High frequency of Plasmodium falciparum chloroquine resistance marker (pfcrt T76 mutation) in Yemen: An urgent need to re-examine malaria drug policy

<p>Abstract</p> <p>Background</p> <p>Malaria remains a significant health problem in Yemen with <it>Plasmodium falciparum </it>being the predominant species which is responsible for 90% of the malaria cases. Despite serious concerns regarding increasing drug resistance, chloroquine is still used for the prevention and treatment of malaria in Yemen. This study was carried out to determine the prevalence of choloroquine resistance (CQR) of <it>P. falciparum </it>isolated from Yemen based on the <it>pfcrt </it>T76 mutation.</p> <p>Methods</p> <p>A cross-sectional study was carried out among 511 participants from four governorates in Yemen. Blood samples were screened using microscopic and species-specific nested PCR based on the 18S rRNA gene to detect and identify <it>Plasmodium </it>species. Blood samples positive for <it>P. falciparum </it>were used for detecting the <it>pfcrt </it>T76 mutation using nested-PCR.</p> <p>Results</p> <p>The prevalence of <it>pfcrt </it>T76 mutation was 81.5% (66 of 81 isolates). Coastal areas/foothills had higher prevalence of <it>pfcrt </it>T76 mutation compared to highland areas (90.5% <it>vs </it>71.8%) (p = 0.031). The <it>pfcrt </it>T76 mutation had a significant association with parasitaemia (p = 0.045). Univariate analysis shows a significant association of <it>pfcrt </it>T76 mutation with people aged > 10 years (OR = 9, 95% CI = 2.3 - 36.2, p = 0.001), low household income (OR = 5, 95% CI = 1.3 - 19.5, p = 0.027), no insecticide spray (OR = 3.7, 95% CI = 1.16 - 11.86, p = 0.025) and not sleeping under insecticide treated nets (ITNs) (OR = 4.8, 95% CI = 1.38 - 16.78, p = 0.01). Logistic regression model confirmed age > 10 years and low household income as predictors of <it>pfcrt </it>T76 mutation in Yemen <it>P. falciparum </it>isolates.</p> <p>Conclusions</p> <p>The high prevalence of <it>pfcrt </it>T76 mutation in Yemen could be a predictive marker for the prevalence of <it>P. falciparum </it>CQR. This finding shows the necessity for an in-vivo therapeutic efficacy test for CQ.<it> P. falciparum </it>CQR should be addressed in the national strategy to control malaria.</p

A szívinfarktus miatt kezelt betegek ellátása Magyarországon. A Nemzeti Szívinfarktus Regiszter 2015. évi adatainak elemzése

The authors summarize the most relevant data of myocardial infarction patients according to the National Myocardial Infarction Registry data base. In 2015 12,681 patients had 12,941 acute myocardial infarctions. Less than half of patients (44.4%) were treated with ST elevation myocardial infarction. National Ambulance Service was the first medical contact of more than half (51.4%) of patients with ST elevation infarction. Prehospital thrombolysis was occasionally done (0.23%), but 91.6% of the patients were treated in hospital with invasive facilities. The median of the ischaemic time (time between onset of symptoms and arrival at the invasive laboratory) was 223 minutes. Most of the patients (94%) with positive coronary arteriography were treated with percutaneous coronary intervention. The 30 day mortality of the whole group was 12.8% vs. 8.6% of patients treated with an invasive procedure. CONCLUSION: comparing the national and international registry data we conclude that we should analyse and decrease the prehospital delay time to improve the patient care in Hungary. Orv. Hetil., 2017, 158(3), 90-93

The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis

<p>Abstract</p> <p>Background</p> <p>This is the second in a series of three articles documenting the geographical distribution of 41 dominant vector species (DVS) of human malaria. The first paper addressed the DVS of the Americas and the third will consider those of the Asian Pacific Region. Here, the DVS of Africa, Europe and the Middle East are discussed. The continent of Africa experiences the bulk of the global malaria burden due in part to the presence of the <it>An. gambiae </it>complex. <it>Anopheles gambiae </it>is one of four DVS within the <it>An. gambiae </it>complex, the others being <it>An. arabiensis </it>and the coastal <it>An. merus </it>and <it>An. melas</it>. There are a further three, highly anthropophilic DVS in Africa, <it>An. funestus</it>, <it>An. moucheti </it>and <it>An. nili</it>. Conversely, across Europe and the Middle East, malaria transmission is low and frequently absent, despite the presence of six DVS. To help control malaria in Africa and the Middle East, or to identify the risk of its re-emergence in Europe, the contemporary distribution and bionomics of the relevant DVS are needed.</p> <p>Results</p> <p>A contemporary database of occurrence data, compiled from the formal literature and other relevant resources, resulted in the collation of information for seven DVS from 44 countries in Africa containing 4234 geo-referenced, independent sites. In Europe and the Middle East, six DVS were identified from 2784 geo-referenced sites across 49 countries. These occurrence data were combined with expert opinion ranges and a suite of environmental and climatic variables of relevance to anopheline ecology to produce predictive distribution maps using the Boosted Regression Tree (BRT) method.</p> <p>Conclusions</p> <p>The predicted geographic extent for the following DVS (or species/suspected species complex*) is provided for Africa: <it>Anopheles </it>(<it>Cellia</it>) <it>arabiensis</it>, <it>An. </it>(<it>Cel.</it>) <it>funestus*</it>, <it>An. </it>(<it>Cel.</it>) <it>gambiae</it>, <it>An. </it>(<it>Cel.</it>) <it>melas</it>, <it>An. </it>(<it>Cel.</it>) <it>merus</it>, <it>An. </it>(<it>Cel.</it>) <it>moucheti </it>and <it>An. </it>(<it>Cel.</it>) <it>nili*</it>, and in the European and Middle Eastern Region: <it>An. </it>(<it>Anopheles</it>) <it>atroparvus</it>, <it>An. </it>(<it>Ano.</it>) <it>labranchiae</it>, <it>An. </it>(<it>Ano.</it>) <it>messeae</it>, <it>An. </it>(<it>Ano.</it>) <it>sacharovi</it>, <it>An. </it>(<it>Cel.</it>) <it>sergentii </it>and <it>An. </it>(<it>Cel.</it>) <it>superpictus*</it>. These maps are presented alongside a bionomics summary for each species relevant to its control.</p