scholarly journals The wide spectrum of neuropsychiatric complications in Covid-19 patients within a multidisciplinary hospital context

2020 ◽  
Author(s):  
Cécile Delorme ◽  
Marion Houot ◽  
Charlotte Rosso ◽  
Stéphanie Carvalho ◽  
Thomas Nedelec ◽  
...  
Keyword(s):  
Intensive Care ◽  
Critical Illness ◽  
Psychiatric Symptoms ◽  
Neuropsychiatric Symptoms ◽  
Cerebrovascular Disorders ◽  
Motor Deficit ◽  
Emission Computed Tomography ◽  
Psychiatric Disturbance ◽  
Risk Of Death ◽  
Neuropsychiatric Complications

AbstractObjectiveTo describe the spectrum of neurological and psychiatric complications in patients with Covid-19 seen in a multidisciplinary center over six months.MethodsWe conducted a retrospective, observational study on all patients showing neurological or psychiatric symptoms in the context of Covid-19 seen in the Department of Neurology and Psychiatry of the APHP-Sorbonne University. We collected demographic data, medical and treatment history, comorbidities, symptoms, date of onset, and severity of Covid-19 infection, neurological and psychiatric symptoms, neurological and psychiatric examination data and, when available, results from cerebrospinal fluid (CSF) analysis, brain magnetic resonance (MRI) imaging, 18-fluorodesoxyglucose-position emission computed tomography (FDG-PET/CT)), electroencephalography (EEG) and electroneuromyography (ENMG).Results245 patients were included in the analysis. One-hundred fourteen patients (47%) were admitted to the intensive care unit (ICU) and 10 (4%) died. The most frequently reported neuropsychiatric symptoms were motor deficit (41%), cognitive disturbance (35%), impaired consciousness (26%), psychiatric disturbance (24%), headache (20%) and behavioral disturbance (18%). The most frequent syndromes diagnosed were encephalopathy (43%), critical illness polyneuropathy and myopathy (26%), isolated psychiatric disturbance (18%), and cerebrovascular disorders (16%). No patients showed evidence of SARS-CoV-2 in their CSF. Encephalopathy was associated with greater age and higher risk of death. Critical illness neuromyopathy was associated with an extended stay in the ICU.ConclusionsThe majority of the neuropsychiatric complications recorded could be imputed to critical illness, intensive care and systemic inflammation, which contrasts with the paucity of more direct SARS-CoV-2-related complications or post-infection disorders.

Mortality after Critical Illness

2014 ◽  
Author(s):  
Matthew Baldwin ◽  
Hannah Wunsch
Keyword(s):  
Mechanical Ventilation ◽  
Intensive Care ◽  
Critical Illness ◽  
Prolonged Mechanical Ventilation ◽  
Risk Of Death ◽  
Increased Risk ◽  
Poor Nutrition ◽  
Long Term Mortality

Many critically ill patients now survive what were previously fatal illnesses, but long-term mortality after critical illness remains high. While study populations vary by country, age, intervention, or specific diagnosis, investigations demonstrate that the majority of additional deaths occur in the first 6 to 12 months after hospital discharge. Patients with diagnoses of cancer, respiratory failure, and neurological disorders leading to the need for intensive care have the highest long-term mortality, while those with trauma and cardiovascular diseases have much lower long-term mortality. Use of mechanical ventilation, older age, and a need for care in a facility after the acute hospitalization are associated with particularly high 1-year mortality among survivors of critical illnesses. Due to challenges of follow-up, less is known about causes of delayed mortality following critical illness. Longitudinal studies of survivors of pneumonia, stroke, and patients who require prolonged mechanical ventilation suggest that most debilitated survivors die from recurrent infections and sepsis. Potential biologic mechanisms for increased risk of death after a critical illness include sepsis-induced immunoparalysis, intensive care unit-acquired weakness, neuroendocrine changes, poor nutrition, and genetic variance. Studies are needed to fully understand how the severity of the acute critical illness interacts with comorbid disease, pre-illness disability, and pre-existing and acquired frailty to affect long-term mortality. Such studies will be fundamental to improve targeting of rehabilitative, therapeutic, and palliative interventions to improve both survival and quality of life after critical illness.

scholarly journals Risk of a Diagnosis of Dementia for Elderly Medicare Beneficiaries after Intensive Care

2015 ◽  
Vol 123 (5) ◽  
pp. 1105-1112 ◽  
Author(s):  
Carmen Guerra ◽  
May Hua ◽  
Hannah Wunsch
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Critical Illness ◽  
General Population ◽  
Hospital Discharge ◽  
Medicare Beneficiaries ◽  
Risk Of Death ◽  
Increased Risk ◽  
Diagnosis Of Dementia

Abstract Background Critical illness is likely associated with an increased risk of dementia, but the magnitude remains uncertain. Methods The cohort was a random 2.5% sample of Medicare beneficiaries who received intensive care in 2005 and survived to hospital discharge. Patients were matched with general population controls (age, sex, and race) with 3 yr of follow-up. The authors used an extended Cox model to assess the risk of a diagnosis of dementia, adjusting for the known risk factors for dementia, and the competing risk of death. Results Among 10,348 intensive care patients who survived to hospital discharge, dementia was newly diagnosed in 1,648 (15.0%) over the 3 yr of follow-up versus 12.2% in controls (incidence per 1,000 person-years, 73.6; 95% CI, 70.0 to 77.1 vs. 45.8; 95% CI, 43.2 to 48.3; hazard ratio [HR], 1.61; 95% CI, 1.50 to 1.74; P < 0.001). After accounting for the known risk factors in the year before the index hospitalization, the risk of receiving a diagnosis of dementia remained increased in patients who received intensive care (adjusted HR, 1.43; 95% CI, 1.32 to 1.54; P < 0.001). Inclusion of identifiable risk factors accrued during the quarter of critical illness accounted for almost all of the increased risks (adjusted HR, 1.09; 95% CI, 1.00 to 1.20; P = 0.06). Conclusions Elderly critical care survivors have a 60% increased relative risk, but only 3% increased absolute risk, of receiving a diagnosis of dementia in the subsequent 3 yr compared with the general population. This increased risk is not accounted for by risk factors preexisting the critical illness. Surveillance bias, which increases the likelihood of receiving a diagnosis of dementia, could account for some or all of these additional risks.

scholarly journals Psychiatric Disturbance As a Presenting Symptom in Central Nervous Lymphoma

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 5415-5415
Author(s):  
Akanksha Sharma ◽  
Natalie Ertz-Archambault ◽  
Luke Mountjoy ◽  
Alyx Porter ◽  
Maciej M Mrugala
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Psychiatric Symptoms ◽  
Conflicts Of Interest ◽  
Neuropsychiatric Symptoms ◽  
B Cell Lymphoma ◽  
Psychiatric Disease ◽  
Cns Lymphoma ◽  
Psychiatric Disturbance ◽  
Cognitive Changes

Abstract Background: Central nervous system (CNS) lymphoma manifests as a highly aggressive non-Hodgkins lymphoma, either confined to the central nervous system or secondary to spread of systemic diffuse large B cell lymphoma. Rising incidence of CNS lymphoma has been observed, especially in elderly populations. Presentation depends on the burden and location of disease, with a varying spectrum of symptoms ranging from headaches and cognitive changes to focal neurological deficits and seizures. Neuropsychiatric presentation of CNS lymphoma has been seen and anecdotally reported but appears to be under-represented in the literature. In this retrospective review of patients with CNS lymphoma at MCA we report a cohort of patients who presented with primarily neuropsychiatric symptoms Methods: After receiving IRB approval, we retrospectively identified 135 patients with ICD 9 and 10 codes consistent with CNS lymphoma, seen at Mayo Clinic Arizona, between 1998-2018. Symptoms identified prior to presentation with the CNS component of the lymphoma were recorded with attention to those with depression, anxiety, agitation, psychosis, disinhibition, and apathy. Patients with long term premorbid psychiatric disease or symptoms that developed later in the course as a result the stressors of disease and treatment were excluded. Results: A total of 19 out of 136 patients (14%) were noted to have primarily neuropsychiatric symptoms prior to diagnosis of CNS lymphoma. Symptom onset to diagnosis of PCNSL ranged from 3 weeks to 11 months. The average age was 65, and 47% of subjects were male. Depression, apathy, agitation and features of parkinsonism were the most common neuropsychiatric symptoms identified, with psychosis and disinhibition being the least frequent. The majority of these patients had frontal lobe lesions (42%), although several also had multifocal disease at time of diagnosis. Improvement of neuropsychiatric disease was not explicitly discussed or noted in the treatment and post-treatment notes. In fact, we found it notable that follow up notes generally did not comment on these psychiatric symptoms at all, and there was no clear management plan separate from treating the disease process. Parkinsonian features were observed in 5 patients (26%), with onset range from 2 weeks to 29 months prior to PCNSL diagnosis. The associated lesions were mostly deep basal ganglia or corpus callosum except in one case of left parietal lobe tumor. Notably, all patients had resolution of their parkinsonism with treatment of the lymphoma. Conclusions: Neuropsychiatric symptoms are a rare but noteworthy presentation of CNS lymphoma, distinct from cognitive changes that have been previously described with this condition. There is an increasing awareness of neurological illness presenting as pure psychiatric disturbance, prompting exclusion of organic disease, particularly in elderly patients who present with new psychiatric complaints. Disclosures No relevant conflicts of interest to declare.

scholarly journals Adaptive metabolic and inflammatory responses identified using accelerated aging metrics are linked to adverse outcomes in severe SARS-CoV-2 infection

2021 ◽  
Author(s):  
Alejandro Márquez-Salinas ◽  
Carlos A Fermín-Martínez ◽  
Neftalí Eduardo Antonio-Villa ◽  
Arsenio Vargas-Vázquez ◽  
Enrique C. Guerra ◽  
...  
Keyword(s):  
Critical Illness ◽  
Proportional Hazards ◽  
Inflammatory Responses ◽  
Age Groups ◽  
Accelerated Aging ◽  
Cox Proportional Hazards ◽  
Adverse Outcomes ◽  
Adaptive Responses ◽  
Predictive Capacity ◽  
Risk Of Death

Abstract Background Chronological age (CA) is a predictor of adverse COVID-19 outcomes; however, CA alone does not capture individual responses to SARS-CoV-2 infection. Here, we evaluated the influence of aging metrics PhenoAge and PhenoAgeAccel to predict adverse COVID-19 outcomes. Furthermore, we sought to model adaptive metabolic and inflammatory responses to severe SARS-CoV-2 infection using individual PhenoAge components. Methods In this retrospective cohort study, we assessed cases admitted to a COVID-19 reference center in Mexico City. PhenoAge and PhenoAgeAccel were estimated using laboratory values at admission. Cox proportional hazards models were fitted to estimate risk for COVID-19 lethality and adverse outcomes (ICU admission, intubation, or death). To explore reproducible patterns which model adaptive responses to SARS-CoV-2 infection, we used k-means clustering using PhenoAge components. Results We included 1068 subjects of whom 222 presented critical illness and 218 died. PhenoAge was a better predictor of adverse outcomes and lethality compared to CA and SpO2 and its predictive capacity was sustained for all age groups. Patients with responses associated to PhenoAgeAccel>0 had higher risk of death and critical illness compared to those with lower values (log-rank p<0.001). Using unsupervised clustering we identified four adaptive responses to SARS-CoV-2 infection: 1) Inflammaging associated with CA, 2) metabolic dysfunction associated with cardio-metabolic comorbidities, 3) unfavorable hematological response, and 4) response associated with favorable outcomes. Conclusions Adaptive responses related to accelerated aging metrics are linked to adverse COVID-19 outcomes and have unique and distinguishable features. PhenoAge is a better predictor of adverse outcomes compared to CA.

scholarly journals Early Prediction of Seven-Day Mortality in Intensive Care Unit Using a Machine Learning Model: Results from the SPIN-UTI Project

2021 ◽  
Vol 10 (5) ◽  
pp. 992
Author(s):  
Martina Barchitta ◽  
Andrea Maugeri ◽  
Giuliana Favara ◽  
Paolo Marco Riela ◽  
Giovanni Gallo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care ◽  
Intensive Care Units ◽  
Learning Algorithm ◽  
Area Under The Curve ◽  
Support Vector ◽  
Icu Admission ◽  
Risk Of Death ◽  
Saps Ii ◽  
Svm Algorithm

Patients in intensive care units (ICUs) were at higher risk of worsen prognosis and mortality. Here, we aimed to evaluate the ability of the Simplified Acute Physiology Score (SAPS II) to predict the risk of 7-day mortality, and to test a machine learning algorithm which combines the SAPS II with additional patients’ characteristics at ICU admission. We used data from the “Italian Nosocomial Infections Surveillance in Intensive Care Units” network. Support Vector Machines (SVM) algorithm was used to classify 3782 patients according to sex, patient’s origin, type of ICU admission, non-surgical treatment for acute coronary disease, surgical intervention, SAPS II, presence of invasive devices, trauma, impaired immunity, antibiotic therapy and onset of HAI. The accuracy of SAPS II for predicting patients who died from those who did not was 69.3%, with an Area Under the Curve (AUC) of 0.678. Using the SVM algorithm, instead, we achieved an accuracy of 83.5% and AUC of 0.896. Notably, SAPS II was the variable that weighted more on the model and its removal resulted in an AUC of 0.653 and an accuracy of 68.4%. Overall, these findings suggest the present SVM model as a useful tool to early predict patients at higher risk of death at ICU admission.

scholarly journals Healthcare trajectories before and after critical illness: population-based insight on diverse patients clusters

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Youenn Jouan ◽  
Leslie Grammatico-Guillon ◽  
Noémie Teixera ◽  
Claire Hassen-Khodja ◽  
Christophe Gaborit ◽  
...  
Keyword(s):  
Septic Shock ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Critical Illness ◽  
Length Of Stay ◽  
Population Based ◽  
Hospital Length Of Stay ◽  
Healthcare Use ◽  
Icu Admission ◽  
Icu Discharge

Abstract Background The post intensive care syndrome (PICS) gathers various disabilities, associated with a substantial healthcare use. However, patients’ comorbidities and active medical conditions prior to intensive care unit (ICU) admission may partly drive healthcare use after ICU discharge. To better understand retative contribution of critical illness and PICS—compared to pre-existing comorbidities—as potential determinant of post-critical illness healthcare use, we conducted a population-based evaluation of patients’ healthcare use trajectories. Results Using discharge databases in a 2.5-million-people region in France, we retrieved, over 3 years, all adult patients admitted in ICU for septic shock or acute respiratory distress syndrome (ARDS), intubated at least 5 days and discharged alive from hospital: 882 patients were included. Median duration of mechanical ventilation was 11 days (interquartile ranges [IQR] 8;20), mean SAPS2 was 49, and median hospital length of stay was 42 days (IQR 29;64). Healthcare use (days spent in healthcare facilities) was analyzed 2 years before and 2 years after ICU admission. Prior to ICU admission, we observed, at the scale of the whole study population, a progressive increase in healthcare use. Healthcare trajectories were then explored at individual level, and patients were assembled according to their individual pre-ICU healthcare use trajectory by clusterization with the K-Means method. Interestingly, this revealed diverse trajectories, identifying patients with elevated and increasing healthcare use (n = 126), and two main groups with low (n = 476) or no (n = 251) pre-ICU healthcare use. In ICU, however, SAPS2, duration of mechanical ventilation and length of stay were not different across the groups. Analysis of post-ICU healthcare trajectories for each group revealed that patients with low or no pre-ICU healthcare (which represented 83% of the population) switched to a persistent and elevated healthcare use during the 2 years post-ICU. Conclusion For 83% of ARDS/septic shock survivors, critical illness appears to have a pivotal role in healthcare trajectories, with a switch from a low and stable healthcare use prior to ICU to a sustained higher healthcare recourse 2 years after ICU discharge. This underpins the hypothesis of long-term critical illness and PICS-related quantifiable consequences in healthcare use, measurable at a population level.

scholarly journals Cardiac biomarkers in acute respiratory distress syndrome: a systematic review and meta-analysis

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Dilip Jayasimhan ◽  
Simon Foster ◽  
Catherina L. Chang ◽  
Robert J. Hancox
Keyword(s):  
Systematic Review ◽  
Acute Respiratory Distress Syndrome ◽  
Intensive Care ◽  
Cardiac Dysfunction ◽  
Distress Syndrome ◽  
Troponin I ◽  
Meta Analysis ◽  
Cardiac Injury ◽  
Cardiac Biomarkers ◽  
Risk Of Death

Abstract Background Acute respiratory distress syndrome (ARDS) is a leading cause of morbidity and mortality in the intensive care unit. Biochemical markers of cardiac dysfunction are associated with high mortality in many respiratory conditions. The aim of this systematic review is to examine the link between elevated biomarkers of cardiac dysfunction in ARDS and mortality. Methods A systematic review of MEDLINE, EMBASE, Web of Science and CENTRAL databases was performed. We included studies of adult intensive care patients with ARDS that reported the risk of death in relation to a measured biomarker of cardiac dysfunction. The primary outcome of interest was mortality up to 60 days. A random-effects model was used for pooled estimates. Funnel-plot inspection was done to evaluate publication bias; Cochrane chi-square tests and I2 tests were used to assess heterogeneity. Results Twenty-two studies were included in the systematic review and 18 in the meta-analysis. Biomarkers of cardiac stretch included NT-ProBNP (nine studies) and BNP (six studies). Biomarkers of cardiac injury included Troponin-T (two studies), Troponin-I (one study) and High-Sensitivity-Troponin-I (three studies). Three studies assessed multiple cardiac biomarkers. High levels of NT-proBNP and BNP were associated with a higher risk of death up to 60 days (unadjusted OR 8.98; CI 4.15-19.43; p<0.00001). This association persisted after adjustment for age and illness severity. Biomarkers of cardiac injury were also associated with higher mortality, but this association was not statistically significant (unadjusted OR 2.21; CI 0.94-5.16; p= 0.07). Conclusion Biomarkers of cardiac stretch are associated with increased mortality in ARDS.

scholarly journals The Post-ICU presentation screen (PICUPS) and rehabilitation prescription (RP) for intensive care survivors part II: Clinical engagement and future directions for the national Post-Intensive care Rehabilitation Collaborative

2021 ◽  
pp. 175114372098870
Author(s):  
Zudin Puthucheary ◽  
Craig Brown ◽  
Evelyn Corner ◽  
Sarah Wallace ◽  
Julie Highfield ◽  
...  
Keyword(s):  
Intensive Care ◽  
Critical Illness ◽  
Inpatient Rehabilitation ◽  
Service Evaluation ◽  
Language Therapy ◽  
Initial Development ◽  
Related Data ◽  
Acute Hospitals ◽  
Rehabilitation Needs ◽  
Post Intensive Care Syndrome

Background Many Intensive Care Unit (ICU) survivors suffer from a multi- system disability, termed the post-intensive care syndrome. There is no current national coordination of either rehabilitation pathways or related data collection for them. In the last year, the need for tools to systematically identify the multidisciplinary rehabilitation needs of severely affected COVID-19 survivors has become clear. Such tools offer the opportunity to improve rehabilitation for all critical illness survivors through provision of a personalised Rehabilitation Prescription (RP). The initial development and secondary refinement of such an assessment and data tools is described in the linked paper. We report here the clinical and workforce data that was generated as a result. Methods Prospective service evaluation of 26 acute hospitals in England using the Post-ICU Presentation Screen (PICUPS) tool and the RP. The PICUPS tool comprised items in domains of a) Medical and essential care, b) Breathing and nutrition; c) Physical movement and d) Communication, cognition and behaviour. Results No difference was seen in total PICUPS scores between patients with or without COVID-19 (77 (IQR 60-92) vs. 84 (IQR 68-97); Mann-Whitney z = −1.46, p = 0.144. A network analysis demonstrated that requirements for physiotherapy, occupational therapy, speech and language therapy, dietetics and clinical psychology were closely related and unaffected by COVID-19 infection status. A greater proportion of COVID-19 patients were referred for inpatient rehabilitation (13% vs. 7%) and community-based rehabilitation (36% vs.15%). The RP informed by the PICUPS tool generally specified a greater need for multi-professional input when compared to rehabilitation plans instituted. Conclusions The PICUPS tool is feasible to implement as a screening mechanism for post-intensive care syndrome. No differences are seen in the rehabilitation needs of patients with and without COVID-19 infection. The RP could be the vehicle that drives the professional interventions across the transitions from acute to community care. No single discipline dominates the rehabilitation requirements of these patients, reinforcing the need for a personalised RP for critical illness survivors.

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