We developed an automated morphological image recognition deep learning system (image recognition DLS) of peripheral blood cells, then constructed the diagnostic assist DLS combining image recognition DLS data with complete blood count (CBC) data. This study aimed to evaluate the clinical performance of the image recognition DLS and the diagnostic assist DLS in routine examinations. The image recognition DLS was trained using datasets containing 1 476 727 images of white blood cells (WBCs), nucleated red blood cells (NRBCs), and large platelets to differentiate 14 blood cell types and to recognize 24 morphological characteristics. CBC data were obtained through the automated hematology analyzer (Sysmex XN-9000) and combined with the image recognition DLS data to construct the diagnostic assist DLS. The clinical performance of the image recognition DLS was evaluated using 128 716 blood cell images from 589 smears obtained from healthy subjects, ALL, AML, ML, MPN, and MDS cases in routine examinations. The image recognition DLS classified 14 blood cell types with an accuracy of 97.3%-99.9%. The accuracy of 11 morphological characteristics exceeded 90%. Blast cells were detected accurately on all slides, where they were identified by manual microscopy. Malignant lymphocytes were classified as blasts and/or lymphocytes with the morphological characteristics of each subtype of lymphoma. The diagnostic assist DLS successfully differentiated MDS, achieving an AUC (area under the curve) of 0.99. This study demonstrated the potential of the diagnostic assist DLS, utilizing morphological image recognition DLS data combined with CBC parameters, as a promising diagnostic tool.

Differentiating between healthy intrauterine pregnancy (HP) and ectopic pregnancy (EP) in early gestation is clinically challenging. This study aimed to evaluate the role of the delta neutrophil index (DNI), pan-immun inflammation value (PIV) and other hematologic inflammatory markers in the preliminary diagnosis of tubal EP. To the best of our knowledge, there are no studies in the literature examining the relationship between DNI, PIV and EP. This retrospective study included 120 women diagnosed with tubal EP and 102 women with HP who presented to a tertiary hospital in Turkey between 2019 and 2023. Inclusion criteria were women with confirmed tubal EP or HP who had complete clinical and hematologic data and no chronic diseases, infections, or body mass index (BMI) > 30 kg/m2. The primary outcome was to assess whether DNI, PIV and other complete blood count (CBC) parameters could differentiate EP from HP. Statistical analysis included t-tests, Welch's t-test, χ2 tests, and ROC analysis; p < 0.05 was considered statistically significant. No significant difference was found in DNI value (p = 0.256). However, white blood cell count (WBC) (p = 0.007), platelet (PLT) (p = 0.001), lymphocyte (p < 0.001), PIV (p = 0.023), systemic immune-inflammation index (SII) (p = 0.016) and basophil (p = 0.005) levels were higher in the EP group, while hemoglobin (HB) levels were lower (p < 0.001). While DNI was not a significant marker, other hematologic parameters may support early identification of EP, suggesting an underlying inflammatory process.

Chronic myelomonocytic leukemia (CMML) shows marked prognostic heterogeneity. Although leukocytosis is a recognized adverse prognostic factor, the contribution of its individual components remains insufficiently defined. In a cohort of 240 patients classified according to International Consensus Classification (ICC) and World Health Organization (WHO) 2022 criteria—including 23% with oligomonocytic CMML—we evaluated the prognostic impact of neutrophil and monocyte percentage, along with surrogate markers of their relative increase, including relative lymphopenia (<20%) and elevated monocyte‐to‐lymphocyte ratio (MLR > 1). Both relative lymphopenia and MLR > 1 emerged as independent adverse prognostic factors, correlating with adverse mutations (TP53, RAS pathway) and high‐risk clinical features. Notably, MLR > 1 identified a subset of patients with dysplastic CMML with molecular and clinical profiles resembling proliferative CMML (MP‐CMML). These variables retained their prognostic impact after adjustment for established prognostic models (CMML‐specific prognostic scoring system [CPSS], CPSS with the addition of the variable platelet < 100 × 10⁹/L [CPSS‐P], and Mayo prognostic model), and their addition improved predictive performance. Based on these and other objective variables readily available from a routine complete blood count (CBC), we developed the objective prognostic index for CMML (OPIC), which integrates hemoglobin < 11 g/dL, platelets < 100 × 10⁹/L, MP‐CMML, and MLR > 1. OPIC stratified patients into four risk categories with distinct survival outcomes (median overall survival [OS]: 104, 66.6, 34.3, and 18.3 months), demonstrating strong discriminatory power. Variable selection was performed using stepwise and elastic net regression, and random survival forests. Model performance metrics, including the C‐index, time‐dependent area under the receiver operating characteristic curve, and the Brier Score, were internally validated using bootstrapping‐based resampling methods and externally validated in a cohort of 250 patients. OPIC provides a robust, accessible tool for CMML risk stratification, supporting its integration into routine clinical workflows and early therapeutic decision‐making.

This study investigated the relationship between white blood cell counts and pediatric hypertension, addressing the limited evidence on white blood cell counts/subtypes and pediatric hypertension. A prospective cohort study was conducted involving 5971 children aged 6-12 years in Chongqing, China, with baseline data collected in 2014-2015 and 1282 children completed a 5-year follow-up in 2019. White blood cell indicators, including total white blood cell counts (WBC), lymphocyte counts and percentage (LC, LP), monocyte counts and percentage (MC, MP), neutrophil counts and percentage (ANC, NR), and lymphocyte-monocyte ratio (LMR) were measured using Complete Blood Count (CBC) tests. Blood pressure (BP), and anthropometric indices were also measured. Multilevel linear mixed models and logistic regression models, adjusted for confounders were applied to illustrate the relevance of cell counts indicators and blood pressure. Results showed that compared to normal BP (NBP) group, the elevated BP (EBP) group had significant lower MC(OR(95%CIs) = 0.79(0.68,0.90)) and MP(OR(95%CIs) = 0.78(0.68,0.88)) but higher LMR(OR(95%CIs) = 1.31(1.15,1.50)). Multivariate analyses adjusted for confounding factors revealed that MP was negatively correlated with SBP, DBP and MAP, while LMR positively correlated with these blood pressure(P < 0.05). MC and MP were associated with a reduced risk of hypertension, whereas LMR was associated with an increased risk, particularly in boys. No significant mediation effect of WBC indices between BMI and BP was observed. In conclusion, Peripheral MC, MP, and LMR were significantly associated with pediatric hypertension; MC and MP act as protective factors and LMR acts as a risk factor, suggesting that these indices may serve as potential biomarkers for childhood hypertension.

Thalassaemia is a serious anaemia disease caused by genes, which results in serious health and economic problems in the entire globe, particularly in those areas with restricted access to health care. Thalassaemia and iron deficiency anemia are clinically similar as they have similar hematological characteristics. Conventional diagnostic tools comprising of molecular test, conventional index and complete blood count (CBC) parameters may provide pertinent information but are not always available, are not affordable and take a long turnaround time. Over the last few decades, the field of medicine diagnostics has encountered a disruptive technology in the form of Artificial Intelligence (AI) since it is both cheap and quick and incredibly precise in treatment. The artificial intelligence (AI) like Decision Tree, Support Vector Machine, and Neural Networks can be able to determine the traits of thalassaemia using the normal hematological data. Additional methods to be proven to be more dependable in diagnosis, like deep learning and sophisticated algorithms, like XGBoost and Convolutional Neural Networks (CNN) can be further tested to introduce additional reliability in a diagnosis. It has also been found in comparative studies that AI-based models tend to be more sensitive and specific than standard indices, this is the reason that these technologies are currently being utilized as genetic counseling and screening tools. Nevertheless, problems of data quality, bias of the model, and considerations of ethics persist. Nevertheless, AI can serve as an important supportive resource in the early diagnosis, accurate differentiation, and better management of thalassaemia in low resource healthcare facilities despite the challenges. The combination of AI and molecular testing is bright in terms of global thalassaemia control and individualized medication.

Background: Inflammatory activity in rheumatoid arthritis can be determined by normal blood count ratios such as Neutrophil Lymphocyte Ratio (NLR), Platelet Lymphocyte Ratio (PLR), Systemic Immune Inflammation Index (SII), and C-reactive Protein (CRP). Objective: The aim of this research is to determine how these markers change after therapy and whether their pre- and post-treatment differences follow patterns that allow for simple parametric analyses. Methods: A prospective cohort of 52 RA patients (30 females and 22 males) was examined. The patients' blood samples were tested at baseline and at the end of their 6-month Infliximab treatment. Hematologic markers such as NLR, PLR, and SII were calculated from the complete blood count (CBC), and CRP levels were measured. The statistical methods of Shapiro-Wilk (SW), Kolmogorov-Smirnov (KS), and Anderson-Darling (AD) were used, and later, paired t-tests were used to generate statistics where necessary. Results: Post-treatment measurements were consistently lower for all four biomarkers. QQ-plots and formal tests revealed that the differences between findings were essentially normal, allowing for paired t-tests. The mean decreases were as follows: NLR -1.10 (95% CI -1.48 to -0.71), PLR -43.0 (-55.4 to -30.7), SII -299 (-388 to -211), and CRP -11.36 (-13.18 to -9.54), all p < 0.001. CRP showed the greatest drop, with significant decreases in PLR and SII and a moderate decline in NLR, indicating therapy-related attenuation of systemic inflammation. Conclusions: The study shows that six months of infliximab therapy results in a consistent post-treatment decrease in all four biomarkers: NLR, PLR, SII, and CRP. Because the pre-post differences were roughly normal, CRP revealed the greatest decrease, with significant decreases in PLR and SII and a moderate decrease in NLR, consistent with systemic inflammation reduction. When combined, the CBC-derived indices track with CRP and can serve as practical, low-cost markers for monitoring therapy response in RA, despite the single-arm design.

Thalassaemia is a serious anaemia disease caused by genes, which results in serious health and economic problems in the entire globe, particularly in those areas with restricted access to health care. Thalassaemia and iron deficiency anemia are clinically similar as they have similar hematological characteristics. Conventional diagnostic tools comprising of molecular test, conventional index and complete blood count (CBC) parameters may provide pertinent information but are not always available, are not affordable and take a long turnaround time. Over the last few decades, the field of medicine diagnostics has encountered a disruptive technology in the form of Artificial Intelligence (AI) since it is both cheap and quick and incredibly precise in treatment. The artificial intelligence (AI) like Decision Tree, Support Vector Machine, and Neural Networks can be able to determine the traits of thalassaemia using the normal hematological data. Additional methods to be proven to be more dependable in diagnosis, like deep learning and sophisticated algorithms, like XGBoost and Convolutional Neural Networks (CNN) can be further tested to introduce additional reliability in a diagnosis. It has also been found in comparative studies that AI-based models tend to be more sensitive and specific than standard indices, this is the reason that these technologies are currently being utilized as genetic counseling and screening tools. Nevertheless, problems of data quality, bias of the model, and considerations of ethics persist. Nevertheless, AI can serve as an important supportive resource in the early diagnosis, accurate differentiation, and better management of thalassaemia in low resource healthcare facilities despite the challenges. The combination of AI and molecular testing is bright in terms of global thalassaemia control and individualized medication.

Background/Objective: The risk of bleeding is part of blood flow pathophysiology in diabetes mellitus (DM), and there may be potential for the relationship between blood cell indices and estimated whole blood viscosity (eWBV) in DM. However, red blood cell (RBC) indices, platelet ratios, and lymphocyte ratios have been part of routine haematology tests in clinical medicine including diabetes management. This study investigated two research questions. Firstly, how does eWBV correlate with RBC indices, platelet ratios, and lymphocyte ratios? Secondly, which parameters of RBC in routine full blood count (FBC) correlate more with glycated haemoglobin (HbA1c) changes? Methods: This was a laboratory-based clinical observational cohort study using secondary data from ongoing research. Data collected included FBC and biochemistry (HbA1c and serum protein level). Dependent variables were platelet and lymphocyte ratios as well as eWBV. Results: Averages for all parameters in the cross-sectional data were within normal range, except high HbA1c (7.67%) and marginally high monocyte-to-lymphocyte ratio. In the periodic cohort analysis, only RBC distribution width showed a significant difference (p < 0.04) between cohort groups, but least correlated with HbA1c changes. Further analysis for correlations among change scores showed that RBC had the strongest positive linearity for HbA1c (r = 0.30) and among the top three for eWBV (r = 0.54), while mean cell volume (MCV) has the strongest inverse for HbA1c (r = -0.47). Conclusions: The ongoing clinical use of RBC variables is superior to profiles of platelet and/or lymphocyte ratios in assessing the potential risk of bleeding (i.e., hypo-viscosity) in diabetes.

Introduction: Iron deficiency (ID) is the most common cause of nutritional deficiency anemia in the developing world, and complete blood count (CBC) is one of the most common blood tests that is used to diagnose hematological abnormalities. Also, serum Ferritin is a more sensitive test used to evaluate and reflect iron status in the body. Tuberculosis is a major of a big health problem in the world, especially in Sudan. This study was done in Kosti teaching hospital from June to September 2018.Study design: Case-control study. Fifty patients infected with tuberculosis were selected as cases, and fifty normal persons (without TB) were matched as a control group. Methodology: 2.5 ml blood samples were taken in ethylene diamine tetraacetic acid (EDTA) treated tubes and were analyzed in the Mindray BC-3000 automated hematology analyzer. The Biosystem BTS-350 spectrophotometer protocol has been used for Ferritin measurement. ESR was read using the Westergren tube method.Results: The results showed highly significant differences in all hematological parameters in TB patients when compared with healthy person and the P value was 0.000 in all parameters, 0.01 in the Hb. Also, patients with normal and high serum Ferritin were detected (17 with normal value and 23 with a high serum Ferritin), and less than 10 cases of low serum Ferritin were those suffering from iron deficiency anemia. The ESR values of TB patients obtained in this study were significantly higher than control values.Conclusion: Most of the patients were anemic with low Hb and RBC indices. The study found a strong positive association of anemia without iron deficiency and TB (23 cases with high serum Ferritin and 10 cases with low serum Ferritin), suggesting that factors other than iron deficiency also contribute to the association of anemia with poor outcomes, which may be due to chronic infection.

Gastric ulcer remains a common cause of morbidity, yet marked clinical variability suggests contributors beyond established risk factors such as Helicobacter pylori, non-steroidal anti-inflammatory drug exposure, and excess gastric acid. To clarify the role of systemic inflammation, Shen et al evaluated six complete blood count (CBC)-derived inflammatory indices in patients with gastric ulcer. All indices showed significant associations, with the systemic inflammatory response index demonstrating the strongest discriminatory value. Given that CBC testing is routine, inexpensive, and widely accessible, these indices may offer practical adjunctive markers for identifying individuals at increased risk. However, the cross-sectional design and lack of adjustment for major confounders limit causal interpretation. Prospective validation is required to determine whether these indices predict ulcer development, recurrence, or clinical outcomes, and to assess their potential integration with established risk factors.

BackgroundRheumatoid arthritis (RA) is an autoimmune disease for which better biomarkers are needed, especially in seronegative cases. This study evaluates complete blood count (CBC)-derived inflammatory indices – neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) – for RA diagnosis and disease activity assessment, with comparisons between seropositive and seronegative RA.MethodsWe conducted a retrospective case–control study of 230 RA patients and 115 age- and sex-matched healthy controls. CBC-derived indices were calculated from routine blood counts. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves (area under the curve, AUC) for RA versus controls overall and stratified by serostatus. Associations with disease activity (DAS28-CRP, SDAI, CDAI) were assessed via correlations and ROC analysis for active (moderate/high) versus inactive (remission/low) RA.ResultsAll five indices were significantly elevated in RA patients compared to controls (all P < 0.001). MLR showed the highest diagnostic accuracy (AUC = 0.771), followed by SIRI (0.72) and PLR (0.70); NLR and SII were more modest (≈0.69–0.68). In seronegative RA, diagnostic discrimination declined (best AUC = 0.707 for MLR; SII and SIRI AUCs ~0.56–0.59). NLR, SII, and SIRI correlated moderately with CRP, ESR, and composite scores (Spearman ρ ~0.3–0.4, P < 0.001), and were higher in active RA (DAS28-CRP AUCs 0.668–0.700). SII and SIRI provided the top discrimination of active disease (AUC ~0.70). PLR showed minimal correlation with activity and no significant difference between active and inactive RA.ConclusionCBC-derived inflammatory indices are elevated in RA and reflect systemic inflammation. MLR is the most robust index for distinguishing RA from healthy individuals, while SII, SIRI, and NLR are useful for gauging disease activity. In seronegative RA, diagnostic performance was attenuated overall, with MLR retaining fair discrimination while SII/SIRI/NLR showed limited utility.

This study investigated whether Whole blood viscosity (WBV) varies with age in clinically healthy Beagle dogs and Korean Shorthair cats and examined the hematologic and biochemical variables associated with WBV. WBV was measured across multiple shear rates using a scanning capillary viscometry; complete blood count (CBC) and serum chemistry profiles were also evaluated. Both species demonstrated characteristic shear-thinning behavior. WBV showed a strong association with red blood cell count (RBC), hematocrit (HCT), and hemoglobin (Hb) in both species, with additional association with serum proteins and cholesterol in dogs. No significant relationship between WBV and age was identified at any shear rate, and principal component analysis (PCA) revealed no age-related clustering in the viscosity profiles. These findings indicated that WBV does not exhibit meaningful age-dependent trends in healthy companion animals. This suggests that, in a clinical setting, deviations in normal WBV are more likely to influence underlying physiological or pathological factors than normal aging.

This review synthesizes current literature regarding metabolic aspects of athlete bone health and incorporates evidence-based recommendations into a clinician-friendly algorithm. Published manuscripts listed in PubMed between 1993 and 2024 were reviewed. Relevant terms including keywords and section titles of manuscripts were searched, and relevant studies identified. Clinical review. Level 1-3. A metabolic workup is often appropriate in the context of an athlete with bone stress injury (BSI) but varies based on clinical scenario. Evidence supports that all athletes with BSI be considered for a minimum workup including 25-hydroxyvitamin D (SORT A), complete blood count (CBC) (SORT B), and an iron panel with ferritin (SORT B). Athletes with features of low energy availability, including ≥2 Triad risk factors (low body mass index, abnormal uterine bleeding), or with multiple features of relative energy deficiency in sport require an initial strategy to correct energy availability (increased energy intake and/or decreased training load) and should be considered for dual-energy x-ray absorptiometry (DXA) (SORT A) and additional laboratory testing. If there is persistent clinical concern, a comprehensive laboratory evaluation should be considered, and varies based on athlete sex and clinical context. People with recurrent or multiple BSI or requiring surgical fixation also warrant detailed, stepwise testing for underlying causes (SORT C). A reasonable strategy starts with a focused workup for more common conditions (eg, CBC, complete metabolic panel, iron panel, 25-OH vitamin D, DXA) and may expand based on initial findings and clinical suspicion. Existing evidence supports optimizing nutrition and further evaluation for factors influencing bone health for all athletes with BSI. More extensive workup is required in athletes with multiple features of low energy availability, multiple/recurrent BSI, BSI requiring surgical fixation, and signs/symptoms of an underlying medical disorder.Strength-of-Recommendation Taxonomy (SORT):A, B, C.

Effects of sample storage time and temperature on equine complete blood counts.

Background: Red blood cell distribution width (RDW) reflects anisocytosis, which is the variability in erythrocyte size. This parameter is commonly used in the differential diagnosis of various types of anemia Mean platelet volume (MPV) demonstrates platelet size and serves as an indirect marker of platelet activation. Both RDW and MPV have been proposed as potential markers for cardiovascular disease severity and prognosis. Aim: To evaluate the role of RDW, MPV, and the MPV/PLT ratio as supporting indicators in the diagnosis and severity assessment of acute coronary syndrome (ACS). Methods: This cross-sectional hospital-based study included 104 patients diagnosed with ACS (ST-elevation myocardial infarction, non-ST elevation myocardial infarction, unstable angina) admitted to the coronary care unit between October and December 2023. A control group of 181 healthy individuals was used to establish reference values. Data analysis was conducted using IBM SPSS. Results: Platelet count, MPV, and the MPV/PLT ratio were significantly associated with ACS. However, RDW showed no association with ACS in this study. Conclusions: This study evaluated the role of hematological parameters in acute coronary syndrome. To the best of our knowledge, this is the first study in Basrah demonstrating that the PLT count, MPV, and MPV /PLT ratio are significantly associated with ACS. In this study, RDW was not related to ACS. Given that a complete blood count (CBC) is a simple, cost-effective, and widely available test, we propose that these hematological indices may serve as supportive tools in the risk assessment of ACS patients.

Associations between immunological and hormonal parameters during healthy pregnancy in mares.

IntroductionBacterial pneumonia remains a major global health challenge, and early pathogen identification is important for timely and targeted treatment. However, conventional microbiological diagnostics such as sputum or blood culture are labor-intensive and time-consuming.MethodsWe propose an interpretable ensemble learning framework (PreBP) for rapid pathogen identification using routinely available complete blood count (CBC) parameters. We analyzed 1,334 CBC samples from patients with culture-confirmed bacterial pneumonia caused by four major pathogens: Pseudomonas aeruginosa, Escherichia coli, Staphylococcus aureus, and Streptococcus pneumoniae. Pathogen labels were determined based on clinical culture results. Five machine learning models (extreme gradient boosting (XGBoost), multilayer perceptron neural network (MLPNN), adaptive boosting (AdaBoost), random forest (RF), and extremely randomized trees (ExtraTrees)) were trained as comparators, and PreBP was developed with metaheuristic-optimized hyperparameters. Key CBC biomarkers were refined using a dual-phase feature selection strategy combining Lasso and Boruta. To enhance transparency, SHapley additive explanations (SHAP) were applied to provide both global biomarker importance and local, case-level explanations.ResultsPreBP achieved the best overall performance, with an AUC of 0.920, precision of 87.1%, and accuracy and sensitivity of 86.7%.DiscussionBecause the framework relies on routine CBC measurements, it can generate interpretable predictions once CBC results are available, which may provide supplementary evidence for earlier pathogen-oriented clinical decision-making alongside culture-dependent workflows. Overall, PreBP offers an interpretable and computational approach for pathogen identification in bacterial pneumonia based on routine laboratory data.

BackgroundInflammation plays a central role in the pathogenesis of atrial fibrillation (AF), a common cardiac arrhythmia. Complete blood count (CBC)-derived markers of inflammation, including the systemic inflammatory index (SII) and systemic inflammatory response index (SIRI), have emerged as novel biomarkers of systemic inflammation. Although small prior studies have reported associations between certain inflammatory markers and AF, their limited sample sizes and potential baseline imbalances prevent definitive conclusions. Using a large population-based cohort, this study examines the association between CBC-derived inflammatory markers—SIRI, SII, monocyte-to-lymphocyte ratio (MLR), aggregate index of systemic inflammation (AISI), neutrophil-monocyte-to-lymphocyte ratio (NMLR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR)—and the risk of AF, and investigates potential mediating mechanisms by integrating clinical data.MethodsThis cross-sectional analysis included 10,474 adults aged ≥20 years from the National Health and Nutrition Examination Survey (NHANES) 2013–2020 and was validated in 13,707 adults aged ≥20 years from Zibo Central Hospital 2015–2024. Seven inflammatory markers were derived from CBC data and categorized into low, medium, and high quartiles according to their distributions. A weighted multivariable logistic regression adjusted for confounders, including age, sex, hypertension, and diabetes. Associations between inflammatory markers and atrial fibrillation were expressed as odds ratios (OR) with 95% confidence intervals (CI). Restricted cubic spline (RCS) regression assessed nonlinear relationships. Subgroup and interaction analyses evaluated the influence of demographic and clinical factors. Finally, a mediation model examined the mediating role of left atrial diameter.ResultsOf the 10,474 participants in the NHANES database, 136 (1.3%) were diagnosed with AF. After full adjustment, the highest SIRI tertile showed a significantly increased risk of AF compared with the lowest tertile (OR = 2.182; 95% CI: 1.094–4.354; P = 0.027). RCS analysis revealed a linear positive association between SIRI and AF risk (overall P > 0.05). Subgroup analyses and interaction tests indicated that the positive association between SIRI and AF persisted across different conditions (all p-value for interaction > 0.05). Results were then validated using the case management system of Zibo Central Hospital. In that cohort, after full adjustment, the highest SIRI tertile again had a significantly increased risk of AF vs. the lowest tertile (OR = 1.436; 95% CI: 1.248–1.652; P < 0.001). Mediation analysis indicated that LA diameter mediated 13.54% of the association between SIRI and AF.ConclusionThis study suggests that elevated SIRI may represent a potential biomarker and is associated with an increased risk of AF, and found that left atrial diameter may partially mediate this relationship, suggesting SIRI as a potential inflammatory biomarker for AF prediction. Although other CBC-derived markers did not show significant associations, the results underscore inflammation's role in AF pathogenesis. Further longitudinal studies are needed to validate these findings and clarify the underlying mechanisms.

BackgroundTyphoid fever is still a major health issue in many parts of the world. Traditional tests like blood culture and the Widal test are often slow or unreliable. This study explores whether Complete Blood Count (CBC) and Liver Function Tests (LFTs) can help in the early and affordable diagnosis of typhoid.CBC Parameters NotedLFT Parameters observedMethodsA retrospective review was done on patients with symptoms like fever, weakness, and abdominal pain. CBC and LFT results were collected and compared with confirmed typhoid cases. Key parameters included hemoglobin, WBC and platelet counts, ESR, and liver enzymes (ALT, AST, bilirubin).ResultsOut of 90 confirmed typhoid patients (ages 1–82), many had abnormal lab results. Low hemoglobin was seen in 31%, low WBC in 15%, high WBC in 18%, and low platelets in 23% [Table 1]. Elevated AST and ALT were found in 34% and 28% of cases, respectively, and 46% had high ESR [Table 2]. A few severe cases had complications, including two deaths.ConclusionCBC and LFT tests provide valuable early diagnostic clues for typhoid fever. A combination of leukopenia, thrombocytopenia, high ESR, and elevated liver enzymes can serve as a rapid, accessible, and cost-effective preliminary diagnostic approach before confirmatory testing. This can aid in early intervention and better clinical management, especially in resource-limited settings.DisclosuresAll Authors: No reported disclosures

To compare systemic inflammation parameters and blood lipid profile in patients with conjunctivochalasis versus healthy individuals. Thirty patients with conjunctivochalasis(Cch) and thirty age-matched healthy controls were included in this retrospective study. Complete blood count (CBC) parameters and serum levels of total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides (TG) were obtained from electronic medical records. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and monocyte-to-HDL ratio (MHR) were calculated for each participant. Group differences were analyzed statistically. The monocyte-to-HDL ratio was significantly higher in the conjunctivochalasis group (p = 0.023), while hemoglobin levels were significantly lower (p = 0.001). No additional significant differences were observed in other hematological or lipid parameters. This study is the first to demonstrate an elevated monocyte-to-HDL ratio in patients with conjunctivochalasis. The concurrent reduction in hemoglobin levels provides further support for a potential systemic association. These findings suggest that conjunctivochalasis may involve not only localized ocular changes but also systemic inflammatory processes.