Evidence map›Paper›PMID 40672782›Full record

ArticleThe Lancet regional health. Southeast Asia2025

Development and internal validation of clinical prediction models for scrub typhus and doxycycline-treatable causes in paediatric acute encephalitis syndrome in Karnataka, India: a multicentre, prospective study.

Tina Damodar, Maria Jose, Uddhava V Kinhal, Bhagteshwar Singh, Surbhi Telang, Akhila Lekha, Srilatha Marate, Namratha Prabhu, Chitra Pattabiraman, Prathyusha Parthipulli Vasuki and 13 more

Abstract read
In one paragraph

Article in The Lancet regional health. Southeast Asia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors.

Tina DamodarNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Maria JoseNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Uddhava V KinhalIndira Gandhi Institute of Child Health, Bengaluru, India.
Bhagteshwar SinghInstitute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK.
Surbhi TelangNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Akhila LekhaNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Srilatha MarateNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Namratha PrabhuNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Chitra PattabiramanNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Prathyusha Parthipulli VasukiNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
A V LalithaSt John's Medical College and Hospital, Bengaluru, India.
Fulton Sebastian DsouzaSt John's Medical College and Hospital, Bengaluru, India.
Sushma Veeranna SajjanBangalore Medical College and Research Institute, Bengaluru, India.
Gangasamudra Veerappa BasavarajaIndira Gandhi Institute of Child Health, Bengaluru, India.
Mallesh KariyappaBangalore Medical College and Research Institute, Bengaluru, India.
Benedict Daniel MichaelInstitute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK.
Reeta S ManiNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Tom SolomonInstitute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK.
Vykuntaraju K GowdaIndira Gandhi Institute of Child Health, Bengaluru, India.
Vasanthapuram RaviNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Ravi YadavNational Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Lance TurtleInstitute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK.
Ruwanthi Kolamunnage-DonaInstitute of Population Health, University of Liverpool, Liverpool, UK.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Background: Scrub typhus and other doxycycline-treatable infections are significant contributors of acute encephalitis syndrome (AES) in India. Limited surveillance in South India has hindered their recognition and the inclusion of doxycycline in treatment protocols. We aimed to systematically investigate infectious aetiologies of AES in children from Karnataka, India, and develop clinical prediction models for diagnosing scrub typhus and guiding clinical decisions for doxycycline therapy. Methods: This multicentre, prospective study enrolled children aged >28 days to 18 years with AES presenting to three tertiary care hospitals in Bengaluru, India. Primary outcomes were microbiological diagnosis of AES and clinical prediction models for diagnosing scrub typhus and identifying patients with doxycycline-treatable causes. Models were developed using multivariable logistic regression, internally validated, and simplified into point-scoring systems. Model performance was evaluated using c-statistics, calibration slopes, and calibration-in-the-large, adhering to TRIPOD guidelines. Findings: Between February 2020 and February 2023, 714 children were screened, of whom 587 were included. Of these, 315 (54%) had a microbiological diagnosis. Scrub typhus accounted for 138/315 (44%), and doxycycline-treatable causes were diagnosed in 193/315 (61%) of these cases. Key predictors associated with both scrub typhus and doxycycline-treatable causes were age, illness duration, lymphadenopathy, oedema, hepatomegaly, lymphocyte count, platelet count, and serum albumin levels. Adjusted c-statistics were 0.83 (95% CI: 0.78-0.87) for the scrub typhus model and 0.75 (95% CI: 0.7-0.81) for the doxycycline model, with calibration slopes of 0.85 (0.82-0.88) and 0.83 (0.78-0.87), respectively. CITL values were -0.03 (-0.06-0) and 0.05 (0.02-0.09). Points-based scores predicted probabilities ranging from 5% to 99.8% (scrub typhus model) and 20%-99% (doxycycline-treatable model). Interpretation: Scrub typhus was the most common microbiological diagnosis, and most patients had a doxycycline-treatable cause, underscoring the need to prioritise doxycycline in empirical treatment protocols in South India. The models demonstrated strong performance; however external validation is necessary for broader applicability. Funding: DBT/Wellcome Trust India Alliance FellowshipIA/CPHE/18/1/503960.

Indexed as

Acute encephalitis syndrome (AES)Clinical prediction modelsDoxycycline-treatable infectionsPaediatric encephalitisPoint-scoring systemsScrub typhus

Identifiers

PMID40672782
PMCPMC12266524

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