Evidence map›Paper›PMID 37821138›Full record

ArticleBMJ open2023

Epidemiology of tuberculosis in Kazakhstan: data from the Unified National Electronic Healthcare System 2014-2019.

Yesbolat Sakko, Meruyert Madikenova, Alexey Kim, Dmitriy Syssoyev, Kamilla Mussina, Arnur Gusmanov, Gulnur Zhakhina, Sauran Yerdessov, Yuliya Semenova, Byron Lawrence Crape and 2 more

Abstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Socioeconomic Interventions for WHO's End TB Strategy Targets: Insights from SIR Modelling in Kazakhstan.International journal of environmental research and public health · 2026
    Article
  5. Article
  6. Article
  7. Impact of Social Determinants of Health on the Incidence of Tuberculosis in Central Asia.International journal of environmental research and public health · 2026
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. 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

12 authors.

Yesbolat Sakko *Department of Medicine, Nazarbayev University, Astana, Kazakhstan.
Meruyert Madikenova *Department of Medicine, Nazarbayev University, Astana, Kazakhstan.ORCID 0000-0002-4833-4494
Alexey KimDepartment of Medicine, Nazarbayev University, Astana, Kazakhstan.
Dmitriy SyssoyevDepartment of Medicine, Nazarbayev University, Astana, Kazakhstan.
Kamilla MussinaDepartment of Medicine, Nazarbayev University, Astana, Kazakhstan.
Arnur GusmanovDepartment of Medicine, Nazarbayev University, Astana, Kazakhstan.
Gulnur ZhakhinaDepartment of Medicine, Nazarbayev University, Astana, Kazakhstan.
Sauran YerdessovDepartment of Medicine, Nazarbayev University, Astana, Kazakhstan.
Yuliya SemenovaDepartment of Medicine, Nazarbayev University, Astana, Kazakhstan.
Byron Lawrence CrapeDepartment of Medicine, Nazarbayev University, Astana, Kazakhstan.
Antonio Sarria-SantameraDepartment of Medicine, Nazarbayev University, Astana, Kazakhstan.ORCID 0000-0001-5734-7468
Abduzhappar GaipovDepartment of Medicine, Nazarbayev University, Astana, Kazakhstan abduzhappar.gaipov@nu.edu.kz.ORCID 0000-0002-9844-8772

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aims to estimate tuberculosis (TB) incidence, mortality rates and survival HRs in Kazakhstan, using large-scale administrative health data records during 2014-2019.

designA retrospective cohort study. SETTINGS: Data for patients with TB in Kazakhstan during 2014-2019, reported in the Unified National Electronic Healthcare System.

participantsPatients with TB in Kazakhstan (ICD-10 (The International Classification of Diseases, 10th revision) codes: A15-A19). OUTCOME MEASURES: Demographic factors, diagnoses and comorbidities were analysed using descriptive, bivariate and multivariable statistical analyses. TB incidence and mortality rates were calculated, and Cox regression and Kaplan-Meier survival analysis were performed to assess risk factors for survival rates.

resultsOf the 149 122 patients with TB, 91 437 (61%) were males, and 139 931 (94%) had respiratory TB. From 2014 to 2019, TB incidence declined from 227 to 15.2 per 100 000 individuals, while all-cause mortality increased from 8.4 to 15.2 per 100 000. Age-specific TB incidence was lowest for 0-10 years of age and highest for 20 years of age. Being older, man, urban residence versus rural, retired versus employed, having HIV and having diabetes versus no comorbidities were associated with lower survival rates.

conclusionTo date, this is the largest TB published study for Kazakhstan, characterising TB incidence and mortality trends by demographic factors, and risk factors for survival rates. The findings highlight the need for targeted interventions to address the growing burden of TB, particularly among older adults, men, urban residents and those with HIV and diabetes. The study underscores the importance of using administrative health data to inform policy and health system responses to TB in Kazakhstan.

Indexed as

Diabetes MellitusHIV InfectionsTuberculosisAgedChildChild, PreschoolFemaleHumansIncidenceInfantInfant, NewbornKazakhstanMaleRetrospective Studiesepidemiologic studiesepidemiologypublic healthtuberculosis

Identifiers

PMID37821138
PMCPMC10582847

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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.