Evidence map›Paper›PMID 42889261›Full record

ArticleCureus2026

Sociodemographic and Clinical Profile of Homeless Patients Attending the Emergency Department of a Tertiary Care Centre in Rishikesh, Uttarakhand, India: A Prospective Observational Study.

Rinku Meena, Bharat Bhardwaj, Vempalli Nagasubramanyam, Anand M Gangdev, Devinder Kumar Lalotra, Jitendra Yadav

Abstract read
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Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Rinku MeenaEmergency Medicine, National Institute of Medical Sciences (NIMS) University, Jaipur, IND.
Bharat BhardwajEmergency Medicine, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Vempalli NagasubramanyamEmergency Medicine, All India Institute of Medical Sciences, Mangalagiri, Mangalagiri, IND.
Anand M GangdevEmergency Medicine, National Institute of Medical Sciences (NIMS) University, Jaipur, IND.
Devinder Kumar LalotraEmergency Medicine, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Jitendra YadavEmergency Medicine, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Homeless individuals are a highly vulnerable population with complex medical and social needs. Emergency departments (EDs) often serve as the primary point of contact for healthcare for homeless persons in India, yet systematic data on their profile and outcomes from tertiary care settings remain limited. Methodology A prospective observational study was conducted in the emergency medicine department of a tertiary care centre in North India from July 2022 to December 2023 (18-month duration). All homeless patients aged over 18 years presenting to the emergency department and meeting inclusion criteria were enrolled. Sociodemographic data, clinical presentation, investigations, consultations and ED outcomes were recorded using a structured pro forma, and data were analysed using SPSS v23.0 (IBM Corp., Armonk, NY). Results Forty-eight homeless patients were enrolled in the study. The majority were men (93.8%), adults aged 31-60 years (52.1%) and from Uttarakhand (85.4%). Most patients (75%) were staying alone, and 81.2% were uninsured. The most common mode of arrival was ambulance (85.4%), with 66.7% referred from another healthcare facility. The most common presenting complaints were abdominal symptoms (22.9%), dyspnoea (18.8%) and trauma (16.7%). Chronic obstructive pulmonary disease (COPD) was the most common diagnosis (12.5%), followed by head injury (10.4%) and decompensated chronic liver disease (8.3%). Two-thirds of the patients (66.7%) were triaged to the red area. ED in-hospital mortality was 18.8%. The median ED length of stay was two days. Fourteen patients had ED revisits during the study period. Conclusions Homeless patients presenting to the ED are predominantly men and uninsured and arrive in critical condition via ambulance. They carry a high burden of chronic disease, present late in the course of illness and have substantially high in-ED mortality. Integrated care models, policy-level expansion of health coverage and dedicated ED protocols for homeless individuals are urgently needed in India.

Indexed as

clinical profileed outcomesemergency departmenthomelessnessindiasociodemographic profiletriagevulnerable population

Identifiers

PMID42889261
PMCPMC13669557

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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.