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Record W4417101631 · doi:10.1097/inf.0000000000005102

In Reply: A Perspective on Human Leishmaniasis and Novel Therapeutic Methods for Diagnosis, Prevention and Treatment

2025· article· en· W4417101631 on OpenAlexaff
Saad Arsalan Wasti, Ahmed Asif, Areesha Wasti

Bibliographic record

VenueThe Pediatric Infectious Disease Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsContinental (Canada)
Fundersnot available
KeywordsLeishmaniasisPerspective (graphical)Cutaneous leishmaniasisNeglected tropical diseasesHealth careMeglumine antimoniateDimension (graph theory)

Abstract

fetched live from OpenAlex

To the Editors: We read with great interest the recent review by Abbasi,1 “A perspective on human leishmaniasis and novel therapeutic methods for diagnosis, prevention and treatment,” published in the October 2025 issue of the Journal. The article thoughtfully synthesizes important advances in diagnostics, therapeutics and emerging molecular targets for leishmaniasis. However, we believe that an important dimension may benefit from further discussion: the disproportionate burden of leishmaniasis on vulnerable pediatric populations in low-resource, conflict-affected regions, particularly in Pakistan. In Pakistan, children represent a substantial proportion of reported cases of leishmaniasis, particularly cutaneous leishmaniasis (CL).2 Recent data from Khyber Pakhtunkhwa documented over 1559 pediatric CL cases from 2020 to 2022, with the highest frequency in children 5–9 years old.2 Conflict-affected districts such as Bajaur report prevalence exceeding 60%, reflecting a complex interplay between displacement, environmental exposure and disrupted healthcare access.3 The innovative diagnostic techniques highlighted by Abbasi, including polymerase chain reaction and loop-mediated isothermal amplification , offer meaningful promise. However, many high-burden areas continue to rely mainly on clinical diagnosis or smear microscopy. This gap is particularly relevant given the increasing recognition of atypical pediatric CL presentations, which may be more challenging to confirm without supportive laboratory tools.4 Improving access to feasible and affordable diagnostics may therefore strengthen local case detection and timely treatment. Similarly, while the review presents a concise summary of current and emerging therapies, practical barriers to availability persist in many low-resource pediatric settings. Pentavalent antimonials remain the predominant option despite logistical challenges, and children with suspected visceral leishmaniasis may experience delayed diagnosis. A study from Abbottabad found 13.2% positivity among children with pancytopenia tested for visceral leishmaniasis, accentuating the importance of maintaining clinical vigilance.5 Looking ahead, future reviews may also find value in exploring the psychosocial impact of pediatric CL. Children with visible or facial lesions frequently face stigma, reduced social participation and disruptions in schooling. Reports of elevated Children’s Dermatology Life Quality Index scores show how these experiences can affect long-term well-being. Integrating such quality-of-life perspectives could complement ongoing biomedical advances and help refine child-centered public health strategies. Future research could also focus on region-specific epidemiology, improving access to affordable diagnostics and treatment in remote or conflict-affected areas and evaluating the effectiveness of integrated interventions that combine clinical care, psychosocial support and community-based prevention. Such multidimensional approaches may provide actionable guidance for policymakers and healthcare providers seeking to reduce both the biomedical and social burdens of leishmaniasis in vulnerable pediatric populations.

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)0.007
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.041
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0020.004
Scholarly communication0.0050.011
Open science0.0040.003
Research integrity0.0190.038
Insufficient payload (model declined to judge)0.0080.007

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 head0.051
GPT teacher head0.438
Teacher spread0.387 · 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 designNot applicable
Domainnot available
GenreCommentary

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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Citations0
Published2025
Admission routes1
Has abstractyes

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