---
title: "Characteristics, Comorbidities, Medications, and Resource Use in Patients Newly Diagnosed with Alz"
id: "bmj-open-5-characterising-patients-with-alzheimers-disease-in-england-a-cohort-study-using"
canonical_url: "https://medichelpline.com/clinical-feed/bmj-open-5-characterising-patients-with-alzheimers-disease-in-england-a-cohort-study-using"
content_type: "clinical_feed_article"
specialty: "Neurology"
source_name: "BMJ Open"
source_url: "http://bmjopen.bmj.com/cgi/content/short/16/8/e115438?rss=1"
published_at: "2026-08-28T09:38:04.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Characteristics, Comorbidities, Medications, and Resource Use in Patients Newly Diagnosed with Alz
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/bmj-open-5-characterising-patients-with-alzheimers-disease-in-england-a-cohort-study-using
- **Specialty:** [Neurology](https://medichelpline.com/clinical-feed/neurology.md)
- **Primary Source:** BMJ Open
- **Source URL:** [Original Journal Publication](http://bmjopen.bmj.com/cgi/content/short/16/8/e115438?rss=1)
- **Published At:** 2026-08-28T09:38:04.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- This observational cohort study used linked UK primary and secondary care records (CPRD Aurum linked to HES) to characterise patients newly diagnosed with **Alzheimer's disease** (AD) in England during 2019. - Three published, validated algorithms were applied to identify AD cases: two disease-based algorithms (Imfeld et al; Douros et al) and one medication-based algorithm (Schroeder et al). - Patients were grouped into three non-mutually exclusive cohorts (A–C) reflecting those algorithms; patients aged ≥60 years were analysed as three subcohorts (subcohorts 1–3). Subcohort sizes were 9,826; 10,265; and 7,355 respectively. - Mean age at index across the three subcohorts ranged from 81 to 83 years. The majority were female (59%–63%) and White (93%). - Frequent comorbidities included **hypertension** (67%–71%), **asthma and chronic obstructive pulmonary disease** (60%–63%), and **arthritis and osteoarthritis** (51%–53%). - High prevalence of co-medications was observed: **analgesics** (87%–89%), systemic corticosteroids (83%–84%), and anti-inflammatory/anti-rheumatic agents (81%–82%). - Up to 34% of patients had a specialist referral or visit; up to 18% involved a neurologist. - In the 12 months up to and including index, up to 46% had an emergency department or inpatient visit for any cause. - Findings were broadly consistent across disease- and medication-based algorithms, supporting internal validity and robustness to case definition method. - The study quantifies England-specific burden of comorbidity, polypharmacy, and **healthcare resource utilisation**, offering insights to help clinicians identify needs and tailor care for patients with AD.
## Clinical Analysis & Structured Key Points
Objectives To characterise demographics, comorbidities, co-medications and healthcare resource utilisation (HCRU) in patients newly diagnosed with Alzheimer's disease (AD) in England using published and validated AD algorithms. Design Observational cohort study. Setting Real-world data in England from the Clinical Practice Research Datalink Aurum primary care database linked to the Hospital Episode Statistics secondary care database. Participants Two disease-based algorithms (Imfeld et al and Douros et al ) and one medication-based algorithm (Schroeder et al ) were selected from the literature to identify patients with AD. The index period for patient selection was from 1 January to 31 December 2019. Patients were grouped into three non-mutually exclusive cohorts reflecting these algorithms (cohorts A - C), then patients aged &ge;60 years were further grouped into three subcohorts (subcohorts 1 - 3). Subcohort 1 included 9826 patients, subcohort 2 included 10 265 patients and subcohort 3 included 7355 patients. Primary outcome measures Demographics, comorbidities, co-medications and HCRU present up to and including the date of cohort qualification were described. Results Across subcohorts 1 - 3, mean age at index ranged from 81 to 83 years, and most patients were female (59% - 63%) and White (93%). Common comorbidities were hypertension (67% - 71%), asthma and chronic obstructive pulmonary disease (60% - 63%) and arthritis and osteoarthritis (51% - 53%). Common co-medications were analgesics (87% - 89%), systemic corticosteroids (83% - 84%) and anti-inflammatory and anti-rheumatic agents (81% - 82%). Up to 34% of patients had a specialist referral or visit, with up to 18% involving a neurologist. In the 12 months prior to and including the index date, up to 46% of patients had an emergency department visit or inpatient visit for any cause. Conclusions In England, most newly diagnosed patients with AD were White females in their early 80s with common comorbidities including hypertension, asthma, chronic obstructive pulmonary disease, arthritis and osteoarthritis. This study addresses a critical evidence gap by quantifying the England-specific burden of comorbidity, polypharmacy, and HCRU among patients with AD using multiple validated and published AD algorithms. Findings were broadly consistent across the three subcohorts identified using disease-based and medication-based algorithms, strengthening internal validity of the study and demonstrating that the findings are robust to the method of AD case definition. This study provides a novel insight into the real-world AD population in England, and findings may help healthcare professionals to identify patients living with AD, understand patients' needs and tailor treatment strategies.
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