Evidence map›Paper›PMID 33661501›Full record

ArticleEnvironmental science and pollution research international2021

A cohort study analyzing the impact of socioeconomic and spatial characteristics alongside treatment regimens on the environmental-health outcomes of the MDR-TB treatment in Pakistan.

Ankasha Arif, Eatzaz Ahmad, Farzana Naheed Khan, Razia Fatima

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2021. 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

4 authors.

Ankasha ArifSchool of Economics, Quaid-i-Azam University, Islamabad, Pakistan. ankashaarif@gmail.com.ORCID https://orcid.org/0000-0002-4557-4644
Eatzaz AhmadSchool of Economics, Quaid-i-Azam University, Islamabad, Pakistan.
Farzana Naheed KhanSchool of Economics, Quaid-i-Azam University, Islamabad, Pakistan.
Razia FatimaNational Tuberculosis Control Program, Ministry of Health, Pakistan, EPI building, F block, PM Health Complex, Chak Shahzad, Islamabad, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study identifies and analyzes a number of factors that correlate with the environmental-health outcome of multi-drug resistance tuberculosis (MDR-TB) treatment in Pakistan. Survival analysis is carried out by applying the multivariable Cox Proportional Hazard model on secondary data of 369 patients registered at three main MDR-TB sites in Pakistan during 2012-2017. Results show that there is no difference in survival of patients between the two treatment arms, hospital and ambulatory care. Male gender and travel expenditure are found to be negatively associated with the environmental-health outcome, whereas spatial characteristic of time expenditure is positively related to it supporting distance bias approach. Medical expenditure is also positively related to the environmental-health outcome. The study concludes that availability of affordable and accessible health services, better environmental conditions, and ambulatory care based on WHO recommendation as well as health education along with social protection schemes should be ensured by the government to improve environmental-health outcome in the resource-scarce setting in Pakistan.

Indexed as

Antitubercular AgentsTuberculosis, Multidrug-ResistantCohort StudiesHumansMaleOutcome Assessment, Health CarePakistanSocioeconomic FactorsAntitubercular AgentsEnvironmental-health outcomeMDR-TBPolicySocio-economicSpatialSurvival analysis

Identifiers

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Registered trials

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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.