Chittagong Medical College Hospital

About: Chittagong Medical College Hospital is a healthcare organization based out in Chittagong, Bangladesh. It is known for research contribution in the topics: Population & Malaria. The organization has 676 authors who have published 601 publications receiving 7040 citations.

Spread of Artemisinin Resistance in Plasmodium falciparum Malaria

Abstract: BACKGROUND: Artemisinin resistance in Plasmodium falciparum has emerged in Southeast Asia and now poses a threat to the control and elimination of malaria. Mapping the geographic extent of resistance is essential for planning containment and elimination strategies. METHODS: Between May 2011 and April 2013, we enrolled 1241 adults and children with acute, uncomplicated falciparum malaria in an open-label trial at 15 sites in 10 countries (7 in Asia and 3 in Africa). Patients received artesunate, administered orally at a daily dose of either 2 mg per kilogram of body weight per day or 4 mg per kilogram, for 3 days, followed by a standard 3-day course of artemisinin-based combination therapy. Parasite counts in peripheral-blood samples were measured every 6 hours, and the parasite clearance half-lives were determined. RESULTS: The median parasite clearance half-lives ranged from 1.9 hours in the Democratic Republic of Congo to 7.0 hours at the Thailand-Cambodia border. Slowly clearing infections (parasite clearance half-life >5 hours), strongly associated with single point mutations in the "propeller" region of the P. falciparum kelch protein gene on chromosome 13 (kelch13), were detected throughout mainland Southeast Asia from southern Vietnam to central Myanmar. The incidence of pretreatment and post-treatment gametocytemia was higher among patients with slow parasite clearance, suggesting greater potential for transmission. In western Cambodia, where artemisinin-based combination therapies are failing, the 6-day course of antimalarial therapy was associated with a cure rate of 97.7% (95% confidence interval, 90.9 to 99.4) at 42 days. CONCLUSIONS: Artemisinin resistance to P. falciparum, which is now prevalent across mainland Southeast Asia, is associated with mutations in kelch13. Prolonged courses of artemisinin-based combination therapies are currently efficacious in areas where standard 3-day treatments are failing. (Funded by the U.K. Department of International Development and others; ClinicalTrials.gov number, NCT01350856.).

Strategy for a globally coordinated response to a priority neglected tropical disease: Snakebite envenoming.

Abstract: In one of his final essays, statesman and former United Nations secretary general Kofi Annan said, ‘Snakebite is the most important tropical disease you’ve never heard of’ [1]. Mr. Annan firmly believed that victims of snakebite envenoming should be recognised and afforded greater efforts at improved prevention, treatment, and rehabilitation. During the last years of his life, he advocated strongly for the World Health Organisation (WHO) and the global community to give greater priority to this disease of poverty and its victims.

The Relationship between Age and the Manifestations of and Mortality Associated with Severe Malaria

Abstract: P ! .001 decreased risk of death among children (adjusted odds ratio, 0.06; 95% confidence interval, 0.01–0.23; ) P ! .001 and the increased risk of death among patients aged 150 years (adjusted odds ratio, 1.88; 95% confidence interval, 1.01–3.52; ) was independent of the variation in presenting manifestations. The incidence of anemia and P p .046 convulsions decreased with age, whereas the incidence of hyperparasitemia, jaundice, and renal insufficiency increased with age. Coma and metabolic acidosis did not vary with age and were the strongest predictors of a fatal outcome. The number of severity signs at hospital admission also had a strong prognostic value. Conclusion. Presenting syndromes in severe malaria depend on age, although the incidence and the strong prognostic significance of coma and acidosis are similar at all ages. Age is an independent risk factor for a fatal outcome of the disease.

Direct In Vivo Assessment of Microcirculatory Dysfunction in Severe Falciparum Malaria

Abstract: Background This study sought to describe and quantify microcirculatory changes in the mucosal surfaces of patients with severe malaria, by direct in vivo observation using orthogonal polarization spectral (OPS) imaging. Methods The microcirculation in the rectal mucosa of adult patients with severe malaria was assessed by use of OPS imaging, at admission and then daily. Comparison groups comprised patients with uncomplicated falciparum malaria, patients with bacterial sepsis, and healthy individuals. Results Erythrocyte velocities were measured directly in 43 adult patients with severe falciparum malaria, of whom 20 died. Microcirculatory blood flow was markedly disturbed, with heterogeneous obstruction that was proportional to severity of disease. Blocked capillaries were found in 29 patients (67%) and were associated with concurrent hyperdynamic blood flow (erythrocyte velocity, >750 mm/s) in adjacent vessels in 27 patients (93%). The proportion of blocked capillaries correlated with the base deficit in plasma and with the concentration of lactate. Abnormalities disappeared when the patients recovered. In healthy individuals and in patients with uncomplicated malaria or sepsis, no stagnant erythrocytes were detected, and, in patients with sepsis, hyperdynamic blood flow was prominent. Conclusion Patients with severe falciparum malaria show extensive microvascular obstruction that is proportional to the severity of the disease. This finding underscores the prominent role that microvascular obstruction plays in the pathophysiology of severe malaria and illustrates the fundamental difference between the microvascular pathophysiology of malaria and that of bacterial sepsis.

CNN-based image analysis for malaria diagnosis

Abstract: Malaria is a major global health threat. The standard way of diagnosing malaria is by visually examining blood smears for parasite-infected red blood cells under the microscope by qualified technicians. This method is inefficient and the diagnosis depends on the experience and the knowledge of the person doing the examination. Automatic image recognition technologies based on machine learning have been applied to malaria blood smears for diagnosis before. However, the practical performance has not been sufficient so far. This study proposes a new and robust machine learning model based on a convolutional neural network (CNN) to automatically classify single cells in thin blood smears on standard microscope slides as either infected or uninfected. In a ten-fold cross-validation based on 27,578 single cell images, the average accuracy of our new 16-layer CNN model is 97.37%. A transfer learning model only achieves 91.99% on the same images. The CNN model shows superiority over the transfer learning model in all performance indicators such as sensitivity (96.99% vs 89.00%), specificity (97.75% vs 94.98%), precision (97.73% vs 95.12%), F1 score (97.36% vs 90.24%), and Matthews correlation coefficient (94.75% vs 85.25%).