Flow chart showing the sequence of patient inclusion, study patient participation (questionnaire and rapid HIV testing) and doctor participation (questionnaire).

<p>Boxes with rounded corners indicate numbers; those with squared corners indicate processes.</p

Patient characteristics, in total and by HIV risk group.

<p>Patient characteristics, in total and by HIV risk group.</p

Patient reasons for not mentioning HIV during the consultation with their emergency department doctor.

<p>Patient reasons for not mentioning HIV during the consultation with their emergency department doctor.</p

Doctor reasons for not mentioning HIV and not offering testing to patients when indicated according to the Federal Office of Public Health (FOPH) testing recommendations.

<p>Doctor reasons for not mentioning HIV and not offering testing to patients when indicated according to the Federal Office of Public Health (FOPH) testing recommendations.</p

Flow chart showing the identification of Federal Office of Public Health (FOPH) indications for HIV testing, mention of HIV and offer of HIV testing by emergency department (ED) doctors, presented according to patient HIV risk group.

<p>¹Group A: patients with a reason for presenting suggestive of primary HIV infection; Group B: patients presenting HIV risk factors and/or reporting condomless sex with sexual partner(s) with risk factors; Group C: patients reporting condomless sex but no other risk factors; Group D: patients reporting no risk factors.</p

Numbers of patients seen in each clinical service during the four twelve-month periods studied.

<p>Abbreviations: OP, outpatients; IP, inpatients; ICU, intensive care units; ED, emergency departments.</p

HIV testing practices by clinical service and year.

<p>Figure shows the numbers of tests performed (A) and the testing rates (B) in each clinical service during each of the four twelve-month periods studied. Abbreviations: OP, outpatients; IP, inpatients; ICU, intensive care units; ED, emergency departments.</p

Percentage of tests performed with positive result, median duration of inpatient stay, mean age of all patients seen and mean age of patients tested, for each clinical service.

<p>As data were not significantly different between 2008–2009 and 2010–2011, they have been pooled for clarity.</p><p>Abbreviations: IQR, interquartile range; SD, standard deviation; N/A, not applicable; OP, outpatients; IP, inpatients; ED, emergency department.</p

An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves

Patients with cancer have been shown to have increased risk of COVID-19 severity. We previously built and validated the COVID-19 Risk in Oncology Evaluation Tool (CORONET) to predict the likely severity of COVID-19 in patients with active cancer who present to hospital. We assessed the differences in presentation and outcomes of patients with cancer and COVID-19, depending on the wave of the pandemic. We examined differences in features at presentation and outcomes in patients worldwide, depending on the waves of the pandemic: wave 1 D614G (n = 1430), wave 2 Alpha (n = 475), and wave 4 Omicron variant (n = 63, UK and Spain only). The performance of CORONET was evaluated on 258, 48, and 54 patients for each wave, respectively. We found that mortality rates were reduced in subsequent waves. The majority of patients were vaccinated in wave 4, and 94% were treated with steroids if they required oxygen. The stages of cancer and the median ages of patients significantly differed, but features associated with worse COVID-19 outcomes remained predictive and did not differ between waves. The CORONET tool performed well in all waves, with scores in an area under the curve (AUC) of >0.72. We concluded that patients with cancer who present to hospital with COVID-19 have similar features of severity, which remain discriminatory despite differences in variants and vaccination status. Survival improved following the first wave of the pandemic, which may be associated with vaccination and the increased steroid use in those patients requiring oxygen. The CORONET model demonstrated good performance, independent of the SARS-CoV-2 variants