Denys Prociuk, Jonathan Clarke, Nikki Smith, Ruairidh Milne, Cassie Lee, Simon de Lusignan, Ghazala Mir, Johannes De Kock, Erik Mayer, Brendan C. Delaney, LOCOMOTION Consortium
{"title":"了解长冠状病毒诊断患者的临床特征和诊断及时性：一项来自伦敦西北部的回顾性观察队列研究","authors":"Denys Prociuk, Jonathan Clarke, Nikki Smith, Ruairidh Milne, Cassie Lee, Simon de Lusignan, Ghazala Mir, Johannes De Kock, Erik Mayer, Brendan C. Delaney, LOCOMOTION Consortium","doi":"10.1111/hex.70429","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Long Covid is a multisystem condition first identified in the Covid-19 pandemic, characterised by a wide range of symptoms including fatigue, breathlessness and cognitive impairment. Considerable disagreement exists in who is most at risk of developing long Covid, driven in part by incomplete coding of a long Covid diagnosis in medical records.</p>\n </section>\n \n <section>\n \n <h3> Objective</h3>\n \n <p>To describe the incidence and impact of long Covid.</p>\n </section>\n \n <section>\n \n <h3> Design</h3>\n \n <p>A retrospective observational cohort study.</p>\n </section>\n \n <section>\n \n <h3> Setting and Participants</h3>\n \n <p>An integrated primary and secondary care dataset from North West London, covering over 2.7 million patients. Patients with long Covid were identified through clinical terms in their primary care records.</p>\n </section>\n \n <section>\n \n <h3> Main Variables Studied</h3>\n \n <p>Multivariate logistic regression was used to identify factors associated with having a long Covid diagnosis, while multivariate quantile regression was used to identify factors predicting the time a long Covid diagnosis was recorded.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>A total of 6078 patients were identified with a long Covid clinical term in their primary care record, 0.33% of the total registered adult population. Women, those aged 41–70 years or of Asian or mixed ethnicity, were more likely to have a recorded long Covid diagnosis, alongside those with pre-existing anxiety, asthma, depressive disorder or eczema and those living outside of the least or most socio-economically deprived areas. Men, those aged 41–70 years, or of black ethnicity, were diagnosed earlier in the pandemic, while those with depressive disorder were diagnosed later.</p>\n </section>\n \n <section>\n \n <h3> Discussion</h3>\n \n <p>Long Covid is poorly coded in primary care records, and significant differences exist between patient groups in the likelihood of receiving a long Covid diagnosis. A recorded long Covid diagnosis is more likely in women, some ethnic minority patients and those with pre-existing long-term conditions.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>The experience of patients with long Covid provides a crucial insight into inequities in access to timely care for complex multisystem conditions and the importance of effective health informatics practices to provide robust, timely analytical support for front line clinical services.</p>\n </section>\n \n <section>\n \n <h3> Patient and Public Contribution</h3>\n \n <p>This study was co-designed, conducted and written in conjunction with people with long Covid.</p>\n </section>\n </div>","PeriodicalId":55070,"journal":{"name":"Health Expectations","volume":"28 5","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/hex.70429","citationCount":"0","resultStr":"{\"title\":\"Understanding the Clinical Characteristics and Timeliness of Diagnosis for Patients Diagnosed With Long Covid: A Retrospective Observational Cohort Study From North West London\",\"authors\":\"Denys Prociuk, Jonathan Clarke, Nikki Smith, Ruairidh Milne, Cassie Lee, Simon de Lusignan, Ghazala Mir, Johannes De Kock, Erik Mayer, Brendan C. Delaney, LOCOMOTION Consortium\",\"doi\":\"10.1111/hex.70429\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Long Covid is a multisystem condition first identified in the Covid-19 pandemic, characterised by a wide range of symptoms including fatigue, breathlessness and cognitive impairment. Considerable disagreement exists in who is most at risk of developing long Covid, driven in part by incomplete coding of a long Covid diagnosis in medical records.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Objective</h3>\\n \\n <p>To describe the incidence and impact of long Covid.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Design</h3>\\n \\n <p>A retrospective observational cohort study.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Setting and Participants</h3>\\n \\n <p>An integrated primary and secondary care dataset from North West London, covering over 2.7 million patients. Patients with long Covid were identified through clinical terms in their primary care records.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Main Variables Studied</h3>\\n \\n <p>Multivariate logistic regression was used to identify factors associated with having a long Covid diagnosis, while multivariate quantile regression was used to identify factors predicting the time a long Covid diagnosis was recorded.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>A total of 6078 patients were identified with a long Covid clinical term in their primary care record, 0.33% of the total registered adult population. Women, those aged 41–70 years or of Asian or mixed ethnicity, were more likely to have a recorded long Covid diagnosis, alongside those with pre-existing anxiety, asthma, depressive disorder or eczema and those living outside of the least or most socio-economically deprived areas. Men, those aged 41–70 years, or of black ethnicity, were diagnosed earlier in the pandemic, while those with depressive disorder were diagnosed later.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Discussion</h3>\\n \\n <p>Long Covid is poorly coded in primary care records, and significant differences exist between patient groups in the likelihood of receiving a long Covid diagnosis. A recorded long Covid diagnosis is more likely in women, some ethnic minority patients and those with pre-existing long-term conditions.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>The experience of patients with long Covid provides a crucial insight into inequities in access to timely care for complex multisystem conditions and the importance of effective health informatics practices to provide robust, timely analytical support for front line clinical services.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Patient and Public Contribution</h3>\\n \\n <p>This study was co-designed, conducted and written in conjunction with people with long Covid.</p>\\n </section>\\n </div>\",\"PeriodicalId\":55070,\"journal\":{\"name\":\"Health Expectations\",\"volume\":\"28 5\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/hex.70429\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health Expectations\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/hex.70429\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Expectations","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/hex.70429","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Understanding the Clinical Characteristics and Timeliness of Diagnosis for Patients Diagnosed With Long Covid: A Retrospective Observational Cohort Study From North West London
Background
Long Covid is a multisystem condition first identified in the Covid-19 pandemic, characterised by a wide range of symptoms including fatigue, breathlessness and cognitive impairment. Considerable disagreement exists in who is most at risk of developing long Covid, driven in part by incomplete coding of a long Covid diagnosis in medical records.
Objective
To describe the incidence and impact of long Covid.
Design
A retrospective observational cohort study.
Setting and Participants
An integrated primary and secondary care dataset from North West London, covering over 2.7 million patients. Patients with long Covid were identified through clinical terms in their primary care records.
Main Variables Studied
Multivariate logistic regression was used to identify factors associated with having a long Covid diagnosis, while multivariate quantile regression was used to identify factors predicting the time a long Covid diagnosis was recorded.
Results
A total of 6078 patients were identified with a long Covid clinical term in their primary care record, 0.33% of the total registered adult population. Women, those aged 41–70 years or of Asian or mixed ethnicity, were more likely to have a recorded long Covid diagnosis, alongside those with pre-existing anxiety, asthma, depressive disorder or eczema and those living outside of the least or most socio-economically deprived areas. Men, those aged 41–70 years, or of black ethnicity, were diagnosed earlier in the pandemic, while those with depressive disorder were diagnosed later.
Discussion
Long Covid is poorly coded in primary care records, and significant differences exist between patient groups in the likelihood of receiving a long Covid diagnosis. A recorded long Covid diagnosis is more likely in women, some ethnic minority patients and those with pre-existing long-term conditions.
Conclusion
The experience of patients with long Covid provides a crucial insight into inequities in access to timely care for complex multisystem conditions and the importance of effective health informatics practices to provide robust, timely analytical support for front line clinical services.
Patient and Public Contribution
This study was co-designed, conducted and written in conjunction with people with long Covid.
期刊介绍：
Health Expectations promotes critical thinking and informed debate about all aspects of patient and public involvement and engagement (PPIE) in health and social care, health policy and health services research including:
• Person-centred care and quality improvement
• Patients'' participation in decisions about disease prevention and management
• Public perceptions of health services
• Citizen involvement in health care policy making and priority-setting
• Methods for monitoring and evaluating participation
• Empowerment and consumerism
• Patients'' role in safety and quality
• Patient and public role in health services research
• Co-production (researchers working with patients and the public) of research, health care and policy
Health Expectations is a quarterly, peer-reviewed journal publishing original research, review articles and critical commentaries. It includes papers which clarify concepts, develop theories, and critically analyse and evaluate specific policies and practices. The Journal provides an inter-disciplinary and international forum in which researchers (including PPIE researchers) from a range of backgrounds and expertise can present their work to other researchers, policy-makers, health care professionals, managers, patients and consumer advocates.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
