Evidence map›Paper›PMID 39040742›Full record

ReviewCureus2024

Green Dialysis From the Indian Perspective: A Systematic Review.

Surendra S Rathore, Kumari Nirja, Sunita Choudhary, Garima Jeswani

Abstract readReview
In one paragraph

Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Surendra S RathoreNephrology, Dr SN Medical College, Jodhpur, IND.
Kumari NirjaPhysiology, Dr SN Medical College, Jodhpur, IND.
Sunita ChoudharyPhysiology, Dr SN Medical College, Jodhpur, IND.
Garima JeswaniPhysiology, Dr SN Medical College, Jodhpur, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Global warming and climate change represent the most significant threats to humanity in the 21st century, both of which are manmade catastrophes. Addressing climate change requires corrective action across all aspects of modern human life and work, including the medical field. Among healthcare sectors, dialysis units stand out as major contributors to plastic waste and excessive water consumption. It is imperative for hemodialysis units to lead by example in the judicious use of natural resources. This systemic review is aimed to establish a bare minimum of recommendations for environmental sustainability across Indian dialysis units, and to guide future initiatives to reduce the environmental impact of dialysis process. A literature search was conducted on PubMed, and Google to retrieve articles or studies related to green dialysis. The predefined keyword search yielded a total of 291 studies. A total of 54 studies and articles which were relevant to study question, and fulfilled inclusion criteria, were retrieved and analyzed to form opinions on the implementation of green dialysis initiatives from an Indian perspective. Green dialysis initiatives are much-needed reforms to be adopted by the Indian dialysis community. Through careful planning and minimal efforts, substantial amounts of water used in hemodialysis can be conserved and repurposed for other hospital activities. Similarly, the vast majority of discarded plastic waste can be recycled or reused. Despite controversy, reconsidering the risk-benefit aspects of dialyzer reuse is essential, particularly in the context of resource-limited developing nations like India.

Indexed as

climate changedialyzer reuseeco-dialysisglobal warminggreen dialysishemodialysis

Identifiers

PMID39040742
PMCPMC11261166

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.