Development of Laboratory Parameters-Based Formulas in Predicting Short Outcomes for Adult Hemophagocytic Lymphohistiocytosis Patients with Different Underlying Diseases.

PURPOSE: Hemophagocytic lymphohistiocytosis (HLH) is a severe disease with high mortality. The purpose of this investigation was to build models to predict 30-day death in total and subgroup HLH patients based on available and cheap laboratory parameters. METHOD: The research contained 431 adults HLH patients from January 2015 to September 2021 in the hospital. Logistic regression and receiver operating characteristic (ROC) were utilized to build models. RESULTS: Results suggested that age, ferritin, lymphocyte (LY), international normalized ratio (INR), thrombin time (TT), globulin, uric acid (UA), chloride, activated partial thromboplastin time (APTT), aspartate aminotransferase (AST), triglycerides (TG), total bilirubin (TB), and indirect bilirubin (IB) were independent factors in HLH and subgroups. Then, models adapted to patients with different underlying diseases were established based on these factors. Area under curve (AUC) of these models was excellent: HLH patients: 0.838 (p < 0.001); infection-associated HLH (I-HLH) patients: 0.913 (p < 0.001); malignancy-associated HLH (M-HLH): 0.921 (p < 0.001) and 0.809 (p < 0.001) for two or more different etiologies-associated HLH (Mix-HLH patients). In addition, UA, TT, and chloride were firstly confirmed as independent factors in adult HLH. CONCLUSION: Four models depending on biomarkers that available and affordable in clinical practice were built. With these models, high-risk patients with different underlying diseases could be easily identified.

Prognostic Value of Lymphocyte-to-White Blood Cell Ratio for In-Hospital Mortality in Infective Endocarditis Patients.

Background: The prognosis of Infective endocarditis (IE) is poor, and we conducted this investigation to evaluate the worth of admission lymphocyte-to-white blood cell ratio (LWR) for prediction of short-term outcome in IE patients. Methods: We retrospectively assessed the medical records of 147 IE patients from January 2017 to December 2019. Patients were divided into the survivor group and nonsurvivor group. Univariate and multivariate analyses were applied to estimate the independent factors contribution to in-hospital death, and receiver-operator characteristic (ROC) curve was utilized to check the performance. Results: The levels of LWR (0.17 ± 0.08 vs. 0.10 ± 0.06) were significantly increased among the survivor group compared with the nonsurvivor group (P = 0.001). Multivariate analysis displayed that LWR (hazard ratio (HR): 1.755, 1.304-2.362, P < 0.001) was not interfered by other confounding factors for early death. Moreover, ROC analysis suggested that LWR (cutoff value = 0.10) performed the best among assessed indexes for the forecast of primary outcome (area under curve (AUC) = 0.750, 95% confidence interval (CI) = 0.634-0.867, P < 0.001, sensitivity = 70.0%, specificity = 76.4%), and the proportion of in-hospital mortality was remarkably inferior in patients with LWR > 0.10 than in those with LWR ≤ 0.10. (5.83% vs. 31.8%, P < 0.001). Conclusions: LMR is an independent, simple, universal, inexpensive, and reliable prognostic parameter to identify high-risk IE patients for in-hospital mortality.

The short-term prognostic value of serum platelet to hemoglobin in patients with type A acute aortic dissection.

PURPOSE: Type A acute aortic dissection (AAD) is an uncommon catastrophic cardiovascular disease with high pre-hospital mortality rate without timely and effectively treated. The aim of this study was to assess the value of serum platelet to hemoglobin (PHR) in predicting in-hospital mortality in type A AAD patients. METHODS: A total of 183 type A AAD patients were included in this retrospective investigation from January 2017 to December 2019. Admission blood routine parameters were gathered and PHR was computed. The outcome was all-cause in-hospital mortality within 30 days. RESULTS: The average levels of serum PHR were significant higher in survivor group than those in non-survivor group (1.14 ± 0.57 vs 0.87 ± 0.47, p = 0.006) and serum PHR was an independent factor associated with in-hospital mortality (hazard ratio (HR): 2.831; 95% confidence interval (CI): 1.108-7.231; p = 0.030). ROC noted that 0.8723 was chosen as the ideal cutoff value with a sensitivity of 64.3% and specificity of 72.5%. In addition, the area under the ROC curve (AUC) was 0.693 (95% CI 0.599-0.787, p < 0.001). CONCLUSION: Admission serum PHR can be used as an independent predictor of in-hospital mortality in patients with type A AAD.

A practical predictive model to predict 30-day mortality in neonatal sepsis.

OBJECTIVE: Neonatal sepsis is a serious disease that needs timely and immediate medical attention. So far, there is no specific prognostic biomarkers or model for dependable predict outcomes in neonatal sepsis. The aim of this study was to establish a predictive model based on readily available laboratory data to assess 30-day mortality in neonatal sepsis. METHODS: Neonates with sepsis were recruited between January 2019 and December 2022. The admission information was obtained from the medical record retrospectively. Univariate or multivariate analysis was utilized to identify independent risk factors. The receiver operating characteristic curve was drawn to check the performance of the predictive model. RESULTS: A total of 195 patients were recruited. There was a big difference between the two groups in the levels of hemoglobin and prothrombin time. Multivariate analysis confirmed that hemoglobin>133 g/L (hazard ratio: 0.351, p=0.042) and prothrombin time >16.6 s (hazard ratio: 4.140, p=0.005) were independent risk markers of 30-day mortality. Based on these results, a predictive model with the highest area under the curve (0.756) was built. CONCLUSION: We established a predictive model that can objectively and accurately predict individualized risk of 30-day mortality. The predictive model should help clinicians to improve individual treatment, make clinical decisions, and guide follow-up management strategies.

The association between systemic inflammatory response index and in-hospital mortality in patients with infective endocarditis.

BACKGROUND: Infective endocarditis (IE) has a significant mortality, and early identification of high-risk patients and prediction of poor outcomes is of great significance. In recent years, increasing research has revealed the predictors associated with infective endocarditis prognosis. Systemic inflammatory response index (SIRI) is an important new indicator of inflammation. So far, there have been no reports on the relationship between SIRI and the prognosis of IE patients. HYPOTHESIS: The purpose of this study was to explore the value of SIRI in predicting in-hospital death for patients with infective endocarditis (IE), so as to provide reference for improving the prognosis of patients with IE. METHOD: A retrospective analysis was performed on the clinical data of patients with IE admitted to the First Affiliated Hospital of Nanjing Medical University from January 2017 to December 2019. SIRI was calculated according to the blood routine results of patients at admission; receiver operating characteristic curve was employed to determined the optimal cutoff value of SIRI. Patients were divided into groups (low SIRI group and high SIRI group; nonsurvivor group and survivor group) according to the levels of SIRI or their prognosis, and the general clinical features of the two groups were compared. Univariate and multivariate logistic regression analysis were performed to analyze the independent prognostic factors of in-hospital death in IE patients. RESULTS: A total of 147 IE patients meeting the diagnostic criteria were included, including 102 males (69.4%) and 45 females (30.6%). There was statistically significant difference in SIRI level between nonsurvivor group and survivor group (p < .05). After adjusting for the related factors, the risk of in-hospital death in the high SIRI was still a risk of in-hospital death with statistical significance (hazard ratio = 5.053, 95% confidence interval: 1.426-17.905, p = .012). CONCLUSIONS: Higher SIRI level is independently associated with the risk of in-hospital death in IE patients, and can be an independent predictor of poor outcome in IE patients.

Prognostic Value of a Novel Parameter in Patients with Infective Endocarditis.

Background: Infective endocarditis (IE) has a high rate of mortality and the prognosis of IE was poor. The purpose of this investigation was to explore the value of lactate dehydrogenase (LDH)/lymphocyte and compare it with LDH/lymphocyte percentage (L-LWR) in predicting the in-hospital mortality in IE patients. Methods: The investigation cohort contained 147 IE patients between January 2017 and December 2019. We retrospectively went over the medical records and selected admission indexes. Results: Compared with IE patients with adverse events, significantly higher levels of LDH/lymphocyte and significantly lower levels of L-LWR were discovered in IE patients without adverse events. After adjustments, L-LWR (odds ratio (OR): 4.558, 95% confidence interval (CI) 1.362-15.256, P = 0.014) still maintained its significant independence. In addition, L-LWR had the highest area under curve (AUC) (0.780, 0.704-0.844, P < 0.001) with good sensitivity (81.89%) and specificity (65.00%) when 34 was selected as the best cutoff value. Conclusions: L-LWR is a reliable, low-priced, easily applicable, and independent prognostic parameter for in-hospital death with good performance in patients with IE.

The role of platelet to mean platelet volume ratio in the identification of adult-onset still's disease from sepsis.

OBJECTIVES: Inflammatory factors exert a significant role in the development of adult-onset Still's disease (AOSD) and sepsis. Although platelet counts and platelet parameters have long served as indicators for inflammatory diseases, their role in the differential diagnosis between adult-onset stills disease and sepsis remains unclear. We designed this retrospective study to explore whether the platelet to mean platelet volume (MPV) ratio (PMR) can help to distinguish AOSD from sepsis. METHODS: A total of 110 AOSD patients and 84 sepsis patients were enrolled in the study. Seventy-three AOSD patients and 56 sepsis patients between January 2010 and June 2017 were enrolled in the test cohort to analyze PMR values, which was then validated in the validation cohort (37 AOSD patients and 28 sepsis patients between June 2017 and December 2019). RESULTS: The values of PMR were significantly higher in AOSD patients than in sepsis patients (test cohort, validation cohort, and entire cohort), In the test cohort, logistic regression analysis showed that PMR was an independent risk factor of AOSD (odds ratios [OR]: 9.22, 95% confidence interval [CI] 2.15-39.46, p=0.003). Further receiver operating characteristic curve (ROC) analysis showed that the area under the ROC curve was 0.735 (95% CI 0.631-0.839, p<0.001) for PMR alone and 0.925 (95% CI 0.869-0.980, p<0.001) for the combination of PMR and serum ferritin. Consistently, the validation cohort exhibited analogous results. CONCLUSIONS: PMR could be used as a single indicator or a complementary indicator to distinguish AOSD from sepsis.

The role of platelet to mean platelet volume ratio in the identification of adult-onset still's disease from sepsis

OBJECTIVES: Inflammatory factors exert a significant role in the development of adult-onset Still's disease (AOSD) and sepsis. Although platelet counts and platelet parameters have long served as indicators for inflammatory diseases, their role in the differential diagnosis between adult-onset stilĺs disease and sepsis remains unclear. We designed this retrospective study to explore whether the platelet to mean platelet volume (MPV) ratio (PMR) can help to distinguish AOSD from sepsis. METHODS: A total of 110 AOSD patients and 84 sepsis patients were enrolled in the study. Seventy-three AOSD patients and 56 sepsis patients between January 2010 and June 2017 were enrolled in the test cohort to analyze PMR values, which was then validated in the validation cohort (37 AOSD patients and 28 sepsis patients between June 2017 and December 2019). RESULTS: The values of PMR were significantly higher in AOSD patients than in sepsis patients (test cohort, validation cohort, and entire cohort), In the test cohort, logistic regression analysis showed that PMR was an independent risk factor of AOSD (odds ratios [OR]: 9.22, 95% confidence interval [CI] 2.15-39.46, p=0.003). Further receiver operating characteristic curve (ROC) analysis showed that the area under the ROC curve was 0.735 (95% CI 0.631-0.839, p<0.001) for PMR alone and 0.925 (95% CI 0.869-0.980, p<0.001) for the combination of PMR and serum ferritin. Consistently, the validation cohort exhibited analogous results. CONCLUSIONS: PMR could be used as a single indicator or a complementary indicator to distinguish AOSD from sepsis.