Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Re-annotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi

Finding needles in haystacks: Linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Reannotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi.B.R. and C.L.S. acknowledge support from the Intramural Research Program of the National Institutes of Health, National Library of MedicinePeer Reviewe

Addressing the information deficit in global health: lessons from a digital acute care platform in Sri Lanka

Lack of investment in low-income and middle-income countries (LMICs) in systems capturing continuous information regarding care of the acutely unwell patient is hindering global efforts to address inequalities, both at facility and national level. Furthermore, this of lack of data is disempowering frontline staff and those seeking to support them, from progressing setting-relevant research and quality improvement. In contrast to high-income country (HIC) settings, where electronic surveillance has boosted the capability of governments, clinicians and researchers to engage in service-wide healthcare evaluation, healthcare information in resource-limited settings remains almost exclusively paper based. In this practice paper, we describe the efforts of a collaboration of clinicians, administrators, researchers and healthcare informaticians working in South Asia, in addressing the inequality in access to patient information in acute care. Harnessing a clinician-led collaborative approach to design and evaluation, we have implemented a national acute care information platform in Sri Lanka that is tailored to priorities of frontline staff. Iterative adaptation has ensured the platform has the flexibility to integrate with legacy paper systems, support junior team members in advocating for acutely unwell patients and has made information captured accessible to diverse stakeholders to improve service delivery. The same platform is now empowering clinicians to participate in international research and drive forwards improvements in care. During this journey, we have also gained insights on how to overcome well-described barriers to implementation of digital information tools in LMIC. We anticipate that this north–south collaborative approach to addressing the challenges of health system implementation in acute care may provide learning and inspiration to other partnerships seeking to engage in similar work

Operationalisation of the Randomized Embedded Multifactorial Adaptive Platform for COVID-19 trials in a low and lower-middle income critical care learning health system

The Randomized Embedded Multifactorial Adaptive Platform (REMAP-CAP) adapted for COVID-19) trial is a global adaptive platform trial of hospitalised patients with COVID-19. We describe implementation in three countries under the umbrella of the Wellcome supported Low and Middle Income Country (LMIC) critical care network: Collaboration for Research, Implementation and Training in Asia (CCA). The collaboration sought to overcome known barriers to multi centre-clinical trials in resource-limited settings. Methods described focused on six aspects of implementation: i, Strengthening an existing community of practice; ii, Remote study site recruitment, training and support; iii, Harmonising the REMAP CAP- COVID trial with existing care processes; iv, Embedding REMAP CAP- COVID case report form into the existing CCA registry platform, v, Context specific adaptation and data management; vi, Alignment with existing pandemic and critical care research in the CCA. Methods described here may enable other LMIC sites to participate as equal partners in international critical care trials of urgent public health importance, both during this pandemic and beyond

Implementing an intensive care registry in India: preliminary results of the case-mix program and an opportunity for quality improvement and research

Background: The epidemiology of critical illness in India is distinct from high-income countries. However, limited data exist on resource availability, staffing patterns, case-mix and outcomes from critical illness. Critical care registries, by enabling a continual evaluation of service provision, epidemiology, resource availability and quality, can bridge these gaps in information. In January 2019, we established the Indian Registry of IntenSive care to map capacity and describe case-mix and outcomes. In this report, we describe the implementation process, preliminary results, opportunities for improvement, challenges and future directions. Methods: All adult and paediatric ICUs in India were eligible to join if they committed to entering data for ICU admissions. Data are collected by a designated representative through the electronic data collection platform of the registry. IRIS hosts data on a secure cloud-based server and access to the data is restricted to designated personnel and is protected with standard firewall and a valid secure socket layer (SSL) certificate. Each participating ICU owns and has access to its own data. All participating units have access to de-identified network-wide aggregate data which enables benchmarking and comparison. Results: The registry currently includes 14 adult and 1 paediatric ICU in the network (232 adult ICU beds and 9 paediatric ICU beds). There have been 8721 patient encounters with a mean age of 56.9 (SD 18.9); 61.4% of patients were male and admissions to participating ICUs were predominantly unplanned (87.5%). At admission, most patients (61.5%) received antibiotics, 17.3% needed vasopressors, and 23.7% were mechanically ventilated. Mortality for the entire cohort was 9%. Data availability for demographics, clinical parameters, and indicators of admission severity was greater than 95%. Conclusions: IRIS represents a successful model for the continual evaluation of critical illness epidemiology in India and provides a framework for the deployment of multi-centre quality improvement and context-relevant clinical research

Impact of COVID-19 on non-COVID intensive care unit service utilization, case mix and outcomes: A registry-based analysis from India

Background: Coronavirus disease 2019 (COVID-19) has been responsible for over 3.4 million deaths globally and over 25 million cases in India. As part of the response, India imposed a nation-wide lockdown and prioritized COVID-19 care in hospitals and intensive care units (ICUs). Leveraging data from the Indian Registry of IntenSive care, we sought to understand the impact of the COVID-19 pandemic on critical care service utilization, case-mix, and clinical outcomes in non-COVID ICUs. Methods: We included all consecutive patients admitted between 1st October 2019 and 27th September 2020. Data were extracted from the registry database and included patients admitted to the non-COVID or general ICUs at each of the sites. Outcomes included measures of resource-availability, utilisation, case-mix, acuity, and demand for ICU beds. We used a Mann-Whitney test to compare the pre-pandemic period (October 2019 - February 2020) to the pandemic period (March-September 2020). In addition, we also compared the period of intense lockdown (March-May 31st 2020) with the pre-pandemic period. Results: There were 3424 patient encounters in the pre-pandemic period and 3524 encounters in the pandemic period. Comparing these periods, weekly admissions declined (median [Q1 Q3] 160 [145,168] to 113 [98.5,134]; p<0.001); unit turnover declined (median [Q1 Q3] 12.1 [11.32,13] to 8.58 [7.24,10], p<0.001), and APACHE II score increased (median [Q1 Q3] 19 [19,20] to 21 [20,22] ; p<0.001). Unadjusted ICU mortality increased (9.3% to 11.7%, p=0.015) and the length of ICU stay was similar (median [Q1 Q3] 2.11 [2, 2] vs. 2.24 [2, 3] days; p=0.151). Conclusion: Our registry-based analysis of the impact of COVID-19 on non-COVID critical care demonstrates significant disruptions to healthcare utilization during the pandemic and an increase in the severity of illness