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Background The incidence of cryptococcosis amongst HIV-negative persons is increasing. Whilst the excellent performance of the CrAg testing in people living with HIV is well described, the diagnostic performance of the CrAg LFA has not been systematically evaluated in HIV-negative cohorts on serum or cerebrospinal fluid. Methods We performed a systematic review to characterise the diagnostic performance of IMMY CrAg® LFA in HIV-negative populations on serum and cerebrospinal fluid. A systematic electronic search was performed using Medline, Embase, Global Health, CENTRAL, WoS Science Citation Index, SCOPUS, Africa-Wide Information, LILACS and WHO Global Health Library. Studies were screened and data extracted from eligible studies by two independent reviewers. A fixed effect meta-analysis was used to estimate the diagnostic sensitivity and specificity. Results Of 447 records assessed for eligibility, nine studies met our inclusion criteria, including 528 participants overall. Amongst eight studies that evaluated the diagnostic performance of the IMMY CrAg® LFA on serum, the pooled median sensitivity was 96% (95% Credible Interval (CrI) 68–100%) with a pooled specificity estimate of 96% (95%CrI 84–100%). Amongst six studies which evaluated the diagnostic performance of IMMY CrAg® LFA on CSF, the pooled median sensitivity was 99% (95%CrI 95–100%) with a pooled specificity median of 99% (95%CrI 95–100%). Conclusions This review demonstrates a high pooled sensitivity and specificity for the IMMY CrAg® LFA in HIV-negative populations, in keeping with findings in HIV-positive individuals. The review was limited by the small number of studies. Further studies using IMMY CrAg® LFA in HIV-negative populations would help to better determine the diagnostic value of this test.

Respiratory syncytial virus (RSV) and influenza viruses are important global causes of morbidity and mortality. We evaluated the diagnostic accuracy of the Luminex NxTAG respiratory pathogen panels (RPPs)™ (index) against other RPPs (comparator) for detection of RSV and influenza viruses. Studies comparing human clinical respiratory samples tested with the index and at least one comparator test were included. A random-effect latent class meta-analysis was performed to assess the specificity and sensitivity of the index test for RSV and influenza. Risk of bias was assessed using the QUADAS-2 tool and certainty of evidence using GRADE. Ten studies were included. For RSV, predicted sensitivity was 99% (95% credible interval [CrI] 96–100%) and specificity 100% (95% CrI 98–100%). For influenza A and B, predicted sensitivity was 97% (95% CrI 89–100) and 98% (95% CrI 88–100) respectively; specificity 100% (95% CrI 99–100) and 100% (95% CrI 99–100), respectively. Evidence was low certainty. Although index sensitivity and specificity were excellent, comparators’ performance varied. Further research with clear patient recruitment strategies could ascertain performance across different populations.Protocol Registration: Prospero CRD42021272062.

Background Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. Methods We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. Results In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. Conclusions We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. Trial registration The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.