RBC INDICES, PERIPHERAL SMEAR AND PLATELET INDICES CORRELATION FOR MICROCYTIC ANEMIA ASSESSMENT: A CROSS-SECTIONAL STUDY.

Aim The current study aims to explore the relationship among platelet indices, RBC indices and peripheral blood smears in the assessment of microcytic hypochromic anemia.  Methods A cross sectional study was conducted at the Indira Gandhi Institute of Medical Sciences, Patna, Bihar over the duration of a February 2021 to March 2022, which included 4560 cases comprising indoor and outdoor patients. Peripheral blood smear stained with Leishman were made using blood samples obtained in EDTA tubes. Automated cell counters were for analysis of complete blood counts including hemoglobin, RBC indices and other hematological parameters.  Results Among 4560 cases, 51.63% were male and 48.37% were female, and adults in their thirties (19.35%) were the group most affected. The most prevalent morphological type was microcytic hypochromic anemia (48.10%), mostly of intermediate severity (63.47%), affecting females and children. Normocytic normochromic anemia (41.01%) was primarily mild (61.52%) and common among the elderly. Macrocytic anemia (11.54%) showed no significant age or severity variations. Only 4.08% cases had dimorphic anemia, with 63.7% being mild.  Conclusion Anemia's prevalence and severity vary across age groups due to diverse underlying causes. As individuals age progresses, anemia becomes more common, linked to infections, inflammation, chronic diseases, and reduced bone marrow response. Accurate diagnosis and treatment planning require identifying cause, type, and severity of anemia.  Recommendations According to the study, healthcare providers should monitor age-related anemia prevalence and severity. Consider infections, inflammation, chronic illnesses, and diminished bone marrow response when examining patients, especially as they age. To optimize patient outcomes, accurate diagnosis and individualized treatment regimens should focus on anemia etiology, type, and severity

THE ROLE OF ABSOLUTE RETICULOCYTE COUNTS IN EVALUATION OF PANCYTOPENIA: A CROSS-SECTIONAL STUDY, BIHAR, INDIA.

Background Hematological conditions like pancytopenia are widespread in our lab. Diagnosis and therapy of pancytopenia require etiology analysis. Most pancytopenia causes are determined by the Absolute Reticulocyte Count (ARC), which has been neglected. The aim of this study is to determine the importance of the Absolute Reticulocyte Count (ARC) in assessing the etiology of pancytopenia, with a focus on its role in distinguishing between different causes of this hematological condition. Materials and Methods The study was conducted in a tertiary health care institution in Bihar, India. Over the course of 1 year (April 2021 to March 2022), a descriptive cross-sectional study was carried out. Complete blood counts (CBC), reticulocyte count including ARC and peripheral blood smear (PBS) examination were performed in all cases of pancytopenia. Serum ferritin, Serum vitamin B12 level and serum folate were also estimated. Bone marrow examination was done in all cases. Results A total of 200 pancytopenia cases were assessed, and the findings were recorded. In cases of aplastic anemia, ARC was found to be 100x109 /L was seen in neoplastic disorders. Lower ARC values were associated with conditions like aplastic anemia, while higher ARC values were indicative of acute leukemia and metastatic deposits, making ARC a valuable diagnostic tool. Conclusion It was concluded that ARC is crucial in distinguishing between different causes of pancytopenia, and it must be a regular part of work-up to prevent needless invasive bone marrow examinations in cases of pancytopenia. Recommendation This study suggests that pancytopenia patients be routinely assessed with Absolute Reticulocyte Count (ARC). ARC helps identify pancytopenia etiologies, preventing needless bone marrow exams. Pancytopenia diagnosis and treatment can be improved by adding ARC to diagnostic techniques

A HOSPITAL-BASED STUDY ON UTILISING HPLC TO DETECT HB-VARIANTS AND HEMOGLOBINOPATHIES: A RETROSPECTIVE DESCRIPTIVE STUDY.

Background Hemoglobinopathies are a growing global health issue. These hereditary diseases are most common worldwide. WHO says the Middle East and India have the highest incidence. HPLC is a good way to screen hemoglobin variants such HbF and HbA2. The present study was carried out to diagnose hemoglobinopathies and thalassemias by the use of HPLC in Indira Gandhi Institute of Medical Sciences, Patna, Bihar, India.  Materials and Methods  A retrospective descriptive research assessed 550 patients for thalassaemia or other hemoglobin structural abnormalities. This investigation included all cases of microcytic hypochromic anemia (MCV< 80 fl, MCH< 27 pg) with a clinical suspicion of hemoglobinopathy that did not respond to usual treatment. The trial excluded patients who had blood transfusions within three months.  Results This study included 550 cases, 310 boys and 240 females, aged 2 months to 40 years. HPLC analysis revealed abnormal hemoglobin fractions in 96 cases. One person had delta thalassemia, one had delta with beta-thalassemia, one had hemoglobin D Iran, two had HbE with beta, six had HbE trait, eight (1%) had beta major, and less than 1% had HbE homozygous. Of the cases, 72 (13%) had beta thalassemia. The HPLC pattern was normal in 48%. In all cases, peripheral blood smears showed target cells, microcytosis, and hypochromia. The majority of patients had increased RBCs.  Conclusion Hemoglobinopathies can be quickly, accurately, and effectively diagnosed with HPLC. It is a valuable diagnostic technique for beta thalassemia characteristics, particularly in impoverished nations like India where hemoglobinopathies are difficult to identify. Prompt diagnosis could aid in appropriate and targeted treatment.  Recommendation This study emphasizes the need of HPLC for hemoglobinopathy diagnosis, especially in high-burden countries like India. HPLC screening and diagnosis can help combat hemoglobinopathies' global health issues by enabling early detection and focused treatment

Reinforcement learning-based spectrum management for cognitive radio networks: A literature review and case study

In cognitive radio (CR) networks, the cognition cycle, i.e., the ability of wireless transceivers to learn the optimal configuration meeting environmen- tal and application requirements, is considered as important as the hardware components which enable the dynamic spectrum access (DSA) capabilities. To this purpose, several machine learning (ML) techniques have been applied on CR spectrum and network management issues, including spectrum sensing, spectrum selection, and routing. In this paper, we focus on reinforcement learning (RL), an online ML paradigm where an agent discovers the optimal sequence of actions required to perform a task via trial-end-error interactions with the environment. Our study provides both a survey and a proof of concept of RL applications in CR networking. As a survey, we discuss pros and cons of the RL framework compared to other ML techniques, and we provide an exhaustive review of the RL-CR literature, by considering a twofold perspective, i.e., an applicationdriven taxonomy and a learning methodology-driven taxonomy. As a proof of concept, we investigate the application of RL techniques on joint spectrum sensing and decision problems, by comparing different algorithms and learning strategies and by further analyzing the impact of information sharing techniques in purely cooperative or mixed cooperative/competitive tasks