Evidence map›Paper›PMID 35034379›Full record

ArticleThe International journal of health planning and management2022

Health services for non-communicable diseases have been severely disrupted by COVID-19 based on an analysis of MicroBlog rescue data in Wuhan, China.

Xiaoyan Zhang, Fenghua Sun, Qianyan Wang

Abstract read
In one paragraph

Article in The International journal of health planning and management, 2022. 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. The need for voices from the grassroots in China's public health system.The Lancet regional health. Western Pacific · 2023
    Article
  2. 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

3 authors.

Xiaoyan ZhangSchool of Public Administration, Hubei University, Wuhan, China.ORCID https://orcid.org/0000-0002-1815-5188
Fenghua SunSchool of Public Administration, Hubei University, Wuhan, China.ORCID https://orcid.org/0000-0001-7618-991X
Qianyan WangLiYuan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.

Funding

Natural Science Foundation of China 71704048
6 · The paper itself

Abstract

Diagnostic and treatment services for non-communicable diseases (NCDs) face significant challenges in the context of the COVID-19 pandemic. We used the Python programing language to extract and classify messages for help posted on the social networking platform microblog by NCD patients in the early stage of the COVID-19 epidemic in Wuhan, China. We found of all NCD patients, the most frequently recorded conditions were basic chronic diseases (42.50%), acute critical diseases (35.53%), malignant tumours (15.10%), and patients requiring haemodialysis (6.79%). Regarding COVID-19, 54.70% of patients reported suspected symptoms of infection, 32.01% were diagnosed with comorbidities, and 13.29% were non-COVID-19 patients. According to the analysis of the needs of the patients, 82.46% of the patients reported "No beds were available in the hospital", 25.31% of patients needed nucleic acid tests. Our results confirmed it is difficult to meet the regular needs in the diagnosis and treatment of patients with NCDs. Effective prevention and management of NCDs in public health emergencies has become an urgent issue to be addressed. During the COVID-19 epidemic, it is necessary to pay particular attention to the prevention and control of NCD patients, especially those with chronic disease. Governments and medical and health institutions at all levels should improve treatment mechanisms during major epidemics and ensure the uninterrupted treatment of patients with NCDs.

Indexed as

COVID-19Noncommunicable DiseasesChinaChronic DiseaseHealth ServicesHumansPandemicsSARS-CoV-2chronic diseaseCOVID-19diagnosis and treatment needspatients with non-communicable diseases

Identifiers

PMID35034379
PMCPMC9015239

What OpenQuestion holds

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Registered trials

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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.