Different neurological manifestations of coronavirus disease 2019 (COVID-19) in adults and children and their impact have not been well characterized. We aimed to determine the prevalence of neurological manifestations and in-hospital complications among hospitalized COVID-19 patients and ascertain differences between adults and children. We conducted a prospective multicentre observational study using the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) cohort across 1507 sites worldwide from 30 January 2020 to 25 May 2021. Analyses of neurological manifestations and neurological complications considered unadjusted prevalence estimates for predefined patient subgroups, and adjusted estimates as a function of patient age and time of hospitalization using generalized linear models. Overall, 161 239 patients (158 267 adults; 2972 children) hospitalized with COVID-19 and assessed for neurological manifestations and complications were included. In adults and children, the most frequent neurological manifestations at admission were fatigue (adults: 37.4%; children: 20.4%), altered consciousness (20.9%; 6.8%), myalgia (16.9%; 7.6%), dysgeusia (7.4%; 1.9%), anosmia (6.0%; 2.2%) and seizure (1.1%; 5.2%). In adults, the most frequent in-hospital neurological complications were stroke (1.5%), seizure (1%) and CNS infection (0.2%). Each occurred more frequently in intensive care unit (ICU) than in non-ICU patients. In children, seizure was the only neurological complication to occur more frequently in ICU versus non-ICU (7.1% versus 2.3%, P < 0.001). Stroke prevalence increased with increasing age, while CNS infection and seizure steadily decreased with age. There was a dramatic decrease in stroke over time during the pandemic. Hypertension, chronic neurological disease and the use of extracorporeal membrane oxygenation were associated with increased risk of stroke. Altered consciousness was associated with CNS infection, seizure and stroke. All in-hospital neurological complications were associated with increased odds of death. The likelihood of death rose with increasing age, especially after 25 years of age. In conclusion, adults and children have different neurological manifestations and in-hospital complications associated with COVID-19. Stroke risk increased with increasing age, while CNS infection and seizure risk decreased with age.
Recent practice guidelines suggest applying non-invasive ventilation (NIV) to prevent postextubation respiratory failure in patients at high risk of extubation failure in intensive care unit (ICU). However, such prophylactic NIV has been only a conditional recommendation given the low certainty of evidence. Likewise, high-flow nasal cannula (HFNC) oxygen therapy has been shown to reduce reintubation rates as compared with standard oxygen and to be as efficient as NIV in patients at high risk. Whereas HFNC may be considered as an optimal therapy during the postextubation period, HFNC associated with NIV could be an additional means of preventing postextubation respiratory failure. We are hypothesising that treatment associating NIV with HFNC between NIV sessions may be more effective than HFNC alone and may reduce the reintubation rate in patients at high risk.This study is an investigator-initiated, multicentre randomised controlled trial comparing HFNC alone or with NIV sessions during the postextubation period in patients at high risk of extubation failure in the ICU. Six hundred patients will be randomised with a 1:1 ratio in two groups according to the strategy of oxygenation after extubation. The primary outcome is the reintubation rate within the 7 days following planned extubation. Secondary outcomes include the number of patients who meet the criteria for moderate/severe respiratory failure, ICU length of stay and mortality up to day 90.The study has been approved by the ethics committee and patients will be included after informed consent. The results will be submitted for publication in peer-reviewed journals.NCT03121482.
Abstract Background Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs). Methods This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support. Results A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI]; 5.86 [4.83–7.10]), treatment in an LMIC (OR [95%CI]; 2.04 [1.97–2.11]), and tachypnoea at hospital admission (OR [95%CI]; 1.16 [1.14–1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI]; 1.27 [1.25–1.30]). Conclusions In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable.
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.
Coronavirus disease-2019 (COVID-19) has devastated healthcare systems and public health globally [1].Many patients develop a wide spectrum of persisting or new symptoms 3 months after the acute COVID-19 illness (long-COVID-19), and these symptoms can persist for at least 2 months [2, 3].There is significant variability in the definitions with the lack of standardization and hence the reported frequency of long-COVID-19 also varies.Furthermore, there is sparser data with a significant heterogeneity on neurological long-COVID-19 symptoms [4].Neurological manifestations represent a possible presentation of long-COVID-19 [5][6][7].Data on the type of symptoms and prevalence of neurological long-COVID-19 are still in evolution [1,5].Hence, a clear understanding of neurological long-COVID-19 would aid healthcare systems in implementing health resources to measure and manage this global healthcare burden.Herein, in this study we aimed to characterize the type and prevalence of neurological symptoms related to neurological long-COVID-19 from a large international multicenter cohort of adults after discharge from hospital for acute COVID-19.This is an international, multicenter, prospective, observational cohort using the ISARIC WHO COVID-19 Clinical Characterization Protocol, approved by the WHO Ethics Committee (RPC571 and RPC572).Local Ethics approval was obtained from participating centers according to local regulatory rules as appropriate.Inclusion criteria were: patients ≥ 18 years-old; patients previously admitted to hospital with COVID-19; follow-up data available at least 1-month post-discharge from hospital or health center; person (or family member/next of kin for patients who lack capacity) consent to participate.The case report form (CRF) was completed as a patient self-assessment through an online link, telephone
Abstract Background The optimal treatment duration and the nature of regimen of antibiotics (monotherapy or combination therapy) for Pseudomonas aeruginosa ventilator‑associated pneumonia (PA-VAP) remain debated. The aim of this study was to evaluate whether a combination antibiotic therapy is superior to a monotherapy in patients with PA-VAP in terms of reduction in recurrence and death, based on the 186 patients included in the iDIAPASON trial, a multicenter, randomized controlled trial comparing 8 versus 15 days of antibiotic therapy for PA-VAP. Methods Patients with PA-VAP randomized in the iDIAPASON trial (short-duration—8 days vs. long-duration—15 days) and who received appropriate antibiotic therapy were eligible in the present study. The main objective is to compare mortality at day 90 according to the antibiotic therapy received by the patient: monotherapy versus combination therapy. The primary outcome was the mortality rate at day 90. The primary outcome was compared between groups using a Chi-square test. Time from appropriate antibiotic therapy to death in ICU or to censure at day 90 was represented using Kaplan–Meier survival curves and compared between groups using a Log-rank test. Results A total of 169 patients were included in the analysis. The median duration of appropriate antibiotic therapy was 14 days. At day 90, among 37 patients (21.9%) who died, 17 received monotherapy and 20 received a combination therapy ( P = 0.180). Monotherapy and combination antibiotic therapy were similar for the recurrence rate of VAP, the number of extra pulmonary infections, or the acquisition of multidrug-resistant (MDR) bacteria during the ICU stay. Patients in combination therapy were exposed to mechanical ventilation for 28 ± 12 days, as compared with 23 ± 11 days for those receiving monotherapy ( P = 0.0243). Results remain similar after adjustment for randomization arm of iDIAPASON trial and SOFA score at ICU admission. Conclusions Except longer durations of antibiotic therapy and mechanical ventilation, potentially related to increased difficulty in achieving clinical cure, the patients in the combination therapy group had similar outcomes to those in the monotherapy group. Trial registration : NCT02634411 , Registered 15 December 2015.
Early diagnosis of thrombotic thrombocytopenic purpura (TTP) versus hemolytic and uremic syndrome (HUS) is critical for the prompt initiation of specific therapies.To evaluate the diagnostic performance of the proteinuria/creatininuria ratio (PU/CU) for TTP versus HUS.In a retrospective study, in association with the "French Score" (FS) (platelets < 30 G/L and serum creatinine level < 200 µmol/L), we assessed PU/CU for the diagnosis of TTP in patients above the age of 15 with thrombotic microangiopathy (TMA). Patients with a history of kidney disease or with on-going cancer, allograft or pregnancy were excluded from the analysis.Between February 2011 and April 2019, we identified 124 TMA. Fifty-six TMA patients for whom PU/CU were available, including 35 TTP and 21 HUS cases, were considered. Using receiver-operating characteristic curves (ROC), those with a threshold of 1.5 g/g for the PU/CU had a 77% sensitivity (95% CI (63, 94)) and a 90% specificity (95% CI (71, 100)) for TTP diagnosis compared with those having an 80% sensitivity (95% CI (66, 92)) and a 90% specificity (95% CI (76, 100) with a FS of 2. In comparison, a composite score, defined as a FS of 2 or a PU/CU ≤ 1.5 g/g, improved sensitivity to 99.6% (95% CI (93, 100)) for TTP diagnosis and enabled us to reclassify seven false-negative TTP patients.The addition of urinary PU/CU upon admission of patients with TMA is a fast and readily available test that can aid in the differential diagnosis of TTP versus HUS alongside traditional scoring.
Research diversity and representativeness are paramount in building trust, generating valid biomedical knowledge, and possibly in implementing clinical guidelines.
By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients.
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