Characteristics and outcomes of asthmatic patients with COVID-19 pneumonia who require hospitalisation.

BACKGROUND: Viral respiratory infections are the main causes of asthma exacerbation. The susceptibility of patients with asthma to develop an exacerbation when they present with severe pneumonia due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is unknown. The objective of this study was to investigate the characteristics and outcomes of asthmatic patients with coronavirus disease 2019 (COVID-19) pneumonia who required hospitalisation during the spring 2020 outbreak in Paris, France. METHODS: A prospective cohort follow-up was carried out from 15 March to 15 April 2020 in Bicêtre Hospital, University Paris-Saclay, France. All hospitalised patients with a SARS-CoV-2 infection who reported a history of asthma were included. RESULTS: Among 768 hospitalised patients, 37 (4.8%) reported a history of asthma, which had been previously confirmed by a pulmonologist in 85% of cases. These asthmatic patients were mainly female (70%) and nonsmokers (85%), with a median age of 54 years (interquartile range (IQR) 42-67 years). None of them presented with an asthma exacerbation. 22 (59%) had major comorbidities and 31 (84%) had a body mass index ≥25 kg·m-2. The most common comorbidities were obesity (36%), hypertension (27%) and diabetes (19%). All patients had a confirmed diagnosis of COVID-19 pneumonia on computed tomography of the chest. Eosinopenia was a typical biological feature with a median count of 0 cells·mm-3 (IQR 0-0 cells·mm-3). 11 patients (30%) were admitted into the intensive care unit, with three deaths (8.1%) occurring in the context of comorbidities. CONCLUSION: Asthma patients were not overrepresented among those with severe pneumonia due to SARS-CoV-2 infection who required hospitalisation. The worst outcomes were observed mainly in patients with major comorbidities.

Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions.

OBJECTIVE: To develop and validate a natural language processing (NLP) pipeline that detects 18 conditions in French clinical notes, including 16 comorbidities of the Charlson index, while exploring a collaborative and privacy-enhancing workflow. MATERIALS AND METHODS: The detection pipeline relied both on rule-based and machine learning algorithms, respectively, for named entity recognition and entity qualification, respectively. We used a large language model pre-trained on millions of clinical notes along with annotated clinical notes in the context of 3 cohort studies related to oncology, cardiology, and rheumatology. The overall workflow was conceived to foster collaboration between studies while respecting the privacy constraints of the data warehouse. We estimated the added values of the advanced technologies and of the collaborative setting. RESULTS: The pipeline reached macro-averaged F1-score positive predictive value, sensitivity, and specificity of 95.7 (95%CI 94.5-96.3), 95.4 (95%CI 94.0-96.3), 96.0 (95%CI 94.0-96.7), and 99.2 (95%CI 99.0-99.4), respectively. F1-scores were superior to those observed using alternative technologies or non-collaborative settings. The models were shared through a secured registry. CONCLUSIONS: We demonstrated that a community of investigators working on a common clinical data warehouse could efficiently and securely collaborate to develop, validate and use sensitive artificial intelligence models. In particular, we provided an efficient and robust NLP pipeline that detects conditions mentioned in clinical notes.

Setting the optimal threshold of NT-proBNP and BNP for the diagnosis of heart failure in patients over 75 years.

AIMS: Diagnosing acute heart failure (AHF) remains particularly challenging in older patients. Natriuretic peptides are recommended as valuable diagnostic tools in this context. This study aims to establish the diagnostic thresholds of B-type natriuretic peptide (BNP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) for AHF in patients aged over 75 years, both with and without co-morbidities. METHODS AND RESULTS: In this retrospective longitudinal multicentre cohort study, data were gathered from 12 071 hospitalized patients aged 75 years or older, presenting with acute dyspnoea and undergoing BNP or NT-proBNP measurement within 48 h of admission across 10 Assistance Publique-Hôpitaux de Paris facilities between 2011 and 2022, encompassing geriatrics, cardiology, and pulmonology departments. Final diagnoses were categorized using ICD-10 criteria as either AHF or other acute respiratory conditions such as COPD exacerbation, pulmonary embolism, and pneumonia. The mean (SD) age of the population was 84.0 (80.0, 89.0) years, with 52.7% being female. Out of these, 7946 (65.8%) were diagnosed with AHF upon discharge. For NT-proBNP, the identified 'optimal' threshold for diagnosing AHF was 1748 ng/L, with a positive predictive value (PPV) of 84%. Among patients aged over 85 years, a threshold of 2235 pg/mL for NT-proBNP was associated with an 84% PPV. In patients with atrial fibrillation (AF), a threshold of 2332 pg/mL for NT-proBNP demonstrated a PPV of 90% for AHF diagnosis. Additionally, in patients with an estimated glomerular filtration rate (eGFR) < 30 mL/min, a threshold of 3474 pg/mL for NT-proBNP yielded a 90% PPV for AHF diagnosis. In male patients, a threshold of 1800 pg/mL showed an 85% PPV for AHF diagnosis, while in patients with obesity, a threshold of 1375 pg/mL demonstrated an 85% PPV for AHF diagnosis. CONCLUSIONS: In older patients, we found significant effects of co-morbidities on natriuretic peptides results, particularly in patients over 85 years old, older patients with abnormal renal function, obesity, and atrial fibrillation. Despite the consideration of those co-morbid conditions, NT-proBNP and BNP level continue to demonstrate utility in the diagnosis of AHF in older patients.

How to Improve Cancer Patients ENrollment in Clinical Trials From rEal-Life Databases Using the Observational Medical Outcomes Partnership Oncology Extension: Results of the PENELOPE Initiative in Urologic Cancers.

PURPOSE: To compare the computability of Observational Medical Outcomes Partnership (OMOP)-based queries related to prescreening of patients using two versions of the OMOP common data model (CDM; v5.3 and v5.4) and to assess the performance of the Greater Paris University Hospital (APHP) prescreening tool. MATERIALS AND METHODS: We identified the prescreening information items being relevant for prescreening of patients with cancer. We randomly selected 15 academic and industry-sponsored urology phase I-IV clinical trials (CTs) launched at APHP between 2016 and 2021. The computability of the related prescreening criteria (PC) was defined by their translation rate in OMOP-compliant queries and by their execution rate on the APHP clinical data warehouse (CDW) containing data of 205,977 patients with cancer. The overall performance of the prescreening tool was assessed by the rate of true- and false-positive cases of three randomly selected CTs. RESULTS: We defined a list of 15 minimal information items being relevant for patients' prescreening. We identified 83 PC of the 534 eligibility criteria from the 15 CTs. We translated 33 and 62 PC in queries on the basis of OMOP CDM v5.3 and v5.4, respectively (translation rates of 40% and 75%, respectively). Of the 33 PC translated in the v5.3 of the OMOP CDM, 19 could be executed on the APHP CDW (execution rate of 58%). Of 83 PC, the computability rate on the APHP CDW reached 23%. On the basis of three CTs, we identified 17, 32, and 63 patients as being potentially eligible for inclusion in those CTs, resulting in positive predictive values of 53%, 41%, and 21%, respectively. CONCLUSION: We showed that PC could be formalized according to the OMOP CDM and that the oncology extension increased their translation rate through better representation of cancer natural history.

AP-HP Health Data Space (AHDS) to the Test of the Covid-19 Pandemic.

Sharing observational and interventional health data within a common data space enables university hospitals to leverage such data for biomedical discovery and moving towards a learning health system. OBJECTIVE: To describe the AP-HP Health Data Space (AHDS) and the IT services supporting piloting, research, innovation and patient care. METHODS: Built on three pillars - governance and ethics, technology and valorization - the AHDS and its major component, the Clinical Data Warehouse (CDW) have been developed since 2015. RESULTS: The AP-HP CDW has been made available at scale to AP-HP both healthcare professionals and public or private partners in January 2017. Supported by an institutional secured and high-performance cloud and an ecosystem of tools, mostly open source, the AHDS integrates a large amount of massive healthcare data collected during care and research activities. As of December 2021, the AHDS operates the electronic data capture for almost +840 clinical trials sponsored by AP-HP, the CDW is enabling the processing of health data from more than 11 million patients and generated +200 secondary data marts from IRB authorized research projects. During the Covid-19 pandemic, AHDS has had to evolve quickly to support administrative professionals and caregivers heavily involved in the reorganization of both patient care and biomedical research. CONCLUSION: The AP-HP Data Space is a key facilitator for data-driven evidence generation and making the health system more efficient and personalized.

Excess mortality and hospitalizations in transitional-age youths with a long-term disease: A national population-based cohort study.

INTRODUCTION: The number of adolescents with a severe chronic disease has increased in high-income countries due to improvements in the prognosis of childhood-onset chronic conditions. The transition from childhood to adulthood is a critical period that may be associated with increased mortality and morbidity. We aimed to estimate the prevalence of adolescents with a long-term disease (LTD) in France and assess their mortality and hospitalization risks relative to the general population. MATERIALS AND METHODS: We extracted a population-based cohort from the French national health insurance database that included 61,119 subjects who reached 14 years of age between 2005 and 2014. LTDs are diagnosed by patients' physicians and then confirmed and registered by a physician of the national health insurance system. We assessed mortality and hospitalizations using data of patients who were between 14 and 21 years-old. RESULTS: Among 14-year-old adolescents, 3.30% (95% confidence interval: 3.16-3.44) had a LTD. Their mortality rate between the ages of 14 and 21 years was 20.9/10,000 person-years (13.7-32.1) versus 1.9 (1.5-2.5) for adolescents without a LTD. Mortality was higher in males than females in youths without a LTD, but not in those with a LTD. We found a similar pattern for the risk of hospitalization for an external cause. The five-year probability of hospitalization was 61.8% among youths with a LTD versus 42.7% for those without. The rate of planned hospitalizations sharply fell at 19 years-of-age among youths with a LTD, whereas the rate of unplanned hospitalizations remained stable. CONCLUSION: The 3% of youths with a LTD have ten-fold higher mortality than those without and a high risk of hospitalization. The decrease in the rate of planned hospitalizations at age 19 among youths with a LTD may indicate differences in medical practice after transfer to adult care or a break in medical care.

Correction: Excess mortality and hospitalizations in transitional-age youths with a long-term disease: A national population-based cohort study.

[This corrects the article DOI: 10.1371/journal.pone.0193729.].

Montpellier Infectious Diseases (MID), 2nd annual meeting (2012).

For the second consecutive year, teams of the network "Montpellier Infectious Diseases" held their annual meeting. Whereas the 2011 meeting was focused on host-pathogen interaction and pathophysiology, the 2012 meeting was focused on the cooperation between medical and chemical sciences interdisciplinary approaches to fight against virus, bacteria and parasites. Several approaches aimed at designing new bioactive compounds were described during this meeting.

Subgroup II PAK-mediated phosphorylation regulates Ran activity during mitosis.

Ran is an essential GTPase that controls nucleocytoplasmic transport, mitosis, and nuclear envelope formation. These functions are regulated by interaction of Ran with different partners, and by formation of a Ran-GTP gradient emanating from chromatin. Here, we identify a novel level of Ran regulation. We show that Ran is a substrate for p21-activated kinase 4 (PAK4) and that its phosphorylation on serine-135 increases during mitosis. The endogenous phosphorylated Ran and active PAK4 dynamically associate with different components of the microtubule spindle during mitotic progression. A GDP-bound Ran phosphomimetic mutant cannot undergo RCC1-mediated GDP/GTP exchange and cannot induce microtubule asters in mitotic Xenopus egg extracts. Conversely, phosphorylation of GTP-bound Ran facilitates aster nucleation. Finally, phosphorylation of Ran on serine-135 impedes its binding to RCC1 and RanGAP1. Our study suggests that PAK4-mediated phosphorylation of GDP- or GTP-bound Ran regulates the assembly of Ran-dependent complexes on the mitotic spindle.