ArticlePDF Available

The value of open-source clinical science in pandemic response: lessons from ISARIC

December 2021
The Lancet Infectious Diseases 21(12):1623-1624

DOI:10.1016/S1473-3099(21)00565-X

Authors:

Ali Abbas

University of Agriculture Faisalabad

Sheryl Ann Abdukahil

National Guard Health Affairs

Show all 1695 authorsHide

PIIS14733099210056 5X.pdf

Content uploaded by Jose Andres Calvache

Content may be subject to copyright.

Comment

www.thelancet.com/infection Vol 21 December 2021

1623

1 Freeman MC, Akogun O, Belizario Jr V, et al. Challenges and opportunities

for control and elimination of soil-transmitted helminth infection beyond

2020. PLoS Negl Trop Dis 2019; 13: e0007201.

2 Hotez PJ, Alvarado M, Basáñez M-G, et al. The Global Burden of Disease

Study 2010: interpretation and implications for the neglected tropical

diseases. PLoS Negl Trop Dis 2014; 8: e2865.

3 WHO. Ending the neglect to attain the sustainable development goals:

a road map for neglected tropical diseases 2021–2030. World Health

Organization, 2020. https://www.who.int/neglected_diseases/Ending-the-

neglect-to-attain-the-SDGs--NTD-Roadmap.pdf (accessed Nov 12, 2020).

4 Anderson RM, May RM. Population dynamics of human helminth

infections: control by chemotherapy. Nature 1982; 297: 557–63.

5 Werkman M, Wright JE, Truscott JE, et al. The impact of community-wide,

mass drug administration on aggregation of soil-transmitted helminth

infection in human host populations. Parasit Vectors 2020; 13: 290.

6 Uniting to Combat Neglected Tropical Diseases. The London Declaration on

Neglected Tropical Diseases. 2021. https://unitingtocombatntds.org/

resource-hub/who-resources/london-declaration-neglected-tropical-

diseases/ (accessed Jan 30, 2021).

7 Claerebout E, Geldhof P. Helminth vaccines for ruminants.

Vet Clin North Am Food Anim Pract 2020; 36: 159–71.

8 Siddiqui AA, Siddiqui SZ. Sm-p80-based schistosomiasis vaccine:

preparation for human clinical trials. Trends Parasitol 2017; 33: 194–201.

9 Chapman PR, Webster R, Giacomin P, et al. Vaccination of human

participants with attenuated Necator americanus hookworm larvae and

human challenge in Australia: a dose-ﬁnding study and randomised,

placebo-controlled, phase 1 trial. Lancet Infect Dis 2021; published online

Aug 19. https://doi.org/10.1016/S1473-3099(21)00153-5.

10 Kura K, Truscott JE, Toor J, Anderson RM. Modelling the impact of a

Schistosoma mansoni vaccine and mass drug administration to achieve

morbidity control and transmission elimination. PLoS Negl Trop Dis 2019;

13: e0007349.

The value of open-source clinical science in pandemic

response: lessons from ISARIC

The International Severe Acute Respiratory and

Emerging Infection Consortium (ISARIC) is a global

federation of clinical research networks that work

collaboratively to prevent illness and deaths from

infectious disease outbreaks. In 2014, we proposed

that eﬀective and timely research during outbreaks of

emerging infections would beneﬁt from pre-prepared

research tools, global collaboration, and research-ready

clinical networks.1 After applying this research model

to several outbreaks, and particularly the COVID-19

pandemic, we can now explore what has been achieved

to date.

ISARIC launched the Clinical Characterisation Protocol

(CCP), in collaboration with WHO in 2012.1 A key aim

was to avoid delays in initiating research, such as those

seen during the 2009–10 inﬂuenza A H1N1pdm09

pandemic and other outbreaks.2 The CCP and

associated case report forms (CRFs) were the ﬁrst steps

towards global, harmonised clinical datasets to create

frameworks for characterising current and potential

future emerging infectious diseases. These adaptable

research tools were developed and shared early in the

COVID-19 pandemic by ISARIC3 to prepare the health

community for outbreak research.

After receiving approvals from the WHO Ethics

Committee in 2013 (RPC571 and RPC572, 25/04/2013),

the CCP was implemented in various settings (appendix

p 2). This broad uptake of the CCP, and the development

of tools to support its implementation for various

diseases and contexts, meant that ISARIC partners were

primed for a rapid response when COVID-19 emerged

and spread in 2020. Working with WHO, ISARIC

used early reports from Wuhan, China, to inform the

adaptation of the CRF. On Jan 24, 2020, when less than

1000 COVID-19 cases had been reported globally, the

ISARIC-WHO COVID-19 CRF was launched and made

available globally.3 ISARIC provided a data management

platform, using REDCap, to collect and store data for

institutions that lacked available resources or necessary

infrastructure. Rapid access to the CRFs enabled

collection of critical data for early characterisation of

the disease in hospitalised patients, ﬁrst in Wuhan,4

and then globally.5–8 Institutions that chose to use the

CRF and database simultaneously, collected data for

local analyses and also contributed data for aggregated

international analyses. As the COVID-19 pandemic

progressed and an increasing number of institutions

contributed data, the research beneﬁts of a large,

aggregated dataset also increased. To disseminate this

knowledge, ISARIC and international collaborators

issued the ﬁrst online report analysing risk factors,

symptoms, treatments, and outcomes of patients with

COVID-19 in March, 2020.9

As of July, 2021, 1651 sites in 57 countries have

contributed data from 516 689 individuals with

COVID-19 (appendix p 1),10 including 272 759 individuals

See Online for appendix

Published Online

October 4, 2021

https://doi.org/10.1016/

S1473-3099(21)00565-X

Comment

1624

www.thelancet.com/infection Vol 21 December 2021

from low-income and middle-income countries (as

deﬁned by the Organisation for Economic Co-operation

and Development). These data have informed a publicly

available, regularly updated, clinical data report, with

the aim of accelerating a collective understanding

of COVID-19 globally. The data series have been

published frequently on medrxiv.org, to help inform

the development of policies and clinical management

guidelines. Through the collaborative platform, analyses

are underway for over 20 studies.

This approach has enabled global collaborators

to produce highly relevant outputs during a novel

pandemic. Research preparedness helped avoid or

minimise well known bottlenecks, including protocol

development, database set-up, contractual agreements,

funding applications, and ethics and regulatory

approvals. Additionally, the open-access research tools

enabled the standardised collection of high-quality data,

for ease of aggregation and harmonisation. Bringing

together a global community in a common data platform

fosters a sense of solidarity and community, which is

valued by collaborators and contributors (appendix p 3).

Coordinating research eﬀorts during an evolving

pandemic, across more than 1600 institutions, is a

signiﬁcant undertaking and requires eﬃcient systems

to track and acknowledge contributors. Promoting

local ownership of data and research strategy requires

provision of support to institutions with varying

resource levels. The burden of data collection on health-

care workers, who are already facing considerable

pressures, must be balanced with eﬃcient systems to

deliver high-calibre science that will inform and improve

patient care. By supporting research groups with tools

that are standardised but ﬂexible, ISARIC has delivered

an adaptive, observational infrastructure that enables

the generation, collection, analysis, and dissemination

of important knowledge during a pandemic. The success

of ISARIC highlights the fundamental importance of

investment in research preparedness by health-care

systems, funders, and government organisations.

Our COVID-19 experience has shown that a global

collaborative approach, based on research readiness in a

peer-to-peer network, is achievable and eﬀective. If this

approach can be developed and maintained for future

epidemic and pandemic research responses, the beneﬁts

should be even greater.

Members of the ISARIC Clinical Characterisation Group and their declaration of

interests statements are listed in the appendix (pp 4–9, 11–14).

The ISARIC Clinical Characterisation Group

james.lee@ndm.ox.ac.uk

Centre for Tropical Medicine and Global Health, University of Oxford,

Oxford OX3 7LG, UK

1 Dunning JW, Merson L, Rohde GGU, et al. Open source clinical science for

emerging infections. Lancet Infect Dis 2014; 14: 8–9.

2 Rojek AM, Moran J, Horby PW. Core minimal datasets to advance clinical

research for priority epidemic diseases. Clin Infect Dis 2020; 70: 696–97.

3 Akhvlediani T, Ali SM, Angus DC, et al. Global outbreak research: harmony

not hegemony. Lancet Infect Dis 2020; 20: 770–72.

4 Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019

novel coronavirus in Wuhan, China. Lancet 2020; 395: 497–506.

5 Docherty AB, Harrison EM, Green CA, et al. Features of 20 133 UK patients

in hospital with covid-19 using the ISARIC WHO Clinical Characterisation

Protocol: prospective observational cohort study. BMJ 2020; 369: m1985.

6 Cummings MJ, Baldwin MR, Abrams D, et al. Epidemiology, clinical course,

and outcomes of critically ill adults with COVID-19 in New York City:

a prospective cohort study. Lancet 2020; 395: 1763–70.

7 Lescure F-X, Bouadma L, Nguyen D, et al. Clinical and virological data

of the ﬁrst cases of COVID-19 in Europe: a case series. Lancet Infect Dis

2020; 20: 697–706.

8 Munblit D, Nekliudov NA, Bugaeva P, et al. StopCOVID cohort:

an observational study of 3480 patients admitted to the Sechenov

University hospital network in Moscow city for suspected COVID-19

infection. Clin Infect Dis 2020; 73: 1–11.

9 ISARIC. COVID-19 report: 27 March 2020. https://isarictest.wpengine.com/

wp-content/uploads/2020/11/ISARIC_Data_Platform_COVID-19_

Report_27.03.2020.pdf (accessed Sept 8, 2021).

10 Baillie JK, Baruch J, Beane A, et al. ISARIC Clinical Data Report issued:

14 July 2021. medRxiv 2021; published online July 14. https://doi.

org/10.1101/2020.07.17.20155218 (preprint).

For the ISARIC clinical data

reports see https://isaric.org/

research/covid-19-clinical-

research-resources/evidence-

reports/

Long-term consequences of the misuse of ivermectin data

Ivermectin is an oral anti-infective medicine that is

integral to neglected tropical disease programmes.

It is safe and eﬀective for the treatment and control

of lymphatic ﬁlariasis, scabies, and onchocerciasis,

sometimes as part of a mass drug administration, as

recognised in the WHO road map for neglected tropical

diseases 2021–30.1 The WHO essential medicines list

provides recommendations for minimum medicine

needs for a basic health-care system, which includes

ivermectin as an anthelmintic, antiﬁlarial, and anti-

ectoparasitic treatment.2

There has been a groundswell of opinion across several

countries that ivermectin might be useful in reducing

the symptoms of and mortality due to COVID-19, with

many citing meta-analyses that infer positive eﬀects;3

however, these conclusions appear to be unreliable. On

Published Online

October 18, 2021

https://doi.org/10.1016/

S1473-3099(21)00630-7

For the French translation of

the Comment see Online for

appendix 1

For the Spanish translation of

the Comment see Online for

appendix 2

Association of cancer and outcomes of patients hospitalized for COVID-19 between 2020 and 2023

Article

Apr 2025

Background The coronavirus disease 2019 (COVID-19) has caused substantial morbidity and mortality on a global scale. A strong correlation has been found between COVID-19 treatment outcomes and noncommunicable diseases such as cancers. However, there is limited information on the outcomes of cancer patients who were hospitalised for COVID-19. Methods We conducted an analysis on data collected in a large prospective cohort study set-up by the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC). All patients with laboratory-confirmed or clinically-diagnosed SARS-CoV-2 infection were included. Cancer was defined as having a current solid organ or haematological malignancy. The following outcomes were assessed; 30-day in-hospital mortality, intensive care unit (ICU) admission, length of hospitalization and receipt of higher-level care. Results Of the 560,547 hospitalised individuals who were analysed, 27,243 (4.9%) had cancer. Overall, cancer patients were older and had more comorbidities than non-cancer patients. Patients with cancer had higher 30-day in-hospital mortality than non-cancer patients (29.1.3% vs 18.0%) and longer hospital stays (median of 12 days vs 8 days). However, patients with cancer were admitted less often to intensive care units than non-cancer patients (12.6% vs 17.1%) and received less invasive mechanical ventilation than non-cancer patients (4.5% vs 7.6%). The hazard ratio of dying from cancer, adjusted for age, sex and country income level was 1.18 (95%CI: 1.15-1.2). Conclusions This study's findings underscore the heightened vulnerability of hospitalized COVID-19 patients with cancer, revealing a higher mortality rate, longer hospital stays, and an unstructured pattern of care that reflects the complexity of managing severely ill patients during a public health crisis like the COVID-19 pandemic.

The Ebola Data Platform: A prospective, standardised, clinical dataset collected during the 2013-2016 West African Ebola outbreak

Article

Full-text available

Sep 2024

The Ebola Data Platform (EDP) was developed to strengthen knowledge and capacity across health, research, and humanitarian communities to reduce the impact of Ebola through responsible data use. This collaborative initiative was established by West African governments, NGOs, academic organisations, and intra-governmental health organisations directly involved in the 2013–2016 West African Ebola outbreak. The platform was established to provide a centralised, standardised dataset of individual patient data collected during the outbreak for the purpose of research to improve Ebola treatment and control, and includes over 13,600 patient records of individuals infected and treated from 22 different Ebola treatment centres across Guinea, Sierra Leone, Liberia, and Nigeria. Patient data are available from treatment centre triage and admission, inpatient clinical observations, and outcomes, with outpatient follow-up available for some datasets. Data include signs and symptoms, pre-existing comorbidities, vital signs, laboratory testing, treatments, complications, dates of admission and discharge, mortality, viral strains, and other data. This publication describes characteristics of the EDP dataset, its architecture, methods for data access and tools for utilising the dataset.

Optimising Clinical Epidemiology in Disease Outbreaks: Analysis of ISARIC-WHO COVID-19 Case Report Form Utilisation

Article

Full-text available

Aug 2024

Citation: Merson, L.; Duque, S.; Garcia-Gallo, E.; Yeabah, T.O.; Rylance, J.; Diaz, J.; Flahault, A.; ISARIC Clinical Characterisation Group. Optimising Clinical Epidemiology in Disease Outbreaks: Analysis of ISARIC-WHO COVID-19 Case Report Form Utilisation. Abstract: Standardised forms for capturing clinical data promote consistency in data collection and analysis across research sites, enabling faster, higher-quality evidence generation. ISARIC and the World Health Organization have developed case report forms (CRFs) for the clinical characterisation of several infectious disease outbreaks. To improve the design and quality of future forms, we analysed the inclusion and completion rates of the 243 fields on the ISARIC-WHO COVID-19 CRF. Data from 42 diverse collaborations, covering 1886 hospitals and 950,064 patients, were analysed. A mean of 129.6 fields (53%) were included in the adapted CRFs implemented across the sites. Consistent patterns of field inclusion and completion aligned with globally recognised research priorities in outbreaks of novel infectious diseases. Outcome status was the most highly included (95.2%) and completed (89.8%) field, followed by admission demographics (79.1% and 91.6%), comorbidities (77.9% and 79.0%), signs and symptoms (68.9% and 78.4%), and vitals (70.3% and 69.1%). Mean field completion was higher in severe patients (70.2%) than in all patients (61.6%). The results reveal how clinical characterisation CRFs can be streamlined to reduce data collection time, including the modularisation of CRFs, to offer a choice of data volume collection and the separation of critical care interventions. This data-driven approach to designing CRFs enhances the efficiency of data collection to inform patient care and public health response.

Optimising Clinical Epidemiology in Disease Outbreaks: Analysis of ISARIC-WHO COVID-19 Case Report Form Utilisation

Article

Full-text available

Aug 2024

Standardised forms for capturing clinical data promote consistency in data collection and analysis across research sites, enabling faster, higher-quality evidence generation. ISARIC and the World Health Organization have developed case report forms (CRFs) for the clinical characterisation of several infectious disease outbreaks. To improve the design and quality of future forms, we analysed the inclusion and completion rates of the 243 fields on the ISARIC-WHO COVID-19 CRF. Data from 42 diverse collaborations, covering 1886 hospitals and 950,064 patients, were analysed. A mean of 129.6 fields (53%) were included in the adapted CRFs implemented across the sites. Consistent patterns of field inclusion and completion aligned with globally recognised research priorities in outbreaks of novel infectious diseases. Outcome status was the most highly included (95.2%) and completed (89.8%) field, followed by admission demographics (79.1% and 91.6%), comorbidities (77.9% and 79.0%), signs and symptoms (68.9% and 78.4%), and vitals (70.3% and 69.1%). Mean field completion was higher in severe patients (70.2%) than in all patients (61.6%). The results reveal how clinical characterisation CRFs can be streamlined to reduce data collection time, including the modularisation of CRFs, to offer a choice of data volume collection and the separation of critical care interventions. This data-driven approach to designing CRFs enhances the efficiency of data collection to inform patient care and public health response.

Creation of Standardized Common Data Elements for Diagnostic Tests in Infectious Disease Studies: Semantic and Syntactic Mapping

Article

Jun 2024
J MED INTERNET RES

Background It is necessary to harmonize and standardize data variables used in case report forms (CRFs) of clinical studies to facilitate the merging and sharing of the collected patient data across several clinical studies. This is particularly true for clinical studies that focus on infectious diseases. Public health may be highly dependent on the findings of such studies. Hence, there is an elevated urgency to generate meaningful, reliable insights, ideally based on a high sample number and quality data. The implementation of core data elements and the incorporation of interoperability standards can facilitate the creation of harmonized clinical data sets. Objective This study’s objective was to compare, harmonize, and standardize variables focused on diagnostic tests used as part of CRFs in 6 international clinical studies of infectious diseases in order to, ultimately, then make available the panstudy common data elements (CDEs) for ongoing and future studies to foster interoperability and comparability of collected data across trials. Methods We reviewed and compared the metadata that comprised the CRFs used for data collection in and across all 6 infectious disease studies under consideration in order to identify CDEs. We examined the availability of international semantic standard codes within the Systemized Nomenclature of Medicine - Clinical Terms, the National Cancer Institute Thesaurus, and the Logical Observation Identifiers Names and Codes system for the unambiguous representation of diagnostic testing information that makes up the CDEs. We then proposed 2 data models that incorporate semantic and syntactic standards for the identified CDEs. Results Of 216 variables that were considered in the scope of the analysis, we identified 11 CDEs to describe diagnostic tests (in particular, serology and sequencing) for infectious diseases: viral lineage/clade; test date, type, performer, and manufacturer; target gene; quantitative and qualitative results; and specimen identifier, type, and collection date. Conclusions The identification of CDEs for infectious diseases is the first step in facilitating the exchange and possible merging of a subset of data across clinical studies (and with that, large research projects) for possible shared analysis to increase the power of findings. The path to harmonization and standardization of clinical study data in the interest of interoperability can be paved in 2 ways. First, a map to standard terminologies ensures that each data element’s (variable’s) definition is unambiguous and that it has a single, unique interpretation across studies. Second, the exchange of these data is assisted by “wrapping” them in a standard exchange format, such as Fast Health care Interoperability Resources or the Clinical Data Interchange Standards Consortium’s Clinical Data Acquisition Standards Harmonization Model.

ISO/TS 21564:2019- based Evaluation of a Semantic Map between Variables in the ISARIC Freestanding Follow Up Survey and ORCHESTRA Studies

Article

Full-text available

Nov 2023
J MED SYST

The COVID-19 pandemic has led to tremendous investment in clinical studies to generate much-needed knowledge on the prevention, diagnosis, treatment and long-term effects of the disease. Case report forms, comprised of questions and answers (variables), are commonly used to collect data in clinical trials. Maximizing the value of study data depends on data quality and on the ability to easily pool and share data from several sources. ISARIC, in collaboration with the WHO, has created a case report form that is available for use by the scientific community to collect COVID-19 trial data. One of such research initiatives collecting and analyzing multi-country and multi-cohort COVID-19 study data is the Horizon 2020 project ORCHESTRA. Following the ISO/TS 21564:2019 standard, a mapping between five ORCHESTRA studies’ variables and the ISARIC Freestanding Follow-Up Survey elements was created. Measures of correspondence of shared semantic domain of 0 (perfect match), 1 (fully inclusive match), 2 (partial match), 4 (transformation required) or 4* (not present in ORCHESTRA) as compared to the target code system, ORCHESTRA study variables, were assigned to each of the elements in the ISARIC FUP case report form (CRF) which was considered the source code system. Of the ISARIC FUP CRF’s variables, around 34% were found to show an exact match with corresponding variables in ORCHESTRA studies and about 33% showed a non-inclusive overlap. Matching variables provided information on patient demographics, COVID-19 testing, hospital admission and symptoms. More in-depth details are covered in ORCHESTRA variables with regards to treatment and comorbidities. ORCHESTRA’s Long-Term Sequelae and Fragile population studies’ CRFs include 32 and 27 variables respectively which were evaluated as a perfect match to variables in the ISARIC FUP CRF. Our study serves as an example of the kind of maps between case report form variables from different research projects needed to link ongoing COVID-19 research efforts and facilitate collaboration and data sharing. To enable data aggregation across two data systems, the information they contain needs to be connected through a map to determine compatibility and transformation needs. Combining data from various clinical studies can increase the power of analytical insights. Supplementary information The online version contains supplementary material available at 10.1007/s10916-023-02012-4.

Liver injury in hospitalized patients with COVID-19: An International observational cohort study

Article

Full-text available

Sep 2023
PLOS ONE

Background Using a large dataset, we evaluated prevalence and severity of alterations in liver enzymes in COVID-19 and association with patient-centred outcomes. Methods We included hospitalized patients with confirmed or suspected SARS-CoV-2 infection from the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) database. Key exposure was baseline liver enzymes (AST, ALT, bilirubin). Patients were assigned Liver Injury Classification score based on 3 components of enzymes at admission: Normal; Stage I) Liver injury: any component between 1-3x upper limit of normal (ULN); Stage II) Severe liver injury: any component ≥3x ULN. Outcomes were hospital mortality, utilization of selected resources, complications, and durations of hospital and ICU stay. Analyses used logistic regression with associations expressed as adjusted odds ratios (OR) with 95% confidence intervals (CI). Results Of 17,531 included patients, 46.2% (8099) and 8.2% (1430) of patients had stage 1 and 2 liver injury respectively. Compared to normal, stages 1 and 2 were associated with higher odds of mortality (OR 1.53 [1.37–1.71]; OR 2.50 [2.10–2.96]), ICU admission (OR 1.63 [1.48–1.79]; OR 1.90 [1.62–2.23]), and invasive mechanical ventilation (OR 1.43 [1.27–1.70]; OR 1.95 (1.55–2.45). Stages 1 and 2 were also associated with higher odds of developing sepsis (OR 1.38 [1.27–1.50]; OR 1.46 [1.25–1.70]), acute kidney injury (OR 1.13 [1.00–1.27]; OR 1.59 [1.32–1.91]), and acute respiratory distress syndrome (OR 1.38 [1.22–1.55]; OR 1.80 [1.49–2.17]). Conclusions Liver enzyme abnormalities are common among COVID-19 patients and associated with worse outcomes.

Sex differences in post-acute neurological sequelae of SARS-CoV-2 and symptom resolution in adults after COVID-19 hospitalization: an international multicenter prospective observational study

Article

Full-text available

Feb 2024

Although it is known that COVID-19 can present with a range of neurological manifestations and in-hospital complications, sparse data exist if these initial neurological symptoms of COVID-19 are closely associated with post-acute neurological sequelae of SARS-CoV-2 (PANSC) and if female versus male sex impacts the symptom resolution. In this international, multicentre, prospective observational study across 407 sites from 15 countries (January/30th/2020-April/30th/2022), we report the prevalence and risk factors of PANSC among hospitalized adults and investigate the differences between males and females on neurological symptom resolution over time. PANSC included altered consciousness/confusion, fatigue/malaise, anosmia, dysgeusia, and muscle aches/joint pain, which were collected at the index hospitalization and during the follow-up assessments. The analysis considered time to resolution of individual and all neurological symptoms. Resulting times were modeled by Weibull regression, assuming mixed-case interval censoring, with sex and age included as covariates. Model results were summarized as cumulative probability functions and age- and sex-adjusted median times to resolution. We included 6,862 hospitalized adults with COVID-19, who had follow-up assessments. The median age of participants was 57 years (39.2% females). Males and females had similar baseline characteristics except that more males (vs. females) were admitted to Intensive Care Unit (30.5% vs. 20.3%) and received mechanical ventilation (17.2% vs. 11.8%). Approximately 70% of patients had multiple neurological symptoms at the first follow-up (median=102 days). Fatigue (49.9%) and myalgia/arthralgia (45.2%) were the most prevalent symptoms of PANSC at the initial follow-up. Reported prevalence in females was generally higher (vs. males) for all symptoms. At 12 months, anosmia and dysgeusia were resolved in most patients, though fatigue, altered consciousness, and myalgia remained unresolved in >10% of the cohort. Females had a longer time to resolution (5.2 vs. 3.4 months) of neurological symptoms at follow-up for those with more than one neurological symptom. In multivariable analysis, males were associated with a shorter time to resolution of symptoms (Hazard Ratio=1.53; 95% Confidence Interval =1.39–1.69). Intensive Care Unit admission was associated with a longer time to the resolution of symptoms (Hazard Ratio =0.68; 95% Confidence Interval=0.60–0.77). Post-discharge stroke was uncommon (0.3% in females; 0.5% in males). Despite the methodological challenges of survey data, this international multicentre prospective cohort study demonstrates that PANSC following index hospitalization is high. Symptom prevalence was higher and took longer to resolve in females than in males. This supports that whilst males were sicker during acute illness, females were disproportionately affected by PANSC.

Lightweight transformers for clinical natural language processing

Article

Full-text available

Jan 2024

Specialised pre-trained language models are becoming more frequent in Natural language Processing (NLP) since they can potentially outperform models trained on generic texts. BioBERT (Sanh et al., Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter. arXiv preprint arXiv: 1910.01108 , 2019) and BioClinicalBERT (Alsentzer et al., Publicly available clinical bert embeddings. In Proceedings of the 2nd Clinical Natural Language Processing Workshop , pp. 72–78, 2019) are two examples of such models that have shown promise in medical NLP tasks. Many of these models are overparametrised and resource-intensive, but thanks to techniques like knowledge distillation, it is possible to create smaller versions that perform almost as well as their larger counterparts. In this work, we specifically focus on development of compact language models for processing clinical texts (i.e. progress notes, discharge summaries, etc). We developed a number of efficient lightweight clinical transformers using knowledge distillation and continual learning, with the number of parameters ranging from 15 million to 65 million. These models performed comparably to larger models such as BioBERT and ClinicalBioBERT and significantly outperformed other compact models trained on general or biomedical data. Our extensive evaluation was done across several standard datasets and covered a wide range of clinical text-mining tasks, including natural language inference, relation extraction, named entity recognition and sequence classification. To our knowledge, this is the first comprehensive study specifically focused on creating efficient and compact transformers for clinical NLP tasks. The models and code used in this study can be found on our Huggingface profile at https://huggingface.co/nlpie and Github page at https://github.com/nlpie-research/Lightweight-Clinical-Transformers , respectively, promoting reproducibility of our results.

Thrombotic and hemorrhagic complications of COVID-19 for adults hospitalized in high-income countries compared to low-and middle-income countries in an international registry

Article

Jul 2023

Background COVID-19 has been associated with a broad range of thromboembolic, ischemic, and hemorrhagic complications (coagulopathy complications). Most studies have focused on patients with severe disease from high-income countries (HIC). Objectives The main aims were to compare the frequency of coagulopathy complications in developing countries (low- and middle-income countries (LMIC)) with those in HICs, to delineate the frequency across a range of treatment levels, and to determine associations with in-hospital mortality. Patients/Methods Adult patients enrolled in an observational, multinational registry, the International Severe Acute Respiratory and Emerging Infections COVID-19 study, between January 1, 2020 and September 15, 2021 met inclusion criteria, including admission to the hospital for lab-confirmed, acute COVID-19 and data on complications and survival. The advanced treatment cohort received care such as admission to intensive care, mechanical ventilation, or inotropes or vasopressors- the basic treatment cohort did not receive any of these interventions. Results The study population was 495,682 patients from 55 countries- 63% from LMIC; 85% were in the basic treatment cohort. The frequency of coagulopathy complications was higher in HICs (0.76-3.4%) than in LMICs (0.09-1.22%). Complications were more frequent in the advanced treatment cohort compared to the basic treatment cohort. Coagulopathy complications were associated with increased in-hospital mortality (OR 1.58, 95% CI 1.52-1.64). The increased mortality associated with these complications was higher in LMICs (58.5%) than in HICs (35.4%). After controlling for coagulopathy complications, treatment intensity, and multiple other factors, mortality was higher for patients in LMICs than for patients in HICs (OR 1.45, 95% CI 1.39-1.51). Conclusions In a large, international registry of patients hospitalized with COVID-19, coagulopathy complications were more frequent in HICs than in LMICs (developing countries). Increased mortality associated with coagulopathy complications was of greater magnitude for patients in LMICs. Additional research is needed regarding timely diagnosis and intervention for coagulation derangements associated with COVID-19, particularly for limited resource settings.

StopCOVID cohort: An observational study of 3,480 patients admitted to the Sechenov University hospital network in Moscow city for suspected COVID-19 infection

Article

Full-text available

Oct 2020
CLIN INFECT DIS

Background The epidemiology, clinical course, and outcomes of COVID-19 patients in the Russian population are unknown. Information on the differences between laboratory-confirmed and clinically-diagnosed COVID-19 in real-life settings is lacking. Methods We extracted data from the medical records of adult patients who were consecutively admitted for suspected COVID-19 infection in Moscow, between April 8 and May 28, 2020. Results Of the 4261 patients hospitalised for suspected COVID-19, outcomes were available for 3480 patients (median age 56 years (interquartile range 45-66). The commonest comorbidities were hypertension, obesity, chronic cardiac disease and diabetes. Half of the patients (n=1728) had a positive RT-PCR while 1748 were negative on RT-PCR but had clinical symptoms and characteristic CT signs suggestive of COVID-19 infection.No significant differences in frequency of symptoms, laboratory test results and risk factors for in-hospital mortality were found between those exclusively clinically diagnosed or with positive SARS-CoV-2 RT-PCR.In a multivariable logistic regression model the following were associated with in-hospital mortality; older age (per 1 year increase) odds ratio [OR] 1.05 (95% confidence interval (CI) 1.03 - 1.06); male sex (OR 1.71, 1.24 - 2.37); chronic kidney disease (OR 2.99, 1.89 – 4.64); diabetes (OR 2.1, 1.46 - 2.99); chronic cardiac disease (OR 1.78, 1.24 - 2.57) and dementia (OR 2.73, 1.34 – 5.47). Conclusions Age, male sex, and chronic comorbidities were risk factors for in-hospital mortality. The combination of clinical features were sufficient to diagnose COVID-19 infection indicating that laboratory testing is not critical in real-life clinical practice.

ISARIC COVID-19 Clinical Data Report: 8 June 2020

Preprint

Full-text available

Jul 2020

ISARIC (International Severe Acute Respiratory and emerging Infections Consortium) partnerships and outbreak preparedness initiatives enabled the rapid launch of standardised clinical data collection on COVID-19 in Jan 2020. Extensive global uptake of this resource has resulted in a large, standardised collection of comprehensive clinical data from hundreds of sites across dozens of countries. Data are analysed regularly and reported publicly to inform patient care and public health response. This report is a part of a series and includes the results of data analysis on 8 April 2021. We thank all of the data contributors for their ongoing support. Report highlights include Data have been entered for 340,312 individuals from 1609 sites across 54 countries. The analysis detailed in this report only includes individuals: for whom data collection commenced on or before 1 February 2021. AND who have laboratory-confirmed or clinically-diagnosed SARS-COV-2 infection. For the 264,496 cases who meet eligibility criteria for this report: The median age is 61 years. The five most common symptoms at admission were shortness of breath, cough, history of fever, fatigue/malaise, and altered consciousness/confusion. Children and older adults were less likely to display typical symptoms, and around 40% of patients >80 years experienced confusion. A total of 19% of patients were admitted at some point during their illness into an intensive care unit. Antibiotic use is high (79.9% of patients received antibiotics - the choice of antibiotic and specific indication have not yet been determined.) Altered consciousness/confusion was also relatively frequent (28,190/130,157) and most common in elderly patients. Overall, elderly patients are less likely to present with URTI symptoms. To access previous versions of ISARIC COVID-19 Clinical Data Report please use the link below: https://isaric.org/research/covid-19-clinical-research-resources/evidence-reports/

Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: Prospective observational cohort study

Article

Full-text available

May 2020
Br Med J

Objective To characterise the clinical features of patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United Kingdom during the growth phase of the first wave of this outbreak who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study, and to explore risk factors associated with mortality in hospital. Design Prospective observational cohort study with rapid data gathering and near real time analysis. Setting 208 acute care hospitals in England, Wales, and Scotland between 6 February and 19 April 2020. A case report form developed by ISARIC and WHO was used to collect clinical data. A minimal follow-up time of two weeks (to 3 May 2020) allowed most patients to complete their hospital admission. Participants 20 133 hospital inpatients with covid-19. Main outcome measures Admission to critical care (high dependency unit or intensive care unit) and mortality in hospital. Results The median age of patients admitted to hospital with covid-19, or with a diagnosis of covid-19 made in hospital, was 73 years (interquartile range 58-82, range 0-104). More men were admitted than women (men 60%, n=12 068; women 40%, n=8065). The median duration of symptoms before admission was 4 days (interquartile range 1-8). The commonest comorbidities were chronic cardiac disease (31%, 5469/17 702), uncomplicated diabetes (21%, 3650/17 599), non-asthmatic chronic pulmonary disease (18%, 3128/17 634), and chronic kidney disease (16%, 2830/17 506); 23% (4161/18 525) had no reported major comorbidity. Overall, 41% (8199/20 133) of patients were discharged alive, 26% (5165/20 133) died, and 34% (6769/20 133) continued to receive care at the reporting date. 17% (3001/18 183) required admission to high dependency or intensive care units; of these, 28% (826/3001) were discharged alive, 32% (958/3001) died, and 41% (1217/3001) continued to receive care at the reporting date. Of those receiving mechanical ventilation, 17% (276/1658) were discharged alive, 37% (618/1658) died, and 46% (764/1658) remained in hospital. Increasing age, male sex, and comorbidities including chronic cardiac disease, non-asthmatic chronic pulmonary disease, chronic kidney disease, liver disease and obesity were associated with higher mortality in hospital. Conclusions ISARIC WHO CCP-UK is a large prospective cohort study of patients in hospital with covid-19. The study continues to enrol at the time of this report. In study participants, mortality was high, independent risk factors were increasing age, male sex, and chronic comorbidity, including obesity. This study has shown the importance of pandemic preparedness and the need to maintain readiness to launch research studies in response to outbreaks. Study registration ISRCTN66726260.

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Article

Full-text available

Jan 2020

Background: A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods: All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings: By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0-58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0-13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation: The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding: Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.

Core Minimal Datasets to Advance Clinical Research for Priority Epidemic Diseases

Article

Full-text available

Aug 2019
CLIN INFECT DIS

The Ebola Virus Disease (EVD) outbreak in west Africa has prompted significant progress in responding to the clinical needs of patients affected by emerging infectious disease outbreaks. Amongst the noteworthy successes of vaccine trials, and the commendable efforts to implement clinical treatment trials during Ebola outbreaks, we should also focus on strengthening the collection and curation of epidemiological and observational data that can improve the conception and design of clinical research.

Global outbreak research: harmony not hegemony

Article

Jun 2020
LANCET INFECT DIS

Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study

Article

May 2020

Background Over 40 000 patients with COVID-19 have been hospitalised in New York City (NY, USA) as of April 28, 2020. Data on the epidemiology, clinical course, and outcomes of critically ill patients with COVID-19 in this setting are needed. Methods This prospective observational cohort study took place at two NewYork-Presbyterian hospitals affiliated with Columbia University Irving Medical Center in northern Manhattan. We prospectively identified adult patients (aged ≥18 years) admitted to both hospitals from March 2 to April 1, 2020, who were diagnosed with laboratory-confirmed COVID-19 and were critically ill with acute hypoxaemic respiratory failure, and collected clinical, biomarker, and treatment data. The primary outcome was the rate of in-hospital death. Secondary outcomes included frequency and duration of invasive mechanical ventilation, frequency of vasopressor use and renal replacement therapy, and time to in-hospital clinical deterioration following admission. The relation between clinical risk factors, biomarkers, and in-hospital mortality was modelled using Cox proportional hazards regression. Follow-up time was right-censored on April 28, 2020 so that each patient had at least 28 days of observation. Findings Between March 2 and April 1, 2020, 1150 adults were admitted to both hospitals with laboratory-confirmed COVID-19, of which 257 (22%) were critically ill. The median age of patients was 62 years (IQR 51–72), 171 (67%) were men. 212 (82%) patients had at least one chronic illness, the most common of which were hypertension (162 [63%]) and diabetes (92 [36%]). 119 (46%) patients had obesity. As of April 28, 2020, 101 (39%) patients had died and 94 (37%) remained hospitalised. 203 (79%) patients received invasive mechanical ventilation for a median of 18 days (IQR 9–28), 170 (66%) of 257 patients received vasopressors and 79 (31%) received renal replacement therapy. The median time to in-hospital deterioration was 3 days (IQR 1–6). In the multivariable Cox model, older age (adjusted hazard ratio [aHR] 1·31 [1·09–1·57] per 10-year increase), chronic cardiac disease (aHR 1·76 [1·08–2·86]), chronic pulmonary disease (aHR 2·94 [1·48–5·84]), higher concentrations of interleukin-6 (aHR 1·11 [95%CI 1·02–1·20] per decile increase), and higher concentrations of D-dimer (aHR 1·10 [1·01–1·19] per decile increase) were independently associated with in-hospital mortality. Interpretation Critical illness among patients hospitalised with COVID-19 in New York City is common and associated with a high frequency of invasive mechanical ventilation, extrapulmonary organ dysfunction, and substantial in-hospital mortality. Funding National Institute of Allergy and Infectious Diseases and the National Center for Advancing Translational Sciences, National Institutes of Health, and the Columbia University Irving Institute for Clinical and Translational Research.

Clinical and virological data of the first cases of COVID-19 in Europe: a case series

Article

Mar 2020
LANCET INFECT DIS

Background On Dec 31, 2019, China reported a cluster of cases of pneumonia in people at Wuhan, Hubei Province. The responsible pathogen is a novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We report the relevant features of the first cases in Europe of confirmed infection, named coronavirus disease 2019 (COVID-19), with the first patient diagnosed with the disease on Jan 24, 2020. Methods In this case series, we followed five patients admitted to Bichat-Claude Bernard University Hospital (Paris, France) and Pellegrin University Hospital (Bordeaux, France) and diagnosed with COVID-19 by semi-quantitative RT-PCR on nasopharyngeal swabs. We assessed patterns of clinical disease and viral load from different samples (nasopharyngeal and blood, urine, and stool samples), which were obtained once daily for 3 days from hospital admission, and once every 2 or 3 days until patient discharge. All samples were refrigerated and shipped to laboratories in the National Reference Center for Respiratory Viruses (The Institut Pasteur, Paris, and Hospices Civils de Lyon, Lyon, France), where RNA extraction, real-time RT-PCR, and virus isolation and titration procedures were done. Findings The patients were three men (aged 31 years, 48 years, and 80 years) and two women (aged 30 years and 46 years), all of Chinese origin, who had travelled to France from China around mid-January, 2020. Three different clinical evolutions are described: (1) two paucisymptomatic women diagnosed within a day of exhibiting symptoms, with high nasopharyngeal titres of SARS-CoV-2 within the first 24 h of the illness onset (5·2 and 7·4 log10 copies per 1000 cells, respectively) and viral RNA detection in stools; (2) a two-step disease progression in two young men, with a secondary worsening around 10 days after disease onset despite a decreasing viral load in nasopharyngeal samples; and (3) an 80-year-old man with a rapid evolution towards multiple organ failure and a persistent high viral load in lower and upper respiratory tract with systemic virus dissemination and virus detection in plasma. The 80-year-old patient died on day 14 of illness (Feb 14, 2020); all other patients had recovered and been discharged by Feb 19, 2020. Interpretation We illustrated three different clinical and biological types of evolution in five patients infected with SARS-CoV-2 with detailed and comprehensive viral sampling strategy. We believe that these findings will contribute to a better understanding of the natural history of the disease and will contribute to advances in the implementation of more efficient infection control strategies. Funding REACTing (Research & Action Emerging Infectious Diseases).

Open source clinical science for emerging infections

Article