A Differential Therapeutic consideration for use of Corticosteroids according to Established COVID-19 Clinical Phenotypes in Critically ill Patients.

OBJECTIVE: To determine if the use of corticosteroids was associated with Intensive Care Unit (ICU) mortality among whole population and pre-specified clinical phenotypes. DESIGN: A secondary analysis derived from multicenter, observational studySetting: Critical Care UnitsPatients: Adult critically ill patients with confirmed COVID-19 disease admitted to 63 ICUs in Spain. INTERVENTIONS: corticosteroids vs no corticosteroidsMain variables of interest: Three phenotypes were derived by non-supervised clustering analysis from whole population and classified as (A: severe, B: critical and C: life-threatening). We performed a Multivariate analysis after propensity optimal full matching (PS) for whole population and weighted Cox regression (HR) and Fine-Gray analysis(sHR) to assess the impact of corticosteroids on ICU mortality according to the whole population and distinctive patient clinical phenotypes. RESULTS: A total of 2,017 patients were analyzed, 1171(58%) with corticosteroids. After PS, corticosteroids were shown not to be associated with ICU mortality (OR:1.0,95%CI:0.98-1.15). Corticosteroids were administered in 298/537(55.5%) patients of "A" phenotype and their use was not associated with ICU mortality (HR=0.85[0.55-1.33]). A total of 338/623(54.2%) patients in "B" phenotype received corticosteroids. No effect of corticosteroids on ICU mortality was observed when HR was performed (0.72[0.49-1.05]). Finally, 535/857(62.4%) patients in "C" phenotype received corticosteroids. In this phenotype HR (0.75[0.58-0.98]) and sHR (0.79[0.63-0.98]) suggest a protective effect of corticosteroids on ICU mortality. CONCLUSION: Our finding warns against the widespread use of corticosteroids in all critically ill patients with COVID-19 at moderate dose. Only patients with the highest inflammatory levels could benefit from steroid treatment.

Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis.

BACKGROUND: Identification of clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment. However, previous attempts did not take into account temporal dynamics with high granularity. By including the dimension of time, we aim to gain further insights into the heterogeneity of COVID-19. METHODS: We used granular data from 3202 adult COVID patients in the Dutch Data Warehouse that were admitted to one of 25 Dutch ICUs between February 2020 and March 2021. Parameters including demographics, clinical observations, medications, laboratory values, vital signs, and data from life support devices were selected. Twenty-one datasets were created that each covered 24 h of ICU data for each day of ICU treatment. Clinical phenotypes in each dataset were identified by performing cluster analyses. Both evolution of the clinical phenotypes over time and patient allocation to these clusters over time were tracked. RESULTS: The final patient cohort consisted of 2438 COVID-19 patients with a ICU mortality outcome. Forty-one parameters were chosen for cluster analysis. On admission, both a mild and a severe clinical phenotype were found. After day 4, the severe phenotype split into an intermediate and a severe phenotype for 11 consecutive days. Heterogeneity between phenotypes appears to be driven by inflammation and dead space ventilation. During the 21-day period, only 8.2% and 4.6% of patients in the initial mild and severe clusters remained assigned to the same phenotype respectively. The clinical phenotype half-life was between 5 and 6 days for the mild and severe phenotypes, and about 3 days for the medium severe phenotype. CONCLUSIONS: Patients typically do not remain in the same cluster throughout intensive care treatment. This may have important implications for prognostic or predictive enrichment. Prominent dissimilarities between clinical phenotypes are predominantly driven by inflammation and dead space ventilation.

Heterogeneity of Ventilation/Perfusion Mismatch at Different Levels of PEEP and in Mechanical Phenotypes of COVID-19 ARDS.

BACKGROUND: COVID-19-related ARDS is characterized by severe hypoxemia with initially preserved lung compliance and impaired ventilation/perfusion (V̇/Q̇) matching. PEEP can increase end-expiratory lung volume, but its effect on V̇/Q̇ mismatch in COVID-19-related ARDS is not clear. METHODS: We enrolled intubated and mechanically ventilated subjects with COVID-19 ARDS and used the automatic lung parameter estimator (ALPE) to measure V̇/Q̇. Respiratory mechanics measurements, shunt, and V̇/Q̇ mismatch (low V̇/Q̇ and high V̇/Q̇) were collected at 3 PEEP levels (clinical PEEP = intermediate PEEP, low PEEP [clinical - 50%], and high PEEP [clinical + 50%]). A mixed-effect model was used to evaluate the impact of PEEP on V̇/Q̇. We also investigated if PEEP might have a different effect on V̇/Q̇ mismatch in 2 different respiratory mechanics phenotypes, that is, high elastance/low compliance (phenotype H) and low elastance/high compliance (phenotype L). RESULTS: Seventeen subjects with COVID-related ARDS age 66 [60-71] y with a PaO2 /FIO2 of 141 ± 74 mm Hg were studied at low PEEP = 5.6 ± 2.2 cm H2O, intermediate PEEP = 10.6 ± 3.8 cm H2O, and high PEEP = 15 ± 5 cm H2O. Shunt, low V̇/Q̇, high V̇/Q̇, and alveolar dead space were not significantly influenced, on average, by PEEP. Respiratory system compliance decreased significantly when increasing PEEP without significant variation of PaO2 /FIO2 (P = .26). In the 2 phenotypes, PEEP had opposite effects on shunt, with a decrease in the phenotype L and an increase in phenotype H (P = .048). CONCLUSIONS: In subjects with COVID-related ARDS placed on invasive mechanical ventilation for > 48 h, PEEP had a heterogeneous effect on V̇/Q̇ mismatch and, on average, higher levels were not able to reduce shunt. The subject's compliance could influence the effect of PEEP on V̇/Q̇ mismatch since an increased shunt was observed in subjects with lower compliance, whereas the opposite occurred in those with higher compliance.

An update on anaphylaxis and urticaria.

Notable scientific developments have taken place in the field of anaphylaxis and urticaria in recent years; they are highlighted in this review. Case-control studies, genome-wide association studies, and large omics analyses have promoted further insights into not only the underlying genetics but also the biomarkers of both anaphylaxis and urticaria. New evidence regarding IgE-dependent and non-IgE-dependent mechanisms of anaphylaxis and urticaria, including the Mas-related G protein-coupled receptor (MRGPR [formerly MRG]) signaling pathway, has been gained. Putative elicitors of anaphylactic reactions in the context of coronavirus disease 2019 (COVID-19) vaccination and impact of the COVID-19 pandemic on the management and course of chronic urticaria have been reported. Clinical progress has also been made regarding the severity grading and risk factors of anaphylaxis, as well as the distinction of phenotypes and elicitors of both diseases. Furthermore, novel treatment approaches for anaphylaxis and subtypes of urticaria have been assessed, with different outcome and potential for a better disease control or prevention.

Radiotherapy in COVID-19: a review

The World Health Organization (WHO) stated the novel coronavirus (COVID-19) a global pandemic on 11th March 2020. The virus-infected patients suffered from a respiratory disease called Severe Acute Respiratory Syndrome Coronavirus 2 (SAR-CoV-2). A proteinaceous exudate, alveolar edema, and hyperplasia associated with monocytes and lymphocytes alveolar inflammatory infiltration was observed in the affected patient's lungs. Virus broadens a systemic inflammatory reaction with a cytokine release syndrome which is characterized with the aid of using unexpected growth in many pro-inflammatory cytokines especially IL-6, IL-1, and TNF-a through activated M1 macrophage phenotype. Virus block IL-6 with tocilizumab and the usage of respirator device appears to be very vital. Radioactivity is the process by which unstable atomic nucleus losses energy by radiation, mainly using alpha, beta, and gamma rays. SARS-CoV-2 affected lungs can be treated by a low dose of radiotherapy. It was found that minute dose chest radiation therapy can be able to wean patients off a ventilator as it can reduce inflammation inside the lungs of severely infected COVID-19 patients. Numerous such clinical trials are underway and researchers may work to cure the COVID-19 lung infections by radiotherapy.

Latent class analysis of imaging and clinical respiratory parameters from patients with COVID-19-related ARDS identifies recruitment subphenotypes.

BACKGROUND: Patients with COVID-19-related acute respiratory distress syndrome (ARDS) require respiratory support with invasive mechanical ventilation and show varying responses to recruitment manoeuvres. In patients with ARDS not related to COVID-19, two pulmonary subphenotypes that differed in recruitability were identified using latent class analysis (LCA) of imaging and clinical respiratory parameters. We aimed to evaluate if similar subphenotypes are present in patients with COVID-19-related ARDS. METHODS: This is the retrospective analysis of mechanically ventilated patients with COVID-19-related ARDS who underwent CT scans at positive end-expiratory pressure of 10 cmH2O and after a recruitment manoeuvre at 20 cmH2O. LCA was applied to quantitative CT-derived parameters, clinical respiratory parameters, blood gas analysis and routine laboratory values before recruitment to identify subphenotypes. RESULTS: 99 patients were included. Using 12 variables, a two-class LCA model was identified as best fitting. Subphenotype 2 (recruitable) was characterized by a lower PaO2/FiO2, lower normally aerated lung volume and lower compliance as opposed to a higher non-aerated lung mass and higher mechanical power when compared to subphenotype 1 (non-recruitable). Patients with subphenotype 2 had more decrease in non-aerated lung mass in response to a standardized recruitment manoeuvre (p = 0.024) and were mechanically ventilated longer until successful extubation (adjusted SHR 0.46, 95% CI 0.23-0.91, p = 0.026), while no difference in survival was found (p = 0.814). CONCLUSIONS: A recruitable and non-recruitable subphenotype were identified in patients with COVID-19-related ARDS. These findings are in line with previous studies in non-COVID-19-related ARDS and suggest that a combination of imaging and clinical respiratory parameters could facilitate the identification of recruitable lungs before the manoeuvre.

Do Blood Phenotypes of Feline AB Blood Group System Affect the SARS-CoV-2 Antibody Serostatus in Cats?

Cats are susceptible to coronavirus infections, including infection by human severe acute respiratory syndrome coronavirus (SARS-CoV). In human ABO system blood groups, alloantibodies can play a direct role in resistance to infectious diseases. Individuals with the AB blood type were over-represented in the SARS-CoV-2 infection group. Blood type AB individuals lack both anti-A and anti-B antibodies, and therefore lack the protective effect against SARS-CoV-2 infection given by these antibodies. Starting from this knowledge, this pilot preliminary study evaluated a possible association between feline blood phenotypes A, B, and AB and serostatus for SARS-CoV-2 antibodies in cats. We also investigated selected risk or protective factors associated with seropositivity for this coronavirus. A feline population of 215 cats was analysed for AB group system blood phenotypes and antibodies against the nucleocapsid (N-protein) SARS-CoV-2 antigen using a double antigen ELISA. SARS-CoV-2 seropositive samples were confirmed using a surrogate virus neutralization test (sVNT). Origin (stray colony/shelter/owned cat), breed (DSH/non DSH), gender (male/female), reproductive status (neutered/intact), age class (kitten/young adult/mature adult/senior), retroviruses status (seropositive/seronegative), and blood phenotype (A, B, and AB) were evaluated as protective or risk factors for SARS-CoV-2 seropositivity. Seropositivity for antibodies against the SARS-CoV-2 N-protein was recorded in eight cats, but only four of these tested positive with sVNT. Of these four SARS-CoV-2 seropositive cats, three were blood phenotype A and one was phenotype AB. Young adult age (1-6 years), FeLV seropositivity and blood type AB were significantly associated with SARS-CoV-2 seropositivity according to a univariate analysis, but only blood type AB (p = 0.0344, OR = 15.4, 95%CI: 1.22-194.39) and FeLV seropositivity (p = 0.0444, OR = 13.2, 95%CI: 1.06-163.63) were significant associated risk factors according to a logistic regression. Blood phenotype AB might be associated with seropositivity for SARS-CoV-2 antibodies. This could be due, as in people, to the protective effect of naturally occurring alloantibodies to blood type antigens which are lacking in type AB cats. The results of this pilot study should be considered very preliminary, and we suggest the need for further research to assess this potential relationship.

A differential therapeutic consideration for use of corticosteroids according to established COVID-19 clinical phenotypes in critically ill patients.

OBJECTIVE: To determine if the use of corticosteroids was associated with Intensive Care Unit (ICU) mortality among whole population and pre-specified clinical phenotypes. DESIGN: A secondary analysis derived from multicenter, observational study. SETTING: Critical Care Units. PATIENTS: Adult critically ill patients with confirmed COVID-19 disease admitted to 63 ICUs in Spain. INTERVENTIONS: Corticosteroids vs. no corticosteroids. MAIN VARIABLES OF INTEREST: Three phenotypes were derived by non-supervised clustering analysis from whole population and classified as (A: severe, B: critical and C: life-threatening). We performed a multivariate analysis after propensity optimal full matching (PS) for whole population and weighted Cox regression (HR) and Fine-Gray analysis (sHR) to assess the impact of corticosteroids on ICU mortality according to the whole population and distinctive patient clinical phenotypes. RESULTS: A total of 2017 patients were analyzed, 1171 (58%) with corticosteroids. After PS, corticosteroids were shown not to be associated with ICU mortality (OR: 1.0; 95% CI: 0.98-1.15). Corticosteroids were administered in 298/537 (55.5%) patients of "A" phenotype and their use was not associated with ICU mortality (HR=0.85 [0.55-1.33]). A total of 338/623 (54.2%) patients in "B" phenotype received corticosteroids. No effect of corticosteroids on ICU mortality was observed when HR was performed (0.72 [0.49-1.05]). Finally, 535/857 (62.4%) patients in "C" phenotype received corticosteroids. In this phenotype HR (0.75 [0.58-0.98]) and sHR (0.79 [0.63-0.98]) suggest a protective effect of corticosteroids on ICU mortality. CONCLUSION: Our finding warns against the widespread use of corticosteroids in all critically ill patients with COVID-19 at moderate dose. Only patients with the highest inflammatory levels could benefit from steroid treatment.

COVID-19 Pneumonia Phenotypes Detection with Electrical Impedance Tomography

It was reported that COVID-19 induced acute respiratory distress syndrome (ARDS) comes at least in two different phenotypes. Different responses and outcomes to typical positive end-expiration pressure (PEEP) trial are found in those different phenotypes. Lung recruitability during a PEEP trial can be used to identify different phenotypes to help improve the patient outcome. In this study, we analysed overdistention and collapse ratio with electrical impedance tomography (EIT) monitoring data on four severe COVID-19 pneumonia patients to identify their phenotypes. Results demonstrate the different patient responses to a PEEP trial, and showed the developing change in patient status over time. In one patient a possible phenotype transition was identified. We suggest that EIT may be a practical tool to identify phenotypes and to provide information about COVID-19 pneumonia progression. © 2022 The Author(s), published by De Gruyter.

VAC4EU: A Pan-European Research Network for Collaborative Post-authorization Vaccine Safety and Benefit Monitoring: An International Journal of Medical Toxicology and Drug Experience

Introduction: VAC4EU (Vaccine monitoring Collaboration for Europe) is a not-for profit international association with 24 member organizations specialised in the collaborative generation of real-world evidence on coverage, safety, and efficacy of vaccines in Europe. VAC4EU was established as a result of the IMI-ADVANCE project with the aim to enable, coordinate and accelerate the creation of the best evidence at European level on vaccine effects. In the past two years, VAC4EU has proven preparedness and efficiency in designing post-authorization monitoring for COVID-19 vaccines responding to the requests of both the European Medicines Agency (EMA) and vaccine manufacturers Objective: To describe the VAC4EU organization, data, tools and the accomplishments made towards the generation of real-world evidence on vaccine benefit-risk evaluation. Methods: Not applicable. Results: Since its creation in October 2019, VAC4EU has established a large research network composed of 24 institutions from 9 European countries (BE, DE, DK, FR, IT, NL, NO, ES, UK) providing access to different health care data sources covering more than 150 million European citizens. VAC4EU has implemented a research infrastructure including a catalogue, a codemapper tool, a sharepoint, Github, digital research environment (DRE), a phenotype library of more than 100 variables with definitions and a Zenodo community to facilitate collaboration, transparency, and federated data analysis. VAC4EU has adopted the ConcePTION common data model as a basis for the structural harmonization of electronic health data, but it also allows for primary data collection. VAC4EU has consolidated its governance structure for implementation of pharmacovigilance studies on vaccines and successfully participated in four public tenders regarding vaccines safety and effectiveness launched by the European Medicines Agency (EMA) [1-3] as well as four required post-authorization safety studies on COVID-19 vaccines sponsored by vaccine manufacturers [4-8], and other studies promoted by the Global Vaccine Data Network. All protocols developed within VAC4EU are registered in the EU PAS register, and results are published in the open science VAC4EU Zenodo community. Conclusion: We know already from the H1N1 pandemic that collaboration is needed to study vaccine effects. This collaboration was designed and tested in the IMI-ADVANCE project and implemented in VAC4EU. VAC4EU has demonstrated readiness of its research framework making a key difference in COVID-19 vaccine monitoring in Europe. Research and public health organizations can join the initiative.

Oral-Systemic Health and Disorders: Latest Advances on Oral–Gut–Lung Microbiome Axis

In particular, the bi-directional communication network, also known as the gut lung axis connecting the intestinal and pulmonary microbiota, is considered responsible for the massively increased bacterial load in the cecum after acute lung injury, causing alterations in airway microbiota and its transitory translocation into the bloodstream toward the bowel [7,8]. [...]subjects with chronic obstructive pulmonary disease often show intestinal hyper-permeability and a high prevalence of IBD [9]. Both mechanisms would underlie the association between periodontitis and inflammatory and degenerative diseases, such as atherosclerosis, Alzheimer’s disease, age-related macular degeneration [22], chronic inflammatory bowel disease [23], and solid neoplasms, such as colorectal carcinoma [24]. [...]intestinal microbes could, due to mucosal barrier impairment, translocate to the liver through the biliary tract and the portal vein, and oral dysbiosis could exacerbate chronic liver diseases, likely modulating the gut ecosystem through the oral–gut axis, on the one side, and may reflect the intestinal dysbiotic ecosystem, affected in turn by hepatic diseases, on the other side [12,25]. Furthermore, mainly the upper but also the lower airways of healthy individuals frequently harbor oral anaerobes, including Prevotella and Veillonella species, probably secondary to continuing microaspiration by contiguity. [...]detecting oral bacterial DNA in the lower airways in healthy subjects could represent the traces of aspirated oral bacteria either not eliminated through physiological clearance or living in dynamic equilibrium with host defensive responses by promoting mucosal immunity of the Th17/neutrophilic phenotype and suppressing innate immunity. Whether bacteria from the oral microbiome regulate responses to pulmonary pathogens and whether they interfere in inflammatory lung disease pathogenesis [26] is still under study. [...]a growing body of evidence highlights that gut and oral dysbioses, interconnected with the local microbial and inflammatory environment of the lung, liver, and other organs, are crucially implied in a multitude of diseases also involving distant organs.

Timely and ethical access to genetic investigations on the neonatal unit: a collaboration between Leeds Centre for Newborn Care and The Yorkshire Regional Genetics Service

AimsGenomic testing is often important in the management of neonates in tertiary care. Tests need to be timely, and families need to be adequately counselled to allow informed decision making. Both teams identified several interventions to improve genetics management on the neonatal unit, particularly in response to the Covid pandemic.Our objectives were to improve current practices by focussing on two areas:1. Access to genetics expertise, with an emphasis on virtual working2. Current practices surrounding consent for genetic investigationsMethodsIn response to the Covid pandemic a Neonatal-Genetics virtual MDT was implemented in September 2020. Data was retrospectively collected from the medical notes of all neonates referred to genetics during a fifteen-month period (December 2019-March 2021) to allow for comparison of data before and after this intervention. Data was collected on consent documentation for genetic tests (QF-PCR, microarray) in the neonatal unit. As consent documentation appeared sparse, a survey was disseminated to all clinicians on the unit in February 2021 to assess knowledge of genomic testing and consent-taking. An email survey was sent to 6 neonatal units in Yorkshire and the Humber in August 2021 to explore regional variations in consent processes.ResultsThere was an increase in referral rate from 1.5% to 2.3% after MDT introduction but a 33% reduction in the proportion of babies requiring in-person geneticist reviews. Anecdotally, the MDT was considered a positive change by both teams by facilitating continued communication. Only 11% of neonates (n=2 of 17) had adequate consent documentation for genomic tests by the neonatal team. Of 27 respondents of the staff survey, only 2 (7%) had received formal training in consent for genomic tests and only 22% (n=6 out of 27) felt confident in consenting and explaining genetic testing to parents. All (100%) respondents felt a teaching session on genomic testing would be helpful, and all respondents agreed that it would be beneficial to develop a guideline to aid the consent process. None of the regional neonatal units contacted had a formal education program or standardised guideline in place. In response to this, a teaching programme was devised and a checklist created to facilitate the consent process for genetic testing. The teaching sessions were well-received, attendees scored the sessions an average of 4.8 out of 5 (n=19 respondents) for overall usefulness and quality.ConclusionIntroducing an MDT allowed for streamlined working during the pandemic and facilitated ongoing discussions of neonates with evolving phenotypes, whilst reducing the burden of inpatient reviews for a busy regional genetics service. Our data identified a paucity of genetic test consent documentation and our survey suggested that staff training and confidence around genomic testing/consent was a contributing factor. Therefore, an educational package for clinicians was developed. This was well-received, and a checklist was created to simplify and standardise documentation. A repeat analysis will be undertaken this year to assess the efficacy of these interventions. The intention is to expand the education package and consent checklist to units within our region and beyond.

Silent Hypoxemia in the Emergency Department: A Retrospective Cohort of Two Clinical Phenotypes in Critical COVID-19.

INTRODUCTION: Understanding hypoxemia, with and without the clinical signs of acute respiratory failure (ARF) in COVID-19, is key for management. Hence, from a population of critical patients admitted to the emergency department (ED), we aimed to study silent hypoxemia (Phenotype I) in comparison to symptomatic hypoxemia with clinical signs of ARF (Phenotype II). METHODS: This multicenter study was conducted between 1 March and 30 April 2020. Adult patients who were presented to the EDs of nine Great-Eastern French hospitals for confirmed severe or critical COVID-19, who were then directly admitted to the intensive care unit (ICU), were retrospectively included. RESULTS: A total of 423 critical COVID-19 patients were included, out of whom 56.1% presented symptomatic hypoxemia with clinical signs of ARF, whereas 43.9% presented silent hypoxemia. Patients with clinical phenotype II were primarily intubated, initially, in the ED (46%, p < 0.001), whereas those with silent hypoxemia (56.5%, p < 0.001) were primarily intubated in the ICU. Initial univariate analysis revealed higher ICU mortality (29.2% versus 18.8%, p < 0.014) and in-hospital mortality (32.5% versus 18.8%, p < 0.002) in phenotype II. However, multivariate analysis showed no significant differences between the two phenotypes regarding mortality and hospital or ICU length of stay. CONCLUSIONS: Silent hypoxemia is explained by various mechanisms, most physiological and unspecific to COVID-19. Survival was found to be comparable in both phenotypes, with decreased survival in favor of Phenotype II. However, the spectrum of silent to symptomatic hypoxemia appears to include a continuum of disease progression, which can brutally evolve into fatal ARF.

Evaluation of Association between Blood Phenotypes A, B and AB and Feline Coronavirus Infection in Cats.

Cats are susceptible to feline coronavirus (FCoV), a highly contagious virus with fecal-oral transmission. In people, susceptibility to coronavirus infection, such as SARS-CoV infection, has been associated with the ABO blood group, with individuals with blood group O having significantly lower risk of SARS-CoV infection. This study evaluated a possible association between feline blood group phenotypes A, B and AB and serostatus for antibodies against FCoV. We also investigated risk or protective factors associated with seropositivity for FCoV in the investigated population. Feline populations were surveyed for AB group system blood types and for presence of antibodies against FCoV. Blood phenotype, origin, breed, gender, reproductive status and age of cats were evaluated as protective or risk factors for coronavirus infection. No blood type was associated with FCoV seropositivity, for which being a colony stray cat (p = 0.0002, OR = 0.2, 95% CI: 0.14-0.54) or a domestic shorthair cat (p = 0.0075, OR = 0.2, 95% CI = 0.09-0.69) were protective factors. Based on results of this study, feline blood phenotypes A, B or AB do not seem to predispose cats to seropositivity for FCoV. Future studies on other feline blood types and other infections could clarify whether feline blood types could play a role in predisposing to, or protecting against, feline infections.

Treatment for acute respiratory distress syndrome in adults: a narrative review of phase 2 and 3 trials.

INTRODUCTION: Ventilatory management and general supportive care of acute respiratory distress syndrome (ARDS) in the adult population have led to significant clinical improvements, but morbidity and mortality remain high. Pharmacologic strategies acting on the coagulation cascade, inflammation, oxidative stress, and endothelial cell injury have been targeted in the last decade for patients with ARDS, but only a few of these have shown potential benefits with a meaningful clinical response and improved patient outcomes. The lack of availability of specific pharmacologic treatments for ARDS can be attributed to its complex pathophysiology, different risk factors, huge heterogeneity, and difficult classification into specific biological phenotypes and genotypes. AREAS COVERED: In this narrative review, we briefly discuss the relevance and current advances in pharmacologic treatments for ARDS in adults and the need for the development of new pharmacological strategies. EXPERT OPINION: Identification of ARDS phenotypes, risk factors, heterogeneity, and pathophysiology may help to design clinical trials personalized according to ARDS-specific features, thus hopefully decreasing the rate of failed clinical pharmacologic trials. This concept is still under clinical investigation and needs further development.

Clinical sepsis phenotypes in critically ill COVID-19 patients.

BACKGROUND: A greater understanding of disease heterogeneity may facilitate precision medicine for coronavirus disease 2019 (COVID-19). Previous work identified four distinct clinical phenotypes associated with outcome and treatment responses in non-COVID-19 sepsis patients, but it is unknown if and how these phenotypes are recapitulated in COVID-19 sepsis patients. METHODS: We applied the four non-COVID-19 sepsis phenotypes to a total of 52,274 critically ill patients, comprising two cohorts of COVID-19 sepsis patients (admitted before and after the introduction of dexamethasone as standard treatment) and three non-COVID-19 sepsis cohorts (non-COVID-19 viral pneumonia sepsis, bacterial pneumonia sepsis, and bacterial sepsis of non-pulmonary origin). Differences in proportions of phenotypes and their associated mortality were determined across these cohorts. RESULTS: Phenotype distribution was highly similar between COVID-19 and non-COVID-19 viral pneumonia sepsis cohorts, whereas the proportion of patients with the δ-phenotype was greater in both bacterial sepsis cohorts compared to the viral sepsis cohorts. The introduction of dexamethasone treatment was associated with an increased proportion of patients with the δ-phenotype (6% vs. 11% in the pre- and post-dexamethasone COVID-19 cohorts, respectively, p < 0.001). Across the cohorts, the α-phenotype was associated with the most favorable outcome, while the δ-phenotype was associated with the highest mortality. Survival of the δ-phenotype was markedly higher following the introduction of dexamethasone (60% vs 41%, p < 0.001), whereas no relevant differences in survival were observed for the other phenotypes among COVID-19 patients. CONCLUSIONS: Classification of critically ill COVID-19 patients into clinical phenotypes may aid prognostication, prediction of treatment efficacy, and facilitation of personalized medicine.

CYP2D6 phenotypes and opioid metabolism: the path to personalized analgesia.

INTRODUCTION: Opioids play a fundamental role in chronic pain, especially considering when 1 of 5 Europeans adults, even more in older females, suffer from it. However, half of them do not reach an adequate pain relief. Could pharmacogenomics help to choose the most appropriate analgesic drug? AREAS COVERED: The objective of the present narrative review was to assess the influence of cytochrome P450 2D6 (CYP2D6) phenotypes on pain relief, analgesic tolerability, and potential opioid misuse. Until December 2021, a literature search was conducted through the MEDLINE, PubMed database, including papers from the last 10 years. CYP2D6 plays a major role in metabolism that directly impacts on opioid (tramadol, codeine, or oxycodone) concentration with differences between sexes, with a female trend toward poorer pain control. In fact, CYP2D6 gene variants are the most actionable to be translated into clinical practice according to regulatory drug agencies and international guidelines. EXPERT OPINION: CYP2D6 genotype can influence opioids' pharmacokinetics, effectiveness, side effects, and average opioid dose. This knowledge needs to be incorporated in pain management. Environmental factors, psychological together with genetic factors, under a sex perspective, must be considered when you are selecting the most personalized pain therapy for your patients.

Clinical Phenotypes and Mortality Biomarkers: A Study Focused on COVID-19 Patients with Neurological Diseases in Intensive Care Units.

Purpose: To identify clinical phenotypes and biomarkers for best mortality prediction considering age, symptoms and comorbidities in COVID-19 patients with chronic neurological diseases in intensive care units (ICUs). Subjects and Methods: Data included 1252 COVID-19 patients admitted to ICUs in Cuba between January and August 2021. A k-means algorithm based on unsupervised learning was used to identify clinical patterns related to symptoms, comorbidities and age. The Stable Sparse Classifiers procedure (SSC) was employed for predicting mortality. The classification performance was assessed using the area under the receiver operating curve (AUC). Results: Six phenotypes using a modified v-fold cross validation for the k-means algorithm were identified: phenotype class 1, mean age 72.3 years (ys)-hypertension and coronary artery disease, alongside typical COVID-19 symptoms; class 2, mean age 63 ys-asthma, cough and fever; class 3, mean age 74.5 ys-hypertension, diabetes and cough; class 4, mean age 67.8 ys-hypertension and no symptoms; class 5, mean age 53 ys-cough and no comorbidities; class 6, mean age 60 ys-without symptoms or comorbidities. The chronic neurological disease (CND) percentage was distributed in the six phenotypes, predominantly in phenotypes of classes 3 (24.72%) and 4 (35,39%); χ² (5) 11.0129 p = 0.051134. The cerebrovascular disease was concentrated in classes 3 and 4; χ² (5) = 36.63, p = 0.000001. The mortality rate totaled 325 (25.79%), of which 56 (17.23%) had chronic neurological diseases. The highest in-hospital mortality rates were found in phenotypes 1 (37.22%) and 3 (33.98%). The SSC revealed that a neurological symptom (ageusia), together with two neurological diseases (cerebrovascular disease and Parkinson's disease), and in addition to ICU days, age and specific symptoms (fever, cough, dyspnea and chilliness) as well as particular comorbidities (hypertension, diabetes and asthma) indicated the best prediction performance (AUC = 0.67). Conclusions: The identification of clinical phenotypes and mortality biomarkers using practical variables and robust statistical methodologies make several noteworthy contributions to basic and experimental investigations for distinguishing the COVID-19 clinical spectrum and predicting mortality.

A Process Mining Pipeline to Characterize COVID-19 Patients' Trajectories and Identify Relevant Temporal Phenotypes From EHR Data.

The impact of the COVID-19 pandemic involved the disruption of the processes of care and the need for immediately effective re-organizational procedures. In the context of digital health, it is of paramount importance to determine how a specific patients' population reflects into the healthcare dynamics of the hospital, to investigate how patients' sub-group/strata respond to the different care processes, in order to generate novel hypotheses regarding the most effective healthcare strategies. We present an analysis pipeline based on the heterogeneous collected data aimed at identifying the most frequent healthcare processes patterns, jointly analyzing them with demographic and physiological disease trajectories, and stratify the observed cohort on the basis of the mined patterns. This is a process-oriented pipeline which integrates process mining algorithms, and trajectory mining by topological data analyses and pseudo time approaches. Data was collected for 1,179 COVID-19 positive patients, hospitalized at the Italian Hospital "Istituti Clinici Salvatore Maugeri" in Lombardy, integrating different sources including text admission letters, EHR and hospital infrastructure data. We identified five temporal phenotypes, from laboratory values trajectories, which are characterized by statistically significant different death risk estimates. The process mining algorithms allowed splitting the data in sub-cohorts as function of the pandemic waves and of the temporal trajectories showing statistically significant differences in terms of events characteristics.

Distinct Phenotypes of Multiorgan Abnormalities in Long COVID and Type 2 Diabetes Identified by Multiparametric Magnetic Resonance Imaging

Introduction: Both long COVID and Type 2 Diabetes (T2D) are multi-system conditions requiring multi-organ assessment to monitor organ health and detect co-morbidities earlier. Here, we defined multi-organ abnormalities in both patient groups with a rapid, non-contrast MRI scan. Methods: We recruited 135 long COVID patients (NCT04369807) and 135 T2D patients (NCT04114682) . MRI data were acquired for organ-specific measures of size, fat deposition and fibroinflammation (CoverScan®, Perspectum Ltd.) . Reference values were based on 92 controls and published literature. Results: There was a high prevalence of organ abnormality in both patient groups (Figure, left) , including increased fat deposition (steatosis) in liver, pancreas, and kidney (Figure, right) . 35% of T2D patients had clustering of abnormalities involving at least 2 organs, compared to 23% in long COVID. Abnormalities affecting the liver and renomegaly were more common in T2D than in long COVID. Considering only obese patients, liver fibroinflammation, hepatomegaly, and renomegaly remained significantly more prevalent in T2D than in long COVID. Conclusion: Multi-organ MRI assessment can enrich the current blunt assessment of multi-system abnormalities in diverse disease states to inform earlier intervention and treatments.