Evidence map›Paper›PMID 37532458›Full record

ArticleBMJ open quality2023

Improving outpatient clinic experience: the future of chronic kidney disease care and associated multimorbidity.

Saif Al-Chalabi, Helen Alderson, Natalie Garratt, Darren Green, Philip A Kalra, James Ritchie, Schanhave Santhirasekaran, Dimitrios Poulikakos, Smeeta Sinha

Open access · goldAbstract read
In one paragraph

Article in BMJ open quality, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 25% of its field
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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Cardiovascular-Kidney-Metabolic Syndrome: Models of Care.Reviews in cardiovascular medicine · 2026
    Review
  2. Review
  3. 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 at 2 institutions in 1 country.

Saif Al-ChalabiDepartment of Renal Medicine, Northern Care Alliance NHS Foundation Trust, Salford, UK saif.alchalabi@nca.nhs.uk.ORCID 0000-0003-1669-8514
Helen AldersonDepartment of Renal Medicine, Northern Care Alliance NHS Foundation Trust, Salford, UK.
Natalie GarrattResearch & Innovation, Northern Care Alliance NHS Foundation Trust, Salford, UK.
Darren GreenDepartment of Renal Medicine, Northern Care Alliance NHS Foundation Trust, Salford, UK.
Philip A KalraDepartment of Renal Medicine, Northern Care Alliance NHS Foundation Trust, Salford, UK.
James RitchieDepartment of Renal Medicine, Northern Care Alliance NHS Foundation Trust, Salford, UK.
Schanhave SanthirasekaranDepartment of Renal Medicine, Northern Care Alliance NHS Foundation Trust, Salford, UK.
Dimitrios PoulikakosDepartment of Renal Medicine, Northern Care Alliance NHS Foundation Trust, Salford, UK.
Smeeta SinhaDepartment of Renal Medicine, Northern Care Alliance NHS Foundation Trust, Salford, UK.
University of Manchester · GBNorthern Health and Social Care Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic kidney disease (CKD) is estimated to affect more than 2.5 million adults in England, and this is expected to rise to 4.2 million by 2036 (1). Population-level digital healthcare systems have the potential to enable earlier detection of CKD providing an opportunity to introduce interventions that attenuate progression and reduce the risk of end-stage kidney disease (ESKD) and cardiovascular diseases (CVD). Services that can support patients with CKD, CVD, and diabetes mellitus (DM) have the potential to reduce fragmented clinical care and optimise pharmaceutical management. METHODS AND

resultsThe Salford renal service has established an outpatient improvement programme which aims to address these issues via two projects. Firstly, the development of a CKD dashboard that can stratify patients by their kidney failure risk equation (KFRE) risk. High-risk patients would be invited to attend an outpatient clinic if appropriate. Specialist advice and guidance would be offered to primary care providers looking after patients with medium risk. Patients with lower risk would continue with standard care via their primary care provider unless there was another indication for a nephrology referral. The CKD dashboard identified 11546 patients (4.4% of the total adult population in Salford) with T2DM and CKD. The second project is the establishment of the Metabolic CardioRenal (MRC) clinic. It provided care for 209 patients in the first 8 months of its establishment with a total of 450 patient visits. Initial analysis showed clustering of cardiorenal metabolic diseases with 85% having CKD stages 3 and 4 and 73.2% having DM. In addition, patients had a significant burden of CVD with 50.2% having hypertension and 47.8% having heart failure.

conclusionThere is a pressing need to create new outpatient models of care to tackle the rising epidemic of cardio-renal metabolic diseases. This model of service has potential benefits at both organisational and patient levels including improving patient management via risk stratification, increased care capacity and reduction of variation of care. Patients will benefit from earlier intervention, appropriate referral for care, reduction in CKD-related complications, and reduction in hospital visits and cardiovascular events. In addition, this combined digital and patient-facing model of care will allow rapid translation of advances in cardio-renal metabolic diseases into clinical practice.

Indexed as

Cardiovascular DiseasesRenal Insufficiency, ChronicAdultAmbulatory Care FacilitiesEnglandHumansMultimorbidityChronic disease managementDiabetes mellitusElectronic Health RecordsMultiple Chronic ConditionsOutpatients

Identifiers

PMID37532458
PMCPMC10401237
OpenAlexW4385481158

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.