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Record W4200278035 · doi:10.3390/biology10121275

Alteration of Platelet Count in Patients with Severe Non-Plasmodium falciparum Malaria: A Systematic Review and Meta-Analysis

2021· review· en· W4200278035 on OpenAlexaboutno aff
Aongart Mahittikorn, Frederick Ramirez Masangkay, Kwuntida Uthaisar Kotepui, Wanida Mala, Giovanni De Jesus Milanez, Polrat Wilairatana, Manas Kotepui

Bibliographic record

VenueBiology · 2021
Typereview
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersWalailak University
KeywordsBiologyMalariaPlasmodium falciparumMeta-analysisImmunologyPlateletSevere MalariaVirologyPlasmodium (life cycle)Internal medicineParasite hosting

Abstract

fetched live from OpenAlex

The understanding of platelet biology under physiological and pathological conditions like malaria infection is critical importance in the context of the disease outcome or model systems used. The importance of severe thrombocytopenia (platelet count < 50,000 cells (µL) and profound thrombocytopenia (platelet count < 20,000 cells/µL) in malaria patients remains unclear. This study aimed to synthesize evidence regarding the risks of severe and profound thrombocytopenia in patients with severe non-Plasmodium falciparum malaria. Our overall aim was to identify potential indicators of severe non-P. falciparum malaria and the Plasmodium species that cause severe outcomes. This systematic review was registered at the International Prospective Register of Systematic Reviews (PROSPERO) under registration ID CRD42020196541. Studies were identified from previous systematic reviews (n = 5) and the MEDLINE, Scopus, and Web of Science databases from 9 June 2019 to 9 June 2020. Studies were included if they reported the outcome of severe non-Plasmodium species infection, as defined by the World Health Organization (WHO) criteria, in patients with known platelet counts and/or severe and profound thrombocytopenia. The risk of bias was assessed using the Newcastle–Ottawa Scale (NOS). Data were pooled, and pooled prevalence (PP) and pooled odds ratios (ORs) were calculated using random effects models. Of the 118 studies identified from previous meta-nalyses, 21 met the inclusion criteria. Of the 4807 studies identified from the databases, three met the inclusion criteria. Nine studies identified from reference lists and other sources also met the inclusion criteria. The results of 33 studies reporting the outcomes of patients with severe P. vivax and P. knowlesi infection were pooled for meta-analysis. The PP of severe thrombocytopenia (reported in 21 studies) was estimated at 47% (95% confidence interval (CI): 33–61%, I2: 96.5%), while that of profound thrombocytopenia (reported in 13 studies) was estimated at 20% (95% CI: 14–27%, 85.2%). The pooled weighted mean difference (WMD) in platelet counts between severe uncomplicated Plasmodium infections (reported in 11 studies) was estimated at −28.51% (95% CI: −40.35–61%, I2: 97.7%), while the pooled WMD in platelet counts between severe non-Plasmodium and severe P. falciparum infections (reported in eight studies) was estimated at −3.83% (95% CI: −13.90–6.25%, I2: 85.2%). The pooled OR for severe/profound thrombocytopenia comparing severe to uncomplicated Plasmodium infection was 2.92 (95% CI: 2.24–3.81, I2: 39.9%). The PP of death from severe and profound thrombocytopenia was estimated at 11% (95% CI: 0–22%). These results suggest that individuals with severe non-P. falciparum infection (particularly P. vivax and P. knowlesi) who exhibit severe or profound thrombocytopenia should be regarded as high risk, and should be treated for severe malaria according to current WHO guidelines. In addition, severe or profound thrombocytopenia coupled with other clinical and microscopic parameters can significantly improve malaria diagnosis, enhance the timely treatment of malaria infections, and reduce the morbidity and mortality of severe non-P. falciparum malaria.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.831
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.334
Teacher spread0.290 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations9
Published2021
Admission routes1
Has abstractyes

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