Assessment of leukocyte and systemic inflammation index ratios in dyslipidemia patients with dry eye disease: a retrospective case‒control study.

BACKGROUND: Dry eye disease (DED) is a complication of dyslipidemia (DLP) that is caused by metabolic syndrome and increased inflammation. This research aimed to assess leukocyte and systemic inflammation index ratios as potential biomarkers for systemic inflammation in dyslipidemia patients with dry eye disease (DLP-DED). METHODS: Several blood biomarkers were studied in 32 patients with DLP-DED (study group) and 63 patients with DLP-only (control group). The evaluated blood biomarkers included specific systemic inflammation index ratios, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and neutrophil-to-lymphocyte and platelet ratio (NLPR), and lipid profiles, such as total cholesterol (TC), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), triglyceride (TG), albumin (ALB), and C-reactive protein (CRP) levels. RESULTS: Lymphocyte levels were significantly greater in the DLP-DED group than in the DLP-only group (P = 0.044). In addition, a significant negative correlation between HDL and the NLPR (P = 0.007; r= -0.428) and a significant negative correlation between the serum ALB concentration and the PLR (P = 0.008; r= -0.420) were identified as potential inflammatory predictors of DLP-DED. CONCLUSION: The findings of this study suggest that patients with DLP-DED may benefit from routine blood monitoring of their elevated lipid profile and blood inflammatory biomarkers, such as CRP, leukocytes, and systemic inflammation index ratios (NLR, PLR, MLR, and NLPR), to reduce the complications of DLP on ocular health. The correlation data suggest that the NLPR, PLR, serum ALB concentration, and serum HDL concentration may be valuable inflammatory biomarkers in DLP-DED patients. More research is required to ascertain the significance of the NLR, PLR, MLR, and NLPR and the additive role that leukocytes play.

The Characteristics and Follow-Up of SARS-CoV-2 Infection in Pediatric Oncology Patients.

Introduction Clinical data about the first and second most prominent waves of SARS-CoV-2 among pediatric cancer patients were inconsistent. This study aims to retrospectively report the clinical characteristics and outcomes of SARS-CoV-2 infection in pediatric oncology patients. Methods This is an observational, retrospective study conducted in a tertiary care oncology center from March 2020 to May 2022. We reviewed the prevalence, severity of symptoms, and duration of positivity in relation to blood count laboratory data and mortality with a follow-up of 30 days post-infection for SARS-CoV-2. Results A total of 396 PCR tests were performed on 342 pediatric cancer patients. The overall rate of SARS-CoV-2 positivity was 43.1% (2.7% in the first wave and 95.4% in the second wave). Among 342 screened pediatric cancer patients, 72 patients had confirmed SARS-CoV-2 positivity in 92 different episodes. Nearly 59% had a mild or moderate infection, with fever and cough as the predominant presentations. The mean duration of positivity was 18.4±7.76 days. Comparing the laboratory values before and after acquiring the COVID-19 infection, only monocytes, hemoglobin, hematocrit, and platelets were statistically significantly affected, with P-values of 0.002, 0.03, 0.02, and 0.01, respectively. More than 18% of patients had grade 3 to 4 neutropenia (absolute neutrophil count=0.39±0.35) before COVID-19 infection and remained neutropenic throughout the disease, regardless of symptom severity. The mean recovery time was 13.67±8 days, which resulted in a delay in cancer treatment delivery of up to four weeks in 42.2% of patients. Conclusion Our data demonstrated that pediatric cancer patients with SARS-CoV-2 infection have a mild to moderate course of COVID-19 disease, with the majority being symptomatic, yet a great portion of our study population experienced treatment interruptions reaching up to four weeks caused by COVID-19.

Risk Models to Predict Mortality in Burn Patients: A Systematic Review and Meta-analysis.

The predictive capability of various risk assessment models (RAMs) in evaluating the risk of mortality in burn patients is not well established. It is also unclear which RAM provides the highest discriminative ability and presents the highest clinical utility. We pooled all available studies to establish this validity and compare the predictive capability of the various RAMs. Methods: We reviewed PubMed, MEDLINE, and Embase from their inception up until December 2021 for studies evaluating risk of mortality in burn patients as stratified by RAMs. Data were pooled using random-effect models and presented as area under the receiver operating characteristic (AUROC) curve. Results: Thirty-four studies, comprising of a total of 98,610 patients, were included in our analysis. Most studies were found to have a low risk of bias and a good measure of applicability. Nine RAMs were evaluated. We discovered that the classic Baux; the revised Baux; and the Fatality by Longevity, APACHE II score, Measured Extent of burn, and Sex (FLAMES) scores presented with the highest discriminative power with there being no significant difference between the results presented by them [AUROCs (95% CI), 0.92 (0.90-0.95), 0.92 (0.90-0.93), 0.94 (0.91-0.97), respectively, with P < 0.00001 for all]. Conclusions: Many RAMs exist with no consensus on the optimal model to utilize and assess risk of mortality for burn patients. This study is the first systematic review and meta-analysis to compare the current RAMs' discriminative ability to predict mortality in patients with burn injuries. This meta-analysis demonstrated that RAMs designed for assessing mortality in individuals with burns have acceptable to great discriminative capacity, with the classic Baux, revised Baux, and FLAMES demonstrating superior discriminative performance in predicting death. FLAMES exhibited the highest discriminative ability among the RAMs studied.