Evidence map›Paper›PMID 39261441›Full record

ArticleJournal of robotic surgery2024

Collaborative robot acting as scrub nurse for cataract surgery (CRASCS).

D Rekha, Harish Kumar Kaliyappan

Abstract read
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Article in Journal of robotic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
  4. 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

2 authors.

D RekhaCentre for Automation, Vellore Institute of Technology, Chennai, 600127, India. rekha.d@vit.ac.in.
Harish Kumar KaliyappanSchool of Computer Science and Engineering, Vellore Institute of Technology, Chennai, 600127, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Worldwide, healthcare systems are struggling to tackle a nursing shortage. As per the data released by the American Hospital Association, the healthcare workforce could face a loss of around 5 lakh nurses by the end of the year. Consequently, it could result in those deficiencies, which will be 1.1 million instead of 0.6 million. The current nursing scenario in India as per the Indian Nursing Council (INC), which is a board under the ministry and is responsible for legally confirming and maintaining universal standardized training for nursing, is that the 1.96 nurses out of every 1000 Indians that are there are much behind the World Health Organization's (WHO) recommended figure of 3 nurses per 1000. To mitigate the nurse shortage, a collaborative robotic system was designed that can assist with surgical procedures with a collaborative robot acting as a scrub nurse for cataract surgery (CRASCS) represented in Fig. 1. Accordingly, the model has been built to empower a customized 3d printed 5-Degree of freedom robotic arm by tracking the phase of surgery in real-time and automatically supplying the clinician with the ideal equipment that is needed for the particular phase of surgery. The system is supported with one more model which can identify where the surgical equipment is located within the arm range. The system is also supported with voice commands which help in picking up the right surgical equipment in the middle of any phase of the surgery. In this way, the system could be able to potentially handle the shortage of surgical nurses around the world and benefit humanity.

Indexed as

Cataract ExtractionRobotic Surgical ProceduresHumansIndiaPrinting, Three-Dimensional5-DOF robotic armCataract surgeryCollaborative robotic systemObject detection using YOLO modelsSurgical tool detection

Identifiers

What OpenQuestion holds

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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.