Evidence map›Paper›PMID 37608250›Full record

ArticleBMC infectious diseases2023

Evaluation and optimization of the syndromic management of female genital tract infections in Nairobi, Kenya.

Gloria S Omosa-Manyonyi, Marloes de Kam, Alma Tostmann, Mwasi A Masido, Nyawira Nyagah, Moses M Obimbo, Andre J A M van der Ven, Jaap Ten Oever

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 24% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
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  6. Second trimester vaginalFrontiers in global women's health · 2024
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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

8 authors at 3 institutions in 2 countries.

Gloria S Omosa-Manyonyi *Faculty of Health Sciences, University of Nairobi, Nairobi, Kenya. gomosa@uonbi.ac.ke.ORCID https://orcid.org/0000-0002-4019-8977
Marloes de Kam *Department of Internal Medicine, Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, NL, Netherlands.
Alma TostmannDepartment of Medical Microbiology, Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, NL, Netherlands.
Mwasi A MasidoNairobi City County, Health Services, Nairobi, Kenya.
Nyawira NyagahNairobi City County, Health Services, Nairobi, Kenya.
Moses M ObimboFaculty of Health Sciences, University of Nairobi, Nairobi, Kenya.
Andre J A M van der VenDepartment of Internal Medicine, Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, NL, Netherlands.
Jaap Ten OeverDepartment of Internal Medicine, Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, NL, Netherlands.
Radboud University Nijmegen · NLKenya Forest Service · KEUniversity of Nairobi · KE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenital tract infections pose a public health concern. In many low-middle-income countries, symptom-based algorithms guide treatment decisions. Advantages notwithstanding, this strategy has important limitations. We aimed to determine the infections causing lower genital tract symptoms in women, evaluated the Kenyan syndromic treatment algorithm for vaginal discharge, and proposed an improved algorithm.

methodsThis cross-sectional study included symptomatic non-pregnant adult women presenting with lower genital tract symptoms at seven outpatient health facilities in Nairobi. Clinical, socio-demographic information and vaginal swabs microbiological tests were obtained. Multivariate logistic regression analyses were performed to find predictive factors for the genital infections and used to develop an alternative vaginal discharge treatment algorithm (using 60% of the dataset). The other 40% of data was used to assess the performance of each algorithm compared to laboratory diagnosis.

resultsOf 813 women, 66% had an infection (vulvovaginal candidiasis 40%, bacterial vaginosis 17%, Neisseria gonorrhoea 14%, multiple infections 23%); 56% of women reported ≥ 3 lower genital tract symptoms episodes in the preceding 12 months. Vulvovaginal itch predicted vulvovaginal candidiasis (odds ratio (OR) 2.20, 95% CI 1.40-3.46); foul-smelling vaginal discharge predicted bacterial vaginosis (OR 3.63, 95% CI 2.17-6.07), and sexually transmitted infection (Neisseria gonorrhoea, Trichomonas vaginalis, Chlamydia trachomatis, Mycoplasma genitalium) (OR 1.64, 95% CI 1.06-2.55). Additionally, lower abdominal pain (OR 1.73, 95% CI 1.07-2.79) predicted sexually transmitted infection. Inappropriate treatment was 117% and 75% by the current and alternative algorithms respectively. Treatment specificity for bacterial vaginosis/Trichomonas vaginalis was 27% and 82% by the current and alternative algorithms, respectively. Performance by other parameters was poor to moderate and comparable between the two algorithms.

conclusionSingle and multiple genital infections are common among women presenting with lower genital tract symptoms at outpatient clinics in Nairobi. The conventional vaginal discharge treatment algorithm performed poorly, while the alternative algorithm achieved only modest improvement. For optimal care of vaginal discharge syndrome, we recommend the inclusion of point-of-care diagnostics in the flowcharts.

Indexed as

Candidiasis, VulvovaginalCommunicable DiseasesGenital Diseases, FemaleGonorrheaReproductive Tract InfectionsVaginosis, BacterialAdultCross-Sectional StudiesFemaleHumansKenyaGenital tract infectionsKenyaLower genital tract symptomsPerformanceSyndromic treatmentVaginal dischargeVaginitis

Identifiers

PMID37608250
PMCPMC10463802
OpenAlexW4386050403

What OpenQuestion holds

Textmetadata
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.