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Record W2914115366 · doi:10.1101/537027

What is the explanation for <i>Plasmodium vivax</i> malarial recurrence? Experience of Parasitology Unit of Kinshasa University Hospital of 1982-1983 and 2000-2009

2019· preprint· en· W2914115366 on OpenAlexaff
Guyguy Kabundi Tshima

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMalariaPlasmodium vivaxParasitologyContext (archaeology)Vivax malariaTropical medicinePlasmodium falciparumRapid diagnostic testDiagnostic testMedicineBiologyImmunologyPathologyVeterinary medicine

Abstract

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Abstract Context and Objectives Microscopy is needed for a study involving the surveillance data of a species like P. vivax , the most widespread in Asia and almost non-existent species in the Democratic Republic of the Congo (DRC). The use of microscopy and rapid diagnostics tests (RDTs) approaches are recommended for malaria test. Considering the advantages and disadvantages of the two, microscopy is more suitable for effective identification of presence of malaria parasites for the surveillance data of P. vivax and other species. Rapid diagnostics tests fit better for P. falciparum . This study aimed to revise between the Microscopy and RDTs, which is better for used in city than in rural settings for the surveillance of Plasmodium vivax malarial recurrence in malaria-endemic areas and why? Methods It is a descriptive study of 19,746 laboratory data. The variables wanted were a positive thick drop and a thin smear with the plasmodial species. The analyzes were carried out based on prevalences and the software R was used to generate the figures. The standard threshold of statistical significance was set at 0.05. The ethics committee of the Department of Tropical Medicine approved this study. We were using microscopes as our diagnostic tools for malaria surveillance data in the Parasitology Unit. RDTs are the quickest way to detect and diagnose malaria. It is something that could be easily operated. It can be home-based for everyone depending his understand the principles of how it works. It is also effective and time management. Therefore, this can be used in rural areas because it will be fast to attend to many people. But it has its own limitations because of the differentiation of species. And it not detects P. vivax , P. ovale and P. malariae . Results From 100% malaria-positive samples, 98.83% were positive for P. falciparum , 0.88% were positive for P. malariae , 0.063% were positive for P. ovale , 0.01% was positive for P. vivax . There were co-infections P. falciparum-P. malariae representing 0.2%. November 2001 had the high number of positive samples. Conclusions P. vivax at 0.01% highlights that it is an unknown species in the DRC. P. malariae at 1% advances our understanding of microscopy utility in the diagnosis of renal failure. P. falciparum at 98.83% highlights that it remains the most prevalent species. Efforts for malaria control should be focus on the rain months. Microscopes are effective. Depending on the accurate functionality of the tool and the expertise skill of the technician or scientist. Disadvantages are the facts that it is time consuming. And demands high intellectual understanding of the use of microscopy. Not everyone could operate a microscope. Before you view under the microscope you must prepare the slide and stain to be able to view. All these are long processes. Therefore, microscopy may have lower opportunity to be used in a rural area because of the complexity, the population and time. Microscopy has advantages to be important to use in rural areas because of its accuracy and the ability to detect Plasmodiums species than the RDTs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.256
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2019
Admission routes1
Has abstractyes

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