovascular disease, respiratory disease, NEUT and LUMPH between the survival group and the death group (p < 0.05). Smooth curve fitting and GAM showed that SII and NLR had a non-linear relationship with death. After adjustment, the breakpoints (K) were 1711 and 7.22, respectively (P < 0.05), and there was a positive correlation on both sides of the breakpoint. The comparison of AUC values showed that SII and NLR had higher accuracy in predicting the risk of death in patients with bloodstream infection.ConclusionStudies demonstrates that SII and NLR are more predictive of mortality risk in patients with bloodstream infections. Patients with diabetes, cardiovascular disease, or respiratory disease should be monitored regularly for SII and NLR indicators to reduce the risk of death.

Periprosthetic joint infection (PJI) is a devastating complication that develops after total joint arthroplasty (TJA), whose incidence is expected to increase over the years. Traditionally, surgical treatment of PJI has been based on algorithms, where early infections are preferably treated with debridement, antibiotics, and implant retention (DAIR) and late infections with two-stage revision surgery. Two-stage revision is considered the "gold standard" for treatment of chronic prosthetic joint infection (PJI) as it enables local delivery of antibiotics, maintenance of limb-length and mobility, and easier reimplantation. Many studies have attempted to identify potential predicting factors for early diagnosis of PJI, but its management remains challenging. In this observational retrospective study, we investigated the potential role of inflammatory blood markers (neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), systemic inflammatory response index (SIRI), and aggregate index of systemic inflammation (AISI)) as prognostic factors in two-stage exchange arthroplasty for PJI. A single-center retrospective analysis was conducted, collecting clinical data and laboratory parameters from patients submitted to prosthetic explantation (EP) for chronic PJI. Laboratory parameters (PCR, NLR, MLR, PLR, SIRI, SII, and AISI) were evaluated at the explantation time; at 4, 6, and 8 weeks after surgery; and at reimplantation time. The correlation between laboratory parameters and surgery success was evaluated and defined as infection absence/resolution at the last follow-up. A total of 57 patients with PJI were evaluated (62% males; average age 70 years, SD 12.14). Fifty-three patients with chronic PJI were included. Nine patients underwent DAIR revision surgery and chronic suppressive therapy; two patients died. Nineteen patients completed the two-stage revision process (prosthetic removal, spacer placement, and subsequent replanting). Among them, none showed signs of reinfection or persistence of infection at the last available follow-up. The other twenty-three patients did not replant due to persistent infection: among them, some (the most) underwent spacer retention; others (fewer in number) were submitted to resection arthroplasty and arthrodesis (Girdlestone technique) or chronic suppressive antibiotic therapy; the remaining were, over time, lost to follow-up. Of the patients who concluded the two-stage revision, the ones with high SIRI values (mean 3.08 SD 1.7 and p-value 0.04) and MLR values (mean 0.4 SD 0.2 and p-value 0.02) at the explantation time were associated with a higher probability of infection resolution. Moreover, higher variation in the SIRI and PCR, also defined, respectively, as delta-SIRI (mean -2.3 SD 1.8 and p-value 0.03) and delta-PCR (mean -46 SD 35.7 and p-value 0.03), were associated with favorable outcomes. The results of our study suggest that, in patients with PJI undergoing EP, the SIRI and MLR values and delta-SIRI and delta-PCR values could be predictive of a favorable outcome. The evaluation of these laboratory indices, especially their determination at 4 weeks after removal, could therefore help to determine which patients could be successfully replanted and to identify the best time to replant. More studies analyzing a wider cohort of patients with chronic PJI are needed to validate the promising results of this study.

Asthma, a chronic respiratory disease, is characterized by inflammation and narrowing of bronchi, affecting 300 million people worldwide. Cellular markers neutrophil-to-lymphocyte ratio (NLR), eosinophils-to-lymphocyte ratio (ELR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic inflammatory index (SII), and systemic inflammatory response index (SIRI) reported individually in the assessment of asthma. However, there is no comprehensive approach using correlation between these multiple markers and oxidative stress (OS) in assessing severity of the condition. For the present hospital-based study, blood samples were collected from 200 individuals containing equal number of asthma patients (61% severe, 39% non-severe) and healthy volunteers. Samples were processed for serum MDA (sMDA) and complete blood picture; cell based ratios and indices were calculated (NLR, ELR, PLR, MLR, SII, and SIRI). We found higher values for all the parameters in the asthma patients over healthy controls (p < 0.05) and PLR, SII, and sMDA between severe and non-severe cases. Receiver operating characteristic (ROC) curve analysis showed good area under curve (AUC), specificity and sensitivity (ELR > PLR > SII > NLR) in patient and controls and in severe and non-severe cases (PLR > SII > NLR). Serum MDA exhibited correlation with all ratios and indices except ELR in patient group while no correlation in severe group. These results are suggestive of association of systemic cellular markers with OS in patients over controls. Heightened sMDA in severe cases appears to be independent of circulating cellular markers. As asthma is a progressive disease, understanding the severity requires longitudinal studies to develop novel inexpensive management strategies.

Background: Numerous tools, including inflammatory biomarkers and lung injury severity scores, have been evaluated as predictors of thromboembolic events and the requirement for intensive therapy in COVID-19 patients. This study aims to verify the predictive role of inflammatory biomarkers [monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)] and the CT Severity Score in acute limb ischemia (ALI) risk, intensive unit care (ICU) admission, and mortality in COVID-19 patients.; Methods: The present study was designed as an observational, analytical, retrospective cohort study and included all patients older than 18 years of age with a diagnosis of COVID-19 infection, confirmed through real time-polymerase chain reaction (RT-PCR), and admitted to the County Emergency Clinical Hospital of Targu-Mureș, Romania, and Modular Intensive Care Unit of UMFST “George Emil Palade” of Targu Mures, Romania between January 2020 and December 2021. Results: Non-Survivors and “ALI” patients were associated with higher incidence of cardiovascular disease [atrial fibrillation (AF) p = 0.0006 and p = 0.0001; peripheral arterial disease (PAD) p = 0.006 and p < 0.0001], and higher pulmonary parenchyma involvement (p < 0.0001). Multivariate analysis showed a high baseline value for MLR, NLR, PLR, SII, SIRI, AISI, and the CT Severity Score independent predictor of adverse outcomes for all recruited patients (all p < 0.0001). Moreover, the presence of AF and PAD was an independent predictor of ALI risk and mortality. Conclusions: According to our findings, higher MLR, NLR, PLR, SII, SIRI, AISI, and CT Severity Score values at admission strongly predict ALI risk, ICU admission, and mortality. Moreover, patients with AF and PAD had highly predicted ALI risk and mortality but no ICU admission.

Aim: Despite advances in diagnostic strategies, easily accessible biomarkers that can reliably predict pulmonary embolism (PE) in patients with deep vein thrombosis (DVT) are lacking. Recently, systemic inflammatory indices, such as the systemic immune-inflammation index (SII), systemic inflammatory response index (SIRI), and aggregate index of systemic inflammation (AISI), have been investigated as potential prognostic tools. This study aimed to evaluate the predictive value and clinical applicability of these markers in identifying PE in patients with lower extremity DVT. Material and Methods: A retrospective propensity score–matched cohort study was conducted in patients diagnosed with acute proximal lower extremity DVT. Two groups were compared: patients with isolated DVT and those with concurrent DVT and PE were compared. Propensity score matching yielded 290 patients in each group. Novel systemic inflammatory indices derived from hematological parameters (SII, SIRI, and AISI) were evaluated together with neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and traditional biomarkers (C-reactive protein (CRP) and D-dimer). Comparative analyses, logistic regression, and receiver operating characteristic (ROC) curve assessments were performed. Results: Inflammatory indices (NLR, PLR, SII, and SIRI) and conventional biomarkers (CRP and D-dimer) were higher in the DVT and PE group compared to the isolated DVT group (all p&lt;0.001). Multivariate analysis identified NLR, CRP, and D-dimer as independent predictors of PE. Receiver operating characteristic (ROC) analysis demonstrated the strongest diagnostic accuracy for CRP (AUC 0.811), followed by D-dimer (AUC 0.746) and NLR (AUC 0.735) levels. Conclusion: Easily measurable and low-cost biomarkers, particularly NLR, along with CRP and Ddimer, provide significant predictive value for PE in patients with DVT. These parameters may support early risk stratification and assist in clinical decision-making when advanced imaging is not readily available.