Evidence map›Paper›PMID 39239189›Full record

ArticleIndian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine2024

Referral Audit of Critically Ill Obstetric Patients: A Five-year Review from a Tertiary Care Health Facility in India.

Sheeba Marwah, Jyotsna Suri, Taru Shikha, Poornima Sharma, Rekha Bharti, Mohit Mann, Geyum Ete, Nivedita Shankar, Bindu Bajaj

Abstract read
In one paragraph

Article in Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Does the Referral System for Emergency Obstetric Care in India Require a Major Overhaul?Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2024
    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

9 authors.

Sheeba MarwahDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.ORCID https://orcid.org/0000-0002-3223-9396
Jyotsna SuriDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.ORCID https://orcid.org/0000-0002-7838-3238
Taru ShikhaDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.ORCID https://orcid.org/0000-0002-2462-7823
Poornima SharmaDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.ORCID https://orcid.org/0000-0003-1290-8545
Rekha BhartiDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.ORCID https://orcid.org/0000-0001-9737-8365
Mohit MannDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.ORCID https://orcid.org/0009-0003-4684-1307
Geyum EteDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.ORCID https://orcid.org/0009-0000-3425-9123
Nivedita ShankarDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.ORCID https://orcid.org/0009-0007-6121-022X
Bindu BajajDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.ORCID https://orcid.org/0000-0002-7201-2858

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In resource-limited facilities, the greatest number of unfavorable maternal-fetal outcomes at referral hospitals is chronicled from emergency obstetric referrals of critically ill patients from lower health facilities. An efficient obstetric referral system is thus necessitated for improving maternal health. Referral practices have not been optimized effectively till date, owing to paucity of a detailed profile of referred women and indigenous barriers encountered during implementation process. Materials and methods: This five-year retrospective audit was conducted in the Department of Obstetrics and Gynecology, VMMC and Safdarjung Hospital, New Delhi from September 2018 to 2023, in which records of all critically ill obstetric women referred were reviewed. The primary outcomes included were proportion and pattern of patients being referred, while secondary outcomes included demographic variables, referring hospital, reason and number of steps in referral, duration of hospital stay and fetomaternal outcome. The data were recorded on a predesigned case proforma and analyzed using the SPSSv23 version of software, after application of appropriate statistical tests. Results: The referral rate to obstetric intensive care unit (ICU) ranged from 39 to 47% in last 5 years; hypertensive disorder of pregnancy (31%) being the foremost cause of the referrals. Around 2/3rd women were transferred without escort (70%) or prior communication (90.6%) and referral slips were incomplete in half the admissions. Conclusion: Ensuring emergency obstetric care (EmOC) at various levels by up-gradation of health infrastructure would go a long way in improving fetomaternal health outcomes. There is need of standardized referral slips tailor-made to each state and contextualized protocols for early recognition of complications and effective communication between referral centers. How to cite this article: Marwah S, Suri J, Shikha T, Sharma P, Bharti R, Mann M,

Indexed as

Critically ill obstetric womenFetomaternal outcomesObstetric ICU referral audit

Identifiers

PMID39239189
PMCPMC11372672

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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.