Evidence map›Paper›PMID 34226902›Full record

ArticleEJHaem2021

Models of care for chronic myeloid leukemia patients during the COVID-19 pandemic in the United Kingdom: Changes in patient attitudes to remote consultations and future implications.

Nicholas Duncan, Nigel Deekes, David FitzGerald, Tin Wai Terry Ng, Manoj Raghavan

Abstract read
In one paragraph

Article in EJHaem, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. 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

5 authors.

Nicholas DuncanQueen Elizabeth Hospital and University of Birmingham Birmingham UK.ORCID https://orcid.org/0000-0002-1191-8170
Nigel DeekesPatient representative.
David FitzGeraldPatient representative.
Tin Wai Terry NgSchool of Pharmacy University College London London UK.
Manoj RaghavanQueen Elizabeth Hospital and University of Birmingham Birmingham UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing COVID-19 pandemic has presented numerous challenges to the provision of patient care within hematology. We undertook a questionnaire-based study investigating the experiences and opinions of patients with chronic myeloid leukemia (CML) in the UK in relation to the different models of follow-up care received during the pandemic. One hundred fifty-four patients completed the online questionnaire. Only 19% of patients had experienced remote clinics prior to the pandemic compared with 91% afterward. After having experience of remote clinics, the proportion of patients who were positive about the remote clinic concept increased from 34% to 52% (P < .05). However, when asked to compare their experiences with face to face versus remote clinics, 48% preferred face-to-face clinics compared with 17% preferring remote clinics (35% expressed no preference). During the pandemic, frequency of blood tests was unchanged for 71% of patients, although they were performed in a number of different locations. The majority of patients (57%) had medication delivered to their home, with a small number (8%) having difficulty obtaining their medication. In terms of future models of care, 72% of patients were in favor of building remote appointments into the clinic model with 61% expressing a preference for a mixture of remote and face-to-face appointments. There was also interest in greater utilization of primary care for blood testing. Our findings should help optimize future models of care for CML patients.

Identifiers

PMID34226902
PMCPMC8242739

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.