Evidence map›Paper›PMID 39013380›Full record

Observational studyThe American journal of tropical medicine and hygiene2024

Demographic and Clinical Factors Associated with Bacterial or Nonbacterial Etiologies of Acute Undifferentiated Febrile Illness: Findings from a 3-Year Observational Study in Thailand, 2017-2020.

Natalie R Wodniak, Saithip Bhengsri, Beth Skaggs, Sumonmal Uttayamakul, Pongpun Sawatwong, Ornuma Sangwichian, Christopher J Gregory, Nuttagarn Chuenchom, Pongpot Peanumlom, Supphachoke Khemla and 8 more

Abstract readObservational Study
In one paragraph

Observational study in The American journal of tropical medicine and hygiene, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

18 authors.

Natalie R WodniakDivision of Global Health Protection, Thailand MOPH-US CDC Collaboration, Nonthaburi, Thailand.
Saithip BhengsriDivision of Global Health Protection, Thailand MOPH-US CDC Collaboration, Nonthaburi, Thailand.
Beth SkaggsDivision of Global Health Protection, Thailand MOPH-US CDC Collaboration, Nonthaburi, Thailand.
Sumonmal UttayamakulBamrasnaradura Infectious Diseases Institute, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand.
Pongpun SawatwongDivision of Global Health Protection, Thailand MOPH-US CDC Collaboration, Nonthaburi, Thailand.
Ornuma SangwichianDivision of Global Health Protection, Thailand MOPH-US CDC Collaboration, Nonthaburi, Thailand.
Christopher J GregoryDivision of Global Health Protection, Thailand MOPH-US CDC Collaboration, Nonthaburi, Thailand.
Nuttagarn ChuenchomMae Sot General Hospital, Tak, Thailand.
Pongpot PeanumlomMae Sot General Hospital, Tak, Thailand.
Supphachoke KhemlaNakhon Phanom Hospital, Nakhon Phanom, Thailand.
Tanaphat LertwitayakumjornNakhon Phanom Hospital, Nakhon Phanom, Thailand.
Samkan ChaoprasertTak Provincial Health Office, Tak, Thailand.
Barameht PiralamNakhon Phanom Provincial Health Office, Nakhon Phanom, Thailand.
Tuwan SimmaliNakhon Phanom Provincial Health Office, Nakhon Phanom, Thailand.
Chuwattana CharaNakhon Phanom Hospital, Nakhon Phanom, Thailand.
Emily BlossDivision of Global Health Protection, Thailand MOPH-US CDC Collaboration, Nonthaburi, Thailand.
John R MacArthurDivision of Global Health Protection, Thailand MOPH-US CDC Collaboration, Nonthaburi, Thailand.
James D HeffelfingerDivision of Global Health Protection, Thailand MOPH-US CDC Collaboration, Nonthaburi, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute undifferentiated febrile illness (AUFI) is often undiagnosed in Thailand, resulting in delayed or ineffective treatment. We compared the demographic, exposure history, and clinical characteristics of AUFI patients with laboratory evidence of bacterial and nonbacterial pathogens. Patients aged 2-80 years presenting to 12 hospitals in Nakhon Phanom and Tak provinces were enrolled from April 2017 through May 2020. Interviews were conducted and blood, urine, and sputum were collected for culture as well as rapid diagnostic and molecular testing. A total of 1,263 patients tested positive for one or more bacterial, viral, or parasitic pathogens and were included in the analysis. Multivariable logistic regression was performed to compare factors associated with bacterial infections versus nonbacterial infections. Bacterial infections were more commonly identified in participants from Nakhon Phanom than Tak. Bacterial infections were independently associated with several factors including age ≥50 years (adjusted odds ratio [95% CI]): (4.18 [2.85-6.14]), contact with farm animals (1.82 [1.29-2.57]), antibiotic use within 72 hours of hospital presentation (2.37 [1.50-3.74]), jaundice (2.31 [1.15-4.63]), existing comorbidities (2.77 [1.93-3.96]), contact with febrile individuals (0.42 [0.31-0.57]), muscle pain (0.44 [0.31-0.64]), and rash (0.45 [0.29-0.70]). Bacterial infections were also associated with longer hospitalization (2.75 [2.08-3.64]) and lower odds of recovery at the time of discharge (0.14 [0.07-0.31]). Consideration of patient characteristics and signs/symptoms may help to inform targeted laboratory testing for suspected infectious etiologies. Understanding factors associated with bacterial and non-bacterial causes of AUFI may aid diagnosis and judicious use of antibiotics in resource-limited settings.

Indexed as

Bacterial InfectionsFeverAcute DiseaseAdolescentAdultAgedAged, 80 and overChildChild, PreschoolFemaleHumansMaleMiddle AgedRisk FactorsThailandYoung Adult

Identifiers

PMID39013380
PMCPMC11376184

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.