Anemia to Median Nerve Palsy.

Mesenteric angina has a high mortality rate. Occlusion of the superior mesenteric artery is the most common cause. Increasingly, it is managed endovascularly instead of by open revascularization. Despite the lower risk of complications in minimally invasive procedures, it is important to be mindful of long-term sequelae of minor complications. Patient education regarding risks and complications is paramount for better clinical outcomes. The risks of transbrachial angiography procedures are low. Postprocedural vigilance for interventionists and written educational advice to patients are paramount in all minimally invasive endovascular procedures, especially because most of these patients with a complication require urgent operative correction.

Concordance between platelet counts by impedance and optical technique during microcytic anemia: towards a threshold value of the mean corpuscular volume.

INTRODUCTION: Platelet count is crucial for clinical decision. In cases of microcytosis, platelet count based on impedance technique (PLT-I) may overestimate platelet count. AIM: To compare PLT-I with platelet count using the optical technique (PLT-O) and establish a Mean Corpuscular Volume (MCV) threshold for considering PLT-O. METHODS: A prospective analytical study conducted over two months involved blood samples collected in standard K2 EDTA tubes for complete blood count analysis, revealing microcytosis (MCV<80 fL). PLT-O analysis in channel-Ret mode was performed using the Sysmex-XN1000 (Sysmex Corporation, Kobe, Japan). Percentage of fragmented red cells (FRC%) and percentage of microcytic red cells (Micro-R%) were recorded. Blood smears stained with May-Grünwald-Giemsa were examined for potential interfering particles. RESULTS: A strong correlation was observed between the two techniques for all platelet values as well as for PLT <150 x 109/L (correlation coefficient r = 0.971, 95% CI: [0.956-0.982]; P<10-3 and r = 0.90, 95% CI: [0.79-0.95]; P< 10-3). The Bland-Altman plot revealed a bias of 16.53 x 109/L between the two methods, with agreement limits between -55.8 and 88.8 x 109/L. A threshold MCV value indicating the use of the optical method, with a cut-off at 72.9fL, demonstrated promising performance consistent with literature findings. However, less favorable performance was observed with Micro-R%. CONCLUSION: Impedance could be employed in routine practice. However, for MCV<72.9 fL or in the presence of schizocytes, the hemogram validation procedure may incorporate the use of PLT-O.

Non-invasive hemoglobin screening device: a promising digital method for reducing anemia prevalence through routine screening and timely intervention.

BACKGROUND: Several non-invasive technologies are nowadays available in the market which claim to determine the hemoglobin levels instantly without the requirement of the blood sample. But no study has shown the significance of such non-invasive devices on a routine basis for determining their impact on anemia reduction programs. This study is conducted to determine the impact of regular hemoglobin screening on the women population to determine its potential in reducing anemia, using a digitalized non-invasive device. METHOD: A cross-sectional study was conducted on 203 women of reproductive age group, residing in the Moradabad district. Repetitive readings were taken after a time interval of a minimum of 1 month for determining the impact of regular screening. The entire data collection process was carried out using the EzeCheck mobile app. RESULTS: It was observed that the prevalence of anemia was reduced upon the second time screening and was accepted by the women population. Repetitive testing has a significant impact on reducing anemia prevalence. Also, the simplified non-invasive technology for estimating the hemoglobin values, makes the user more comfortable to take the test. CONCLUSION: Non-invasive devices should be used regularly to keep track of hemoglobin levels which will help in the effective treatment of anemia. The mobile app-based testing could help to easily evaluate the reports of the patients from any remote location with instant result interpretation and health assistance.

Non-cardiac comorbidities in heart failure: an update on diagnostic and management strategies.

Managing non-cardiac comorbidities in heart failure (HF) requires a tailored approach that addresses each patient's specific conditions and needs. Regular communication and coordination among healthcare providers is crucial to providing the best possible care for these patients. Poorly controlled hypertension contributes to left ventricular remodeling and diastolic dysfunction, emphasizing the importance of optimal blood pressure control while avoiding adverse effects. Among HF patients with diabetes, SGLT2 inhibitors and mineralocorticoid receptor antagonists have shown promise in reducing HF-related morbidity and mortality. Chronic kidney disease exacerbates HF and vice versa, forming the vicious cardiorenal syndrome, so disease-modifying therapies should be maintained in HF patients with comorbid CKD, even with transient changes in kidney function. Anemia in HF patients may be multifactorial, and there is growing evidence for the benefit of intravenous iron supplementation in HF patients with iron deficiency with or without anemia. Obesity, although a risk factor for HF, paradoxically offers a better prognosis once HF is established, though developing treatment strategies may improve symptoms and cardiac performance. In HF patients with stroke and atrial fibrillation, anticoagulation therapy is recommended. Among HF patients with sleep-disordered breathing, continuous positive airway pressure may improve sleep quality. Chronic obstructive pulmonary disease often coexists with HF, and many patients can tolerate cardioselective beta-blockers. Cancer patients with comorbid HF require careful consideration of cardiotoxicity risks associated with cancer therapies. Depression is underdiagnosed in HF patients and significantly impacts prognosis. Cognitive impairment is prevalent in HF patients and impacts their self-care and overall quality of life.

Screening of malaria infections in human blood samples with varying parasite densities and anaemic conditions using AI-Powered mid-infrared spectroscopy.

BACKGROUND: Effective testing for malaria, including the detection of infections at very low densities, is vital for the successful elimination of the disease. Unfortunately, existing methods are either inexpensive but poorly sensitive or sensitive but costly. Recent studies have shown that mid-infrared spectroscopy coupled with machine learning (MIRs-ML) has potential for rapidly detecting malaria infections but requires further evaluation on diverse samples representative of natural infections in endemic areas. The aim of this study was, therefore, to demonstrate a simple AI-powered, reagent-free, and user-friendly approach that uses mid-infrared spectra from dried blood spots to accurately detect malaria infections across varying parasite densities and anaemic conditions. METHODS: Plasmodium falciparum strains NF54 and FCR3 were cultured and mixed with blood from 70 malaria-free individuals to create various malaria parasitaemia and anaemic conditions. Blood dilutions produced three haematocrit ratios (50%, 25%, 12.5%) and five parasitaemia levels (6%, 0.1%, 0.002%, 0.00003%, 0%). Dried blood spots were prepared on Whatman™ filter papers and scanned using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) for machine-learning analysis. Three classifiers were trained on an 80%/20% split of 4655 spectra: (I) high contrast (6% parasitaemia vs. negative), (II) low contrast (0.00003% vs. negative) and (III) all concentrations (all positive levels vs. negative). The classifiers were validated with unseen datasets to detect malaria at various parasitaemia levels and anaemic conditions. Additionally, these classifiers were tested on samples from a population survey in malaria-endemic villages of southeastern Tanzania. RESULTS: The AI classifiers attained over 90% accuracy in detecting malaria infections as low as one parasite per microlitre of blood, a sensitivity unattainable by conventional RDTs and microscopy. These laboratory-developed classifiers seamlessly transitioned to field applicability, achieving over 80% accuracy in predicting natural P. falciparum infections in blood samples collected during the field survey. Crucially, the performance remained unaffected by various levels of anaemia, a common complication in malaria patients. CONCLUSION: These findings suggest that the AI-driven mid-infrared spectroscopy approach holds promise as a simplified, sensitive and cost-effective method for malaria screening, consistently performing well despite variations in parasite densities and anaemic conditions. The technique simply involves scanning dried blood spots with a desktop mid-infrared scanner and analysing the spectra using pre-trained AI classifiers, making it readily adaptable to field conditions in low-resource settings. In this study, the approach was successfully adapted to field use, effectively predicting natural malaria infections in blood samples from a population-level survey in Tanzania. With additional field trials and validation, this technique could significantly enhance malaria surveillance and contribute to accelerating malaria elimination efforts.

Microstrip isoelectric focusing with deep learning for simultaneous screening of diabetes, anemia, and thalassemia.

BACKGROUND: Hemoglobin (Hb) is an important protein in red blood cells and a crucial diagnostic indicator of diseases, e.g., diabetes, thalassemia, and anemia. However, there is a rare report on methods for the simultaneous screening of diabetes, anemia, and thalassemia. Isoelectric focusing (IEF) is a common separative tool for the separation and analysis of Hb. However, the current analysis of IEF images is time-consuming and cannot be used for simultaneous screening. Therefore, an artificial intelligence (AI) of IEF image recognition is desirable for accurate, sensitive, and low-cost screening. RESULTS: Herein, we proposed a novel comprehensive method based on microstrip isoelectric focusing (mIEF) for detecting the relative content of Hb species. There was a good coincidence between the quantitation of Hb via a conventional automated hematology analyzer and the one via mIEF with R2 = 0.9898. Nevertheless, our results showed that the accuracy of disease diagnosis based on the quantification of Hb species alone is as low as 69.33 %, especially for the simultaneous screening of multiple diseases of diabetes, anemia, alpha-thalassemia, and beta-thalassemia. Therefore, we introduced a ResNet1D-based diagnosis model for the improvement of screening accuracy of multiple diseases. The results showed that the proposed model could achieve a high accuracy of more than 90 % and a good sensitivity of more than 96 % for each disease, indicating the overwhelming advantage of the mIEF method combined with deep learning in contrast to the pure mIEF method. SIGNIFICANCE: Overall, the presented method of mIEF with deep learning enabled, for the first time, the absolute quantitative detection of Hb, relative quantitation of Hb species, and simultaneous screening of diabetes, anemia, alpha-thalassemia, and beta-thalassemia. The AI-based diagnosis assistant system combined with mIEF, we believe, will help doctors and specialists perform fast and precise disease screening in the future.

Prevalence of iron deficiency and anemia in pediatric heart transplant recipients.

INTRODUCTION: The prevalence of iron deficiency and anemia in the setting of modern-day maintenance immunosuppression in pediatric heart transplant (HTx) recipients is unclear. The primary aim was to determine the prevalence of iron deficiency (serum ferritin < 30 ng/mL ± transferrin saturation < 20%) and anemia per World Health Organization diagnostic criteria and associated risk factors. METHODS: Single-center, cross-sectional analysis of 200 consecutive pediatric HTx recipients (<21 years old) from 2005 to 2021. Data were collected at 1-year post-HTx at the time of annual protocol biopsy. RESULTS: Median age at transplant was 3 years (IQR .5-12.2). The median ferritin level was 32 ng/mL with 46% having ferritin < 30 ng/mL. Median transferrin saturation (TSAT) was 22% with 47% having TSAT < 20%. Median hemoglobin was 11 g/dL with 54% having anemia. Multivariable analysis revealed lower absolute lymphocyte count, TSAT < 20%, and estimated glomerular filtration rate <75 mL/min/1.73 m2 were independently associated with anemia. Ferritin < 30 ng/mL in isolation was not associated with anemia. Ferritin < 30 ng/mL may aid in detecting absolute iron deficiency while TSAT < 20% may be useful in identifying patients with functional iron deficiency ± anemia in pediatric HTx recipients. CONCLUSION: Iron deficiency and anemia are highly prevalent in pediatric HTx recipients. Future studies are needed to assess the impact of iron deficiency, whether with or without anemia, on clinical outcomes in pediatric HTx recipients.

Pregnancy in Morrison Pouch: a case report.

Abdominal pregnancy is a rare form of ectopic pregnancy (accounting for 1% of all ectopic pregnancies). Depending on gestational age and its location various symptoms and signs may be exhibited. This study aimed to report a case of abdominal pregnancy occurring in the Morrison Pouch with a primary presentation of right upper quadrant pain and to highlight complications that may arise in the management of abdominal pregnancy located in the Morrison Pouch. A 22-year pregnant woman at gestation of 22 weeks presented with a right upper quadrant mass and pain. Ultrasound examination revealed a live extrauterine singleton at Morrison Pouch, full blood count showed severe anemia. The patient received a blood transfusion in seven days and underwent emergency laparotomy after experiencing sudden acute internal hemorrhage but died a few hours post laparotomy due to hemorrhagic shock. Abdominal pregnancy carries a high risk of maternal hemorrhage as described in this case.

Recognizing uterine torsion as a differential diagnosis in pregnant cats with severe anemia to provide appropriate and timely care in the absence of a definitive presurgical diagnosis.

A pregnant female domestic longhair cat ~8 mo of age was referred to the Western College of Veterinary Medicine (Saskatoon, Saskatchewan) for a diagnostic evaluation of severe anemia (PCV: 10.8%) after a 2-day period of lethargy. A CBC, serum biochemistry profile, FeLV/FIV testing, and abdominal radiographs were completed and did not determine a cause for the anemia. Abdominal ultrasonography identified 1 viable and 6 nonviable and fetuses, anechoic fluid in the uterus, and a mild volume of peritoneal effusion. A whole-blood transfusion and C-section with ovariohysterectomy were performed even though a definitive presurgical diagnosis for the anemia had not yet been established. Exploratory surgery revealed a left uterine horn torsion with a necrotic base, severe congestion, and 7 nonviable fetuses. Following surgery, the queen made a full clinical recovery. Key clinical message: Uterine torsion can be easily overlooked as a cause of severe anemia due to the relative infrequency of this condition in cats and the low sensitivity of ultrasonography to provide a definitive presurgical diagnosis. Client communication must emphasize the need for a prompt surgical intervention to establish the diagnosis and to save the cat, despite poor rates of neonatal survival. Once the animal is stabilized after surgery, further diagnostic tests and procedures are indicated if the cause of anemia has not yet been identified.

Reconnaître la torsion utérine comme un diagnostic différentiel chez les chattes gestantes souffrant d'anémie sévère afin de fournir des soins appropriés et opportuns en l'absence d'un diagnostic pré-chirurgical définitif. Une chatte domestique à poils longs, âgée d'environ 8 mois, a été référée au Western College of Veterinary Medicine (Saskatoon, Saskatchewan) pour une évaluation diagnostique d'anémie sévère (hématocrite : 10,8 %) après une période de léthargie de 2 jours. Une formule sanguine complète, un profil biochimique sérique, des tests FeLV/FIV et des radiographies abdominales ont été réalisés et n'ont pas permis de déterminer la cause de l'anémie. L'échographie abdominale a identifié 1 foetus viable et 6 non viables, du liquide anéchoïque dans l'utérus et un léger volume d'épanchement péritonéal. Une transfusion de sang total et une césarienne avec ovariohystérectomie ont été réalisées même si le diagnostic pré-chirurgical définitif de l'anémie n'avait pas encore été établi. La chirurgie exploratoire a révélé une torsion de la corne utérine gauche avec une base nécrotique, une congestion sévère et 7 foetus non viables. Après l'opération, la chatte s'est complètement rétablie cliniquement.Message clinique clé:La torsion utérine peut facilement être négligée comme cause d'anémie sévère en raison de la rareté relative de cette affection chez le chat et de la faible sensibilité de l'échographie pour fournir un diagnostic pré-chirurgical définitif. La communication avec le client doit souligner la nécessité d'une intervention chirurgicale rapide pour établir le diagnostic et sauver le chat, malgré de faibles taux de survie néonatale. Une fois l'animal stabilisé après la chirurgie, d'autres tests et procédures de diagnostic sont indiqués si la cause de l'anémie n'a pas encore été identifiée.(Traduit par Dr Serge Messier).

The relationship between menorrhagia, iron deficiency, and anaemia in recreationally active females: An exploratory population based screening study.

OBJECTIVES: Iron deficiency, anaemia, and menorrhagia - or heavy menstrual bleeding - are interrelated conditions that are highly prevalent and commonly underrecognised in exercising females of reproductive age. This study utilised a screening tool to identify risk factors and symptoms associated with heavy menstrual bleeding, iron deficiency, and anaemia in this population. DESIGN: An observational, cross sectional survey study was employed. METHODS: 1042 active females (aged 18-65) completed a comprehensive screening questionnaire and 887 (85 % compliance) provided a fingerprick blood sample for haemoglobin (Hb) concentration measurement. Women that presented as anaemic (defined as a [Hb] < 120 g/L) or deemed to be at risk of iron deficiency (120 < [Hb] < 130 g/L) were asked to complete follow-up blood tests to screen for iron studies. RESULTS: Average [Hb] was 134.2 ±â€¯12.1 g/L, with 94 individuals considered anaemic (10.6 %). Of the sample, 104 underwent follow-up blood tests; 51 (~49 %) presented with iron deficiency (defined as ferritin <30 µg/L). Based on survey responses, 274 (30.9 %) participants were determined to have heavy menstrual bleeding. Those presenting with heavy menstrual bleeding were younger, exercised fewer hours per week, and were more likely to have a history of iron deficiency or anaemia (all p < 0.05). Participants reporting a history of anaemia or iron deficiency were more likely to have heavy menstrual bleeding (anaemia: 39.7 %; iron deficiency; 36.9 %; both p < 0.05). CONCLUSIONS: In this cohort of exercising females of reproductive age, the prevalence of anaemia was 10.6 %. There is a strong association between heavy menstrual bleeding and a self-reported history of iron deficiency and anaemia. Greater awareness of heavy menstrual bleeding and its relationship with iron deficiency and anaemia is needed in this population. Non-invasive screening should be conducted to raise awareness and further understand the associated risk factors and symptomatology.

Hyponutrition among newly diagnosed gastric cancer.

OBJECTIVES: This study aims to determine the malnutrition status among Vietnamese patients newly diagnosed with gastric cancer (GC). BACKGROUND: GC remains the top rank of common and deadly diseases. With limited clinical manifestation, most GC patients were diagnosed at late stages when tumor is not radically resected. Malnutrition was associated with poor prognosis of GC, such as prolonged hospitalization, limited treatment efficacy and low survival rate. METHODS: The cross-sectional descriptive study recruited 77 patients newly diagnosed with GC and 90 healthy individuals (HC). The data used for this study were approved by the local Ethical Committee. The data were analysed on STATA 14.0 and GraphPad Prism 8.0. RESULTS: We observed the male dominant distribution in GC cohort and over 65% of GC were firstly diagnosed at advanced stages (III and IV). Anemia was detected in about 50% of GC patients. Hyponutrition was prevalent in newly diagnosed GC. We found the decreased tendency of anemia related indexes from HC to early stages (I and II) and advanced stages (III and IV) of GC patients. CONCLUSION: Anemia and hypoproteinemia occurred frequently among Vietnamese newly diagnosed GC. The nutrition therapy would benefit GC patients (Tab. 4, Fig. 4, Ref. 20).

Prediction of anemia in real-time using a smartphone camera processing conjunctival images.

Anemia is defined as a low hemoglobin (Hb) concentration and is highly prevalent worldwide. We report on the performance of a smartphone application (app) that records images in RAW format of the palpebral conjunctivae and estimates Hb concentration by relying upon computation of the tissue surface high hue ratio. Images of bilateral conjunctivae were obtained prospectively from a convenience sample of 435 Emergency Department patients using a dedicated smartphone. A previous computer-based and validated derivation data set associating estimated conjunctival Hb (HBc) and the actual laboratory-determined Hb (HBl) was used in deriving Hb estimations using a self-contained mobile app. Accuracy of HBc was 75.4% (95% CI 71.3, 79.4%) for all categories of anemia, and Bland-Altman plot analysis showed a bias of 0.10 and limits of agreement (LOA) of (-4.73, 4.93 g/dL). Analysis of HBc estimation accuracy around different anemia thresholds showed that AUC was maximized at transfusion thresholds of 7 and 9 g/dL which showed AUC values of 0.92 and 0.90 respectively. We found that the app is sufficiently accurate for detecting severe anemia and shows promise as a population-sourced screening platform or as a non-invasive point-of-care anemia classifier.

HemoCue Hb-801 Provides More Accurate Hemoglobin Assessment in Blood Donors Than OrSense NBM-200.

Hemoglobin levels are commonly assessed to prevent causing or worsening of anemia in prospective blood donors. We compared head-to-head the accuracy of different technologies for measuring hemoglobin suitable for use in mobile donation units. We included 144 persons donating platelets at the Central Institute for Blood Transfusion and Immunology in Innsbruck, Austria. Hemoglobin levels were measured in venous blood using the portable hemoglobinometer HemoCue Hb-801 and noninvasively using OrSense NBM-200, and compared to values obtained with the Sysmex XN-430, an automated hematology analyzer employing the sodium lauryl sulphate method, which is broadly used as reference method in everyday clinical practice. Mean age of participants was 34.2 years (SD 13.0); 34.0% were female. Hemoglobin values measured with HemoCue were more strongly correlated with the Sysmex XN-430 (r = 0.90 [95% CI: 0.87-0.93]) than measured with OrSense (r = 0.49 [0.35-0.60]). On average, HemoCue overestimated hemoglobin by 0.40 g/dL (0.31-0.48) and OrSense by 0.75 g/dL (95% CI: 0.54-0.96). When using OrSense, we found evidence for higher overestimation at higher hemoglobin levels (proportional bias) specifically in females but not in males (Pdifference = .003). Sensitivity and specificity for classifying donors according to the hemoglobin donation thresholds were 99.2% (95% CI: 95.3%-100.0%) and 43.8% (23.1%-66.8%) for HemoCue vs 95.3% (89.9%-98.0%) and 12.5% (2.2%-37.3%) for OrSense. Areas under the receiver operating characteristic curves were higher using HemoCue vs OrSense both in females (0.933 vs 0.547; P = .044) and males (0.948 vs 0.628; P < .001). HemoCue Hb-801 measures hemoglobin more accurately than OrSense NBM-200 in the setting of mobile blood donation units. Our findings are particularly relevant for females, having in mind that anemia is more prevalent in females than in males.

Application of machine learning methods for predicting childhood anaemia: Analysis of Ethiopian Demographic Health Survey of 2016.

Childhood anaemia is a public health problem in Ethiopia. Machine learning (ML) is a growing in medicine field to predict diseases. Diagnosis of childhood anaemia is resource intensive. The aim of this study is to apply machine learning (ML) algorithm to predict childhood anaemia using socio-demographic, economic, and maternal and child related variables. The study used data from 2016 Ethiopian demographic health survey (EDHS). We used Python software version 3.11 to apply and test ML algorithms through logistic regression, Random Forest (RF), Decision Tree, and K-Nearest Neighbours (KNN). We evaluated the performance of each of the ML algorithms using discrimination and calibration parameters. The predictive performance of the algorithms was between 60% and 66%. The logistic regression model was the best predictive model of ML with accuracy (66%), sensitivity (82%), specificity (42%), and AUC (69%), followed by RF with accuracy (64%), sensitivity (79%), specificity (42%), and AUC (63%). The logistic regression and the RF models of ML showed poorest family, child age category between 6 and 23 months, uneducated mother, unemployed mother, and stunting as high importance predictors of childhood anaemia. Applying logistic regression and RF models of ML can detect combinations of predictors of childhood anaemia that can be used in primary health care professionals.

A Prospective Observational Study Analyzing the Diagnostic Value of Hepcidin-25 for Anemia in Patients with Inflammatory Bowel Diseases.

Iron deficiency (IDA) and chronic disease (ACD) anemia are complications of inflammatory bowel diseases (IBDs). Therapeutic modalities in remission and active IBD depend on the type of anemia. This study evaluated the link between hepcidin-25, proinflammatory cytokines, and platelet activation markers as biomarkers of anemia and inflammation in active IBD and remission. This prospective observational study included 62 patients with IBD (49 with ulcerative colitis and 13 with Crohn's) and anemia. Patients were divided into Group I (no or minimal endoscopic signs of disease activity and IDA), Group II (moderate and major endoscopic signs of disease activity and mild ACD), and Control group (10 patients with IBD in remission, without anemia). We assessed the difference among groups in the levels of CRP, hemoglobin (Hgb), serum iron, ferritin, hepcidin-25, interleukins, TNF-α, IFN-γ, soluble CD40 ligand, and sP-selectin. Hepcidin-25 levels were significantly higher in Group II versus Group I (11.93 vs. 4.48 ng/mL, p < 0.001). Ferritin and CRP values showed similar patterns in IBD patients: significantly higher levels were observed in Group II (47.5 ng/mL and 13.68 mg/L) than in Group I (11.0 ng/mL and 3.39 mg/L) (p < 0.001). In Group II, hepcidin-25 was positively correlated with ferritin (ρ = 0.725, p < 0.001) and CRP (ρ = 0.502, p = 0.003). Ferritin was an independent variable influencing hepcidin-25 concentration in IBD patients, regardless of disease activity and severity of anemia. IBD hepcidin-25 best correlates with ferritin, and both parameters reflected inflammation extent and IBD activity.

Affordable Method for Hematocrit Determination in Murine Models.

Hematocrit (Hct) is a powerful tool often used in a clinical setting for the diagnosis of blood conditions such as anemia. It is also used in the research field as a hematological parameter in both human and mouse models. Measuring Hct, however, involves the use of expensive standardized equipment (such as a CritSpin™ Microhematocrit Centrifuge). Here, we describe a novel, simple, and affordable method to determine the Hct in untreated wild-type (WT) mice and phenylhydrazine (PHZ)-induced anemic mice with reasonable accuracy, using a benchtop centrifuge commonly available in laboratories. Hct of murine samples processed with a benchtop centrifuge, when compared to the standardized method CritSpin™, showed comparable results. This approach for determining Hct of murine can prove useful to research laboratories that cannot afford specialized equipment for Hct studies. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Affordable Method for Hematocrit Determination in Murine Models Basic Protocol 2: Murine Sample Validation Support Protocol: Phenylhydrazine-induced anemia in wild-type (WT) mice.

Estimation of haemoglobin using non-invasive portable device with spectroscopic signal application.

An estimated 52% of non-pregnant women of reproductive age in India are estimated to be affected by anaemia, which is categorised as a chronic condition. In 2019-2021, the National Family Health Survey-5 (NFHS-5) which was undertaken revealed the following statistics about the prevalence of anaemia in the state of Karnataka. To estimate haemoglobin levels using non-invasive portable device among nursing students. A cross sectional study was done among students of Nursing college in central Karnataka for a period of 3 months. Total of 140 students were included in the study. EzeCheck haemoglobin estimation was done twice and was recorded in the same Google form. The frequency and percentage of variation of results between Haematology Analyzer and EzeCheck devices was presented with a range of difference such as 0, less than 1, 1.0 to 1.9, 2.0 to 2.9, 3.0 to 3.9, and 4.0 and above. The total prevalence of anaemia among nursing students was 57.8% and most of the students had moderate degree of anaemia (28.6%). Two readings of haemoglobin were taken and difference of readings were calculated and majority of the students had difference of < 0.5 gm/dl (61.4%) and only 1.4% of the students had difference of > 2 gm/dl. The mean difference of haemoglobin of two readings was 0.5 ± 0.5 gm/dl. The technology employed in this study bridges the gap between patients and anaemia diagnosis by providing screening services. The device provides the diagnosis via a non-invasive, IoT-enabled service at a low cost.

Employing supervised machine learning algorithms for classification and prediction of anemia among youth girls in Ethiopia.

In developing countries, one-quarter of young women have suffered from anemia. However, the available studies in Ethiopia have been usually used the traditional stastical methods. Therefore, this study aimed to employ multiple machine learning algorithms to identify the most effective model for the prediction of anemia among youth girls in Ethiopia. A total of 5642 weighted samples of young girls from the 2016 Ethiopian Demographic and Health Survey dataset were utilized. The data underwent preprocessing, with 80% of the observations used for training the model and 20% for testing. Eight machine learning algorithms were employed to build and compare models. The model performance was assessed using evaluation metrics in Python software. Various data balancing techniques were applied, and the Boruta algorithm was used to select the most relevant features. Besides, association rule mining was conducted using the Apriori algorithm in R software. The random forest classifier with an AUC value of 82% outperformed in predicting anemia among all the tested classifiers. Region, poor wealth index, no formal education, unimproved toilet facility, rural residence, not used contraceptive method, religion, age, no media exposure, occupation, and having more than 5 family size were the top attributes to predict anemia. Association rule mining was identified the top seven best rules that most frequently associated with anemia. The random forest classifier is the best for predicting anemia. Therefore, making it potentially valuable as decision-support tools for the relevant stakeholders and giving emphasis for the identified predictors could be an important intervention to halt anemia among youth girls.