Severe Plasmodium ovale malaria complicated by acute respiratory distress syndrome in a young Caucasian man

D’Abramo, Alessandra; Teklè, Saba Gebremeskel; Iannetta, Marco; Scorzolini, Laura; Oliva, Alessandra; Paglia, Maria Grazia; Corpolongo, Angela; Nicastri, Emanuele

doi:10.1186/s12936-018-2289-2

Cited by 13 publications

(8 citation statements)

References 11 publications

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“…However, P. ovale can cause severe complications and death [19,20]. Previous studies have reported that the severe complications of P. ovale infections include acute respiratory distress syndrome (ARDS) [21][22][23][24][25][26], renal impairment [24,27], jaundice, and hypotension [26,27]. The most recent study on severe P. ovale malaria in travelers and migrants demonstrated that 5.3% of patients with P. ovale developed severe complications according to the 2015 WHO criteria, including hyperbilirubinemia, pulmonary edema, shock, significant bleeding, and impaired consciousness [28].…”

Section: Introductionmentioning

confidence: 99%

Severity and mortality of severe Plasmodium ovale infection: A systematic review and meta-analysis

Kotepui

Milanez

et al. 2020

PLoS ONE

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Plasmodium ovale can infect humans, causing malaria disease. We aimed to investigate the severity and mortality of severe P. ovale infection to increase the awareness of physicians regarding the prognosis of this severe disease and outcome-related deaths in countries in which this disease is endemic. Articles that were published in the PubMed, Scopus, and ISI Web of Science databases prior to January 5, 2020 and reported the prevalence of severe P. ovale infection were systematically searched and reviewed. Studies that mainly reported severe P. ovale infection according to the 2014 WHO criteria for the treatment of malaria were included. Two reviewers selected, identified, assessed, and extracted data from studies independently. The pooled prevalence of severe P. ovale mono-infections was estimated using the command "metaprop case population, random/fixed", which yielded the pooled estimate, 95% confidence interval (CI) and the I 2 value, indicating the level of heterogeneity. Meta-analyses of the proportions were performed using a random-effects model to explore the different proportions of severity between patients with P. ovale and those with other Plasmodium species infections. Among the eight studies that were included and had a total of 1,365 ovale malaria cases, the pooled prevalence of severe P. ovale was 0.03 (95% CI = 0.03-0.05%, I 2 = 54.4%). Jaundice (1.1%), severe anemia (0.88%), and pulmonary impairments (0.59%) were the most common severe complications found in patients infected with P. ovale. The meta-analysis demonstrated that a smaller proportion of patients with P. ovale than of patients with P. falciparum had severe infections (P-value = 0.01, OR = 0.36, 95% CI = 0.16-0.81, I 2 = 72%). The mortality rate of severe P. ovale infections was 0.15% (2/1,365 cases). Although severe complications of P. ovale infections in patients are rare, it is very important to increase the awareness of physicians regarding the prognosis of severe P. ovale infections in patients, especially in a high-risk population.

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Section: Introductionmentioning

confidence: 99%

Severity and mortality of severe Plasmodium ovale infection: A systematic review and meta-analysis

Kotepui

Milanez

et al. 2020

PLoS ONE

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“…P. ovale infection would not have been identified without a sensitive molecular test. P. ovale, which is now separated into the two sympatric species Plasmodium ovale curtisi and Plasmodium ovale wallikeri, is generally linked to rather mild disease but severe complications can develop [19]. The delay in the manifestation of symptomatic disease is characteristic even when atovaquone/proguanil chemoprophylaxis has been used.…”

Section: Discussionmentioning

confidence: 99%

Diagnosis of malaria in a traveler 9 months after returning from West Africa by illumigene® LAMP assay: A case report

Reuken

Baier

Hagel

et al. 2019

AMicr

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Loop-mediated isothermal amplification (LAMP) is a rapid molecular technique that has been introduced into malaria diagnosis. The test is easy to perform and offers high sensitivity. We report a 53-year-old male patient who was hospitalized with fever attacks, chills, and headache caused 9 months after returning from Africa. During his stay in Africa, he used malaria chemoprophylaxis. Microscopy of thin and thick blood films and rapid diagnostic antigen testing remained negative for three times. The EDTA blood samples were tested using the Meridian illumigene ® malaria LAMP assay that gave a positive result for Plasmodium spp. Diagnosis of malaria was subsequently specified as P. ovale infection by real-time PCR. Ovale malaria often manifests with delay and low parasitemia. The patient was treated with atovaquoneproguanil, followed by primaquine for prophylaxis of relapse. This case illustrates the usefulness of the illumigene ® malaria LAMP assay for initial screening of malaria parasites.

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“…Bronchitis COVID-19 X*** (11) X* (10) X** (13) X* (10) X*** (11) Dengue X* (12,17) X** (12) X** (12,17) X*** (12) X*** (12) Malaria X** (8 ) X** (1 ) X** (13 ) X** (1 ) X** (8 ) Streptococcus pneumoniae X** (9) X** (9) X*** (6) X** (6,9) X* (6,9) Tuberculosis X* (15,18) X** (2) X** (14) X* (15,2,18) X* (15,18) * ordinary; ** 40-60% of cases; *** uncommon; mon * are significantly different; ** are not significantly different.…”

Section: Rounded Morphological Opacitiesmentioning

confidence: 99%

Intelligent Computational Model for the Classification of Covid-19 with Chest Radiography Compared to other Respiratory Diseases

Santos¹

2021

Computer Science &Amp; Information Technology (CS &Amp; IT)

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Lung X-ray images, if processed using statistical and computational methods, can distinguish pneumonia from COVID-19. The present work shows that it is possible to extract lung X-ray characteristics to improve the methods of examining and diagnosing patients with suspected COVID-19, distinguishing them from malaria, dengue, H1N1, tuberculosis, and Streptococcus pneumonia. More precisely, an intelligent computational model was developed to process lung X-ray images and classify whether the image is of a patient with COVID-19. The images were processed and extracted their characteristics. These characteristics were the input data for an unsupervised statistical learning method, PCA, and clustering, which identified specific attributes of X-ray images with Covid-19. The introduction of statistical models allowed a fast algorithm, which used the X-means clustering method associated with the Bayesian Information Criterion (CIB). The developed algorithm efficiently distinguished each pulmonary pathology from X-ray images. The method exhibited excellent sensitivity. The average recognition accuracy of COVID-19 was 0.93 ± 0.051.

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Severe Plasmodium ovale malaria complicated by acute respiratory distress syndrome in a young Caucasian man

Cited by 13 publications

References 11 publications

Severity and mortality of severe Plasmodium ovale infection: A systematic review and meta-analysis

Severity and mortality of severe Plasmodium ovale infection: A systematic review and meta-analysis

Diagnosis of malaria in a traveler 9 months after returning from West Africa by illumigene® LAMP assay: A case report

Intelligent Computational Model for the Classification of Covid-19 with Chest Radiography Compared to other Respiratory Diseases

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