scholarly journals Predicting risk of hospital admission in patients with suspected COVID-19 in a community setting : protocol for development and validation of a multivariate risk prediction tool (RECAP) (Preprint)

2021 ◽  
Author(s):  
Ana B Espinosa-Gonzalez ◽  
Ana Luisa Neves ◽  
Francesca Fiorentino ◽  
Denys Prociuk ◽  
Laiba Husain ◽  
...  
Keyword(s):  
Primary Care ◽  
Risk Prediction ◽  
Patient Outcomes ◽  
Model Development ◽  
Community Setting ◽  
Signs And Symptoms ◽  
Multivariate Risk ◽  
Primary Care Clinicians ◽  
Development And Validation ◽  
Remote Consultations

BACKGROUND During the pandemic, remote consultations have become the norm for the assessment of patients with signs and symptoms of COVID-19 in order to decrease the risk of transmission. This has added to the already existing challenges experienced by primary care clinicians when assessing suspected COVID-19 patients due to the uncertainty around disease progression (e.g., risk of deterioration around the 8th day of disease) and has prompted the use of risk prediction scores, such as NEWS2, to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and have not been designed to capture the idiosyncrasy of COVID-19 infection. OBJECTIVE The objective of this study is to produce a multivariate risk prediction tool (RECAP–V1) to support primary care clinicians in the identification of those COVID-19 patients that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes. METHODS The study follows a prospective cohort observational design, whereby patients presenting in primary or community care with signs and symptoms suggestive of COVID-19 will be followed and their data linked with hospital outcomes (hospital admission, intensive care unit admission and death). The collection of the primary data for the model will be carried out by primary care clinicians in four arms, i.e., North West London Clinical Commissioning Groups (NWL CCG), Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC), Covid Clinical Assessment Service (CCAS) and South East London CCGs (Doctaly platform), and will involve the use of an electronic template that incorporates a list of items (known as RECAP-V0) thought to be associated with worse disease outcome according to previous qualitative work.. This data will be linked to patient outcomes in highly secure environments (iCARE and ORCHID secure environments). We will then use multivariate logistic regression analyses for model development and validation. RESULTS Recruitment of participants started in October 2021. Initially, only NWL CCGs and RCGP RSC arms were active. As of 24th of March 2021, we have recruited a combined sample of 3,827 participants in these two arms. CCAS and Doctaly joined the study in February 2021, with CCAS starting recruitment process on the 15th of March 2021. The first part of the analysis (RECAP-V1 model development) is planned to start in April 2021 using the first half of the NWL CCG and RCGP RSC combined datasets. Posteriorly, the model will be validated with the rest of NWL CCG and RCGP RSC data as well as CCAS and Doctaly datasets. The study was approved by the Research Ethics Committee on the 27th of May 2020 (IRAS number 283024, REC reference number: 20/NW/0266) and badged as NIHR Urgent Public Health Study on 14th of October 2020. CONCLUSIONS We believe the validated RECAP-V1 early warning score will be a valuable tool for the assessment of suspected COVID-19 patients’ severity in the community, either in face-to-face or remote consultations, and will facilitate the timely escalation of treatment with the potential to improve patient outcomes. CLINICALTRIAL ISRCTN registry (ISRCTN13953727)

scholarly journals Remote Covid Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies.

2021 ◽  
Author(s):  
Ana B Espinosa-Gonzalez ◽  
Denys Prociuk ◽  
Francesca Fiorentino ◽  
Christian Ramtale ◽  
Ella Mi ◽  
...  
Keyword(s):  
Primary Care ◽  
Risk Prediction ◽  
Model Development ◽  
Area Under The Curve ◽  
Community Setting ◽  
Signs And Symptoms ◽  
Low Risk ◽  
Peripheral Oxygen Saturation ◽  
Care Practices ◽  
Primary Care Practices

Background Accurate assessment of COVID-19 severity in the community is essential for best patient care and efficient use of services and requires a risk prediction score that is COVID-19 specific and adequately validated in a community setting. Following a qualitative phase to identify signs, symptoms and risk factors, we sought to develop and validate two COVID-19-specific risk prediction scores RECAP-GP (without peripheral oxygen saturation (SpO2)) and RECAP-O2 (with SpO2). Methods Prospective cohort study using multivariable logistic regression for model development. Data on signs and symptoms (model predictors) were collected on community-based patients with suspected COVID-19 via primary care electronic health records systems and linked with secondary data on hospital admission (primary outcome) within 28 days of symptom onset. Data sources: RECAP-GP: Oxford-Royal College of General Practitioners Research and Surveillance Centre (RSC) primary care practices (development), Northwest London (NWL) primary care practices, NHS COVID-19 Clinical Assessment Service (CCAS) (validation). RECAP-O2: Doctaly Assist platform (development, and validation in subsequent sample). Estimated sample size was 2,880 per model. Findings Data were available from 8,311 individuals. Observations, such SpO2, were mostly missing in NWL, RSC, and CCAS data; however, SpO2 was available for around 70% of Doctaly patients. In the final predictive models, RECAP-GP included sex, age, degree of breathlessness, temperature symptoms, and presence of hypertension (Area Under the Curve (AUC): 0.802, Validation Negative Predictive Value (NPV) of low risk 98.8%. RECAP-O2 included age, degree of breathlessness, fatigue, and SpO2 at rest (AUC: 0.843), Validation NPV of low risk 99.4%. Interpretation Both RECAP models are a valid tool in the assessment of COVID-19 patients in the community. RECAP-GP can be used initially, without need for observations, to identify patients who require monitoring. If the patient is monitored at home and SpO2 is available, RECAP-O2 is useful to assess the need for further treatment escalation.

scholarly journals Rare presentation of the great imitator: a rare case report

2017 ◽  
Vol 3 (3) ◽  
pp. 453
Author(s):  
Ravindranath Brahmadeo Chavan ◽  
Vasudha Abhijit Belgaumkar ◽  
Aarti Sudam Salunke ◽  
Sharada Shivaji Chirame
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Rare Case ◽  
Signs And Symptoms ◽  
Rare Presentation ◽  
The Past ◽  
Modern Health Care ◽  
Rare Case Report ◽  
Life Threatening ◽  
Primary Care Clinicians

<span>Syphilis is often thought to be a disease of the past, largely eradicated in modern health care; however, the rates are still extremely high in certain populations. The diagnosis of syphilis may be overlooked by primary-care clinicians due to the presence of nonspecific signs and symptoms that may be indistinguishable from other diseases. Left undiagnosed and untreated, life-threatening complications, including hepatitis, stroke, and nervous system damage, may occur particularly in immuno-compromised individuals. We present a case of lues maligna an extremely rare presentation of syphilis.</span>

Ulcerative colitis

2019 ◽  
Vol 12 (9) ◽  
pp. 501-506
Author(s):  
Charlie Andrews
Keyword(s):  
Quality Of Life ◽  
Ulcerative Colitis ◽  
Primary Care ◽  
Patient Outcomes ◽  
Colon And Rectum ◽  
Inflammatory Bowel ◽  
Primary Care Clinicians ◽  
Improve Patient ◽  
Prompt Diagnosis

Ulcerative colitis is a form of inflammatory bowel disease. It is a chronic relapsing condition affecting the colon and rectum and can cause a variety of symptoms, the commonest of which is bloody diarrhoea. Prompt diagnosis, as well as flare identification and management by primary care clinicians can improve patient outcomes such as disease progression and effects on quality of life.

scholarly journals Changes in presentations with features potentially indicating cancer in primary care during the COVID-19 pandemic: a retrospective cohort study

BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e050131
Author(s):  
Lauren J Scott ◽  
Mairead Murphy ◽  
Sarah Price ◽  
Rhys Lewis ◽  
Rachel Denholm ◽  
...  
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Signs And Symptoms ◽  
Patient Characteristics ◽  
Face To Face ◽  
Number Of Patients ◽  
Potential Cancer ◽  
Remote Consultations

ObjectivesTo investigate how the COVID-19 pandemic affected the number of people aged 50+ years presenting to primary care with features that could potentially indicate cancer, and to explore how reporting differed by patient characteristics and in face-to-face vs remote consultations.Design, setting and participantsA retrospective cohort study of general practitioner (GP), nurse and paramedic primary care consultations in 21 practices in South-West England covering 123 947 patients. The models compared potential cancer indicators reported in April–July 2019 with April–July 2020.Main outcome measuresPotential indicators of cancer were identified using code lists for symptoms, signs, test results and diagnoses listed in the National Institute for Health and Care Excellence suspected cancer referral guidance (NG12).ResultsDuring April–July 2019, 17% of registered patients aged 50+ years reported a potential cancer indicator in a consultation with a GP or nurse. During April–July 2020, this reduced to 11% (incidence rate ratio (IRR) 0.64, 95% CI 0.62 to 0.67, p<0.001). Reductions in potential cancer indicators were stable across age group, sex, ethnicity, index of multiple deprivation quintile and shielding status, but less marked in patients with mental health conditions than without (IRR 0.75, 95% CI 0.72 to 0.79, interaction p<0.001). Proportions of GP consultations with potential indicators of cancer reduced between 2019 and 2020 for face-to-face consultations (IRR 0.84, 95% CI 0.76 to 0.92, p<0.001) and increased for remote consultations (IRR 1.17, 95% CI 1.07 to 1.29, p=0.001), although it remained lower in remote consulting than face-to-face in April–July 2020. This difference was greater for nurse/paramedic consultations (face-to-face: IRR 0.61, 95% CI 0.44 to 0.83, p=0.002; remote: IRR 1.60, 95% CI 1.10 to 2.333, p=0.014).ConclusionThe number of patients consulting with presentations that could potentially indicate cancer reduced during the first wave of the COVID-19 pandemic. Patients should be encouraged to continue contacting primary care for persistent signs and symptoms, and GPs and nurses should be encouraged to probe patients for further information during remote consulting, in the absence of non-verbal cues.

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