Prediction of multidrug-resistant bacteria (MDR) hospital-acquired infection (HAI) and colonisation: A systematic review.

BACKGROUND: Hospital-Acquired Infections (HAI) represent a public health priority in most countries worldwide. Our main objective was to systematically review the quality of the predictive modeling literature regarding multidrug-resistant gram-negative bacteria in Intensive Care Units (ICUs). METHODS: We conducted and reported a Systematic Literature Review according to the recommendations of the PRISMA statement. We analysed the quality of the articles in terms of adherence to the TRIPOD checklist. RESULTS: The initial search identified 1935 papers and 15 final articles were included in the review. Most studies analysed used traditional prediction models (logistic regression), and only three developed machine-learning techniques. We noted poor adherence to the main methodological issues recommended in the TRIPOD checklist to develop prediction models, such as handling missing data (20% adherence), model-building procedures (20% adherence), assessing model performance (47% adherence), and reporting performance measures (33% adherence). CONCLUSIONS: Our review found few studies that use efficient alternatives to predict the acquisition of multidrug-resistant gram-negative bacteria in ICUs. Furthermore, we noted a lack of strategies for dealing with missing data, feature selection, and imbalanced datasets, a common problem in HAI studies.

Clinical features, etiologies, and outcomes of central nervous system infections in intensive care: A multicentric retrospective study in a large Brazilian metropolitan area.

PURPOSE: The goal of this study was to investigate severe central nervous system infections (CNSI) in adults admitted to the intensive care unit (ICU). We analyzed the clinical presentation, causes, and outcomes of these infections, while also identifying factors linked to higher in-hospital mortality rates. MATERIALS AND METHODS: We conducted a retrospective multicenter study in Rio de Janeiro, Brazil, from 2012 to 2019. Using a prediction tool, we selected ICU patients suspected of having CNSI and reviewed their medical records. Multivariate analyses identified variables associated with in-hospital mortality. RESULTS: In a cohort of 451 CNSI patients, 69 (15.3%) died after a median 11-day hospitalization (5-25 IQR). The distribution of cases was as follows: 29 (6.4%) had brain abscess, 161 (35.7%) had encephalitis, and 261 (57.8%) had meningitis. Characteristics: median age 41 years (27-53 IQR), 260 (58%) male, and 77 (17%) HIV positive. The independent mortality predictors for encephalitis were AIDS (OR = 4.3, p = 0.01), ECOG functional capacity limitation (OR = 4.0, p < 0.01), ICU admission from ward (OR = 4.0, p < 0.01), mechanical ventilation ≥10 days (OR = 6.1, p = 0.04), SAPS 3 ≥ 55 points (OR = 3.2, p = 0.02). Meningitis: Age > 60 years (OR = 234.2, p = 0.04), delay >3 days for treatment (OR = 2.9, p = 0.04), mechanical ventilation ≥10 days (OR = 254.3, p = 0.04), SOFA >3 points (OR = 2.7, p = 0.03). Brain abscess: No associated factors found in multivariate regression. CONCLUSIONS: Patients' overall health, prompt treatment, infection severity, and prolonged respiratory support in the ICU all significantly affect in-hospital mortality rates. Additionally, the implementation of CNSI surveillance with the used prediction tool could enhance public health policies.

Evidence-Based Checklist to Delay Cardiac Arrest in Brain-Dead Potential Organ Donors: The DONORS Cluster Randomized Clinical Trial.

Importance: The effectiveness of goal-directed care to reduce loss of brain-dead potential donors to cardiac arrest is unclear. Objective: To evaluate the effectiveness of an evidence-based, goal-directed checklist in the clinical management of brain-dead potential donors in the intensive care unit (ICU). Design, Setting, and Participants: The Donation Network to Optimize Organ Recovery Study (DONORS) was an open-label, parallel-group cluster randomized clinical trial in Brazil. Enrollment and follow-up were conducted from June 20, 2017, to November 30, 2019. Hospital ICUs that reported 10 or more brain deaths in the previous 2 years were included. Consecutive brain-dead potential donors in the ICU aged 14 to 90 years with a condition consistent with brain death after the first clinical examination were enrolled. Participants were randomized to either the intervention group or the control group. The intention-to-treat data analysis was conducted from June 15 to August 30, 2020. Interventions: Hospital staff in the intervention group were instructed to administer to brain-dead potential donors in the intervention group an evidence-based checklist with 13 clinical goals and 14 corresponding actions to guide care, every 6 hours, from study enrollment to organ retrieval. The control group provided or received usual care. Main Outcomes and Measures: The primary outcome was loss of brain-dead potential donors to cardiac arrest at the individual level. A prespecified sensitivity analysis assessed the effect of adherence to the checklist in the intervention group. Results: Among the 1771 brain-dead potential donors screened in 63 hospitals, 1535 were included. These patients included 673 males (59.2%) and had a median (IQR) age of 51 (36.3-62.0) years. The main cause of brain injury was stroke (877 [57.1%]), followed by trauma (485 [31.6%]). Of the 63 hospitals, 31 (49.2%) were assigned to the intervention group (743 [48.4%] brain-dead potential donors) and 32 (50.8%) to the control group (792 [51.6%] brain-dead potential donors). Seventy potential donors (9.4%) at intervention hospitals and 117 (14.8%) at control hospitals met the primary outcome (risk ratio [RR], 0.70; 95% CI, 0.46-1.08; P = .11). The primary outcome rate was lower in those with adherence higher than 79.0% than in the control group (5.3% vs 14.8%; RR, 0.41; 95% CI, 0.22-0.78; P = .006). Conclusions and Relevance: This cluster randomized clinical trial was inconclusive in determining whether the overall use of an evidence-based, goal-directed checklist reduced brain-dead potential donor loss to cardiac arrest. The findings suggest that use of such a checklist has limited effectiveness without adherence to the actions recommended in this checklist. Trial Registration: ClinicalTrials.gov Identifier: NCT03179020.

Effectiveness of a multicomponent intervention to face the COVID-19 pandemic in Rio de Janeiro's favelas: difference-in-differences analysis.

INTRODUCTION: Few community-based interventions addressing the transmission control and clinical management of COVID-19 cases have been reported, especially in poor urban communities from low-income and middle-income countries. Here, we analyse the impact of a multicomponent intervention that combines community engagement, mobile surveillance, massive testing and telehealth on COVID-19 cases detection and mortality rates in a large vulnerable community (Complexo da Maré) in Rio de Janeiro, Brazil. METHODS: We performed a difference-in-differences (DID) analysis to estimate the impact of the multicomponent intervention in Maré, before (March-August 2020) and after the intervention (September 2020 to April 2021), compared with equivalent local vulnerable communities. We applied a negative binomial regression model to estimate the intervention effect in weekly cases and mortality rates in Maré. RESULTS: Before the intervention, Maré presented lower rates of reported COVID-19 cases compared with the control group (1373 vs 1579 cases/100 000 population), comparable mortality rates (309 vs 287 deaths/100 000 population) and higher case fatality rates (13.7% vs 12.2%). After the intervention, Maré displayed a 154% (95% CI 138.6% to 170.4%) relative increase in reported case rates. Relative changes in reported death rates were -60% (95% CI -69.0% to -47.9%) in Maré and -28% (95% CI -42.0% to -9.8%) in the control group. The case fatality rate was reduced by 77% (95% CI -93.1% to -21.1%) in Maré and 52% (95% CI -81.8% to -29.4%) in the control group. The DID showed a reduction of 46% (95% CI 17% to 65%) of weekly reported deaths and an increased 23% (95% CI 5% to 44%) of reported cases in Maré after intervention onset. CONCLUSION: An integrated intervention combining communication, surveillance and telehealth, with a strong community engagement component, could reduce COVID-19 mortality and increase case detection in a large vulnerable community in Rio de Janeiro. These findings show that investment in community-based interventions may reduce mortality and improve pandemic control in poor communities from low-income and middle-income countries.

Microglial NLRP3 Inflammasome Induces Excitatory Synaptic Loss Through IL-1ß-Enriched Microvesicle Release: Implications for Sepsis-Associated Encephalopathy.

Acute cerebral dysfunction is a pathological state common in severe infections and a pivotal determinant of long-term cognitive outcomes. Current evidence indicates that a loss of synaptic contacts orchestrated by microglial activation is central in sepsis-associated encephalopathy. However, the upstream signals that lead to microglial activation and the mechanism involved in microglial-mediated synapse dysfunction in sepsis are poorly understood. This study investigated the involvement of the NLRP3 inflammasome in microglial activation and synaptic loss related to sepsis. We demonstrated that septic insult using the cecal ligation and puncture (CLP) model induced the expression of NLRP3 inflammasome components in the brain, such as NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3), apoptosis-associated speck-like protein containing a C-terminal caspase recruitment domain (ASC), caspase-1, and IL-1ß. Immunostaining techniques revealed increased expression of the NLRP3 inflammasome in microglial cells in the hippocampus of septic mice. Meanwhile, an in vitro model of primary microglia stimulated with LPS exhibited an increase in mitochondrial reactive oxygen species (ROS) production, NLRP3 complex recruitment, and IL-1ß release. Pharmacological inhibition of NLRP3, caspase-1, and mitochondrial ROS all decreased IL-1ß secretion by microglial cells. Furthermore, we found that microglial NLRP3 activation is the main pathway for IL-1ß-enriched microvesicle (MV) release, which is caspase-1-dependent. MV released from LPS-activated microglia induced neurite suppression and excitatory synaptic loss in neuronal cultures. Moreover, microglial caspase-1 inhibition prevented neurite damage and attenuated synaptic deficits induced by the activated microglial MV. These results suggest that microglial NLRP3 inflammasome activation is the mechanism of IL-1ß-enriched MV release and potentially synaptic impairment in sepsis.

Seroepidemiology of SARS-CoV-2 on a partially vaccinated island in Brazil: Determinants of infection and vaccine response.

Background: A vaccination campaign targeted adults in response to the pandemic in the City of Rio de Janeiro. Objective: We aimed to evaluate the seroprevalence of SARS-CoV-2 antibodies and identify factors associated with seropositivity on vaccinated and unvaccinated residents. Methods: We performed a seroepidemiologic survey in all residents of Paquetá Island, a neighborhood of Rio de Janeiro city, during the COVID-19 vaccine roll-out. Serological tests were performed from June 16 to June 19, 2021, and adjusted seropositivity rates were estimated by age and epidemiological variables. Logistic regression models were used to estimate adjusted ORs for risk factors to SARS-CoV-2 seropositivity in non-vaccinated individuals, and potential determinants of the magnitude of antibody responses in the seropositive population. Results: We included in the study 3,016 residents of Paquetá (83.5% of the island population). The crude seroprevalence of COVID-19 antibodies in our sample was 53.6% (95% CI = 51.0, 56.3). The risk factors for SARS-CoV-2 seropositivity in non-vaccinated individuals were history of confirmed previous COVID-19 infection (OR = 4.74; 95% CI = 3.3, 7.0), being a household contact of a case (OR = 1.93; 95% CI = 1.5, 2.6) and in-person learning (OR = 2.01; 95% CI = 1.4, 3.0). Potential determinants of the magnitude of antibody responses among the seropositive were hybrid immunity, the type of vaccine received, and time since the last vaccine dose. Being vaccinated with Pfizer or AstraZeneca (Beta = 2.2; 95% CI = 1.8, 2.6) determined higher antibody titers than those observed with CoronaVac (Beta = 1.2; 95% CI = 0.9, 1.5). Conclusions: Our study highlights the impact of vaccination on COVID-19 collective immunity even in a highly affected population, showing the difference in antibody titers achieved with different vaccines and how they wane with time, reinforcing how these factors should be considered when estimating effectiveness of a vaccination program at any given time. We also found that hybrid immunity was superior to both infection-induced and vaccine-induced immunity alone, and online learning protected students from COVID-19 exposure.

Data-driven methodology to predict the ICU length of stay: A multicentre study of 99,492 admissions in 109 Brazilian units.

PURPOSE: The length of stay (LoS) is one of the most used metrics for resource use in Intensive Care Units (ICU). We propose a structured data-driven methodology to predict the ICU length of stay and the risk of prolonged stay, and its application in a large multicentre Brazilian ICU database. METHODS: Demographic data, comorbidities, complications, laboratory data, and primary and secondary diagnosis were prospectively collected and retrospectively analysed by a data-driven methodology, which includes eight different machine learning models and a stacking model. The study setting included 109 mixed-type ICUs from 38 Brazilian hospitals and the external validation was performed by 93 medical-surgical ICUs of 55 hospitals in Brazil. RESULTS: A cohort of 99,492 adult ICU admissions were included from the 1st of January to the 31st of December 2019. The stacking model combining Random Forests and Linear Regression presented the best results to predict ICU length of stay (RMSE = 3.82; MAE = 2.52; R² = 0.36). The prediction model for the risk of long stay were accurate to early identify prolonged stay patients (Brier Score = 0.04, AUC = 0.87, PPV = 0.83, NPV = 0.95). CONCLUSION: The data-driven methodology to predict ICU length of stay and the risk of long-stay proved accurate in a large multicentre cohort of general ICU patients. The proposed models are helpful to predict the individual length of stay and to early identify patients with high risk of prolonged stay.

Antibiotic Consumption and Deviation of Prescribed Daily Dose From the Defined Daily Dose in Critical Care Patients: A Point-Prevalence Study.

Background: The consumption of antibiotics is one of the metrics used to evaluate the impact of antimicrobial stewardship programs (ASP). The aim of this study was to determine the prevalence of antibiotic consumption in Brazilian intensive care units (ICUs) and estimate the deviation of the prescribed daily dose (PDD) from the defined daily dose (DDD). Methods: This is a multicenter, observational, point-prevalence study carried out in adult ICUs of 8 Brazilian hospitals from August 2019, to February 2020. We collected data on the patient's demographic and clinical characteristics, antibiotic therapy, classification and site of infections. The DU90 (antibiotic accounting for 90% of the volume utilized) was calculated, and the antibiotics were classified by the Anatomical Therapeutic Chemical (ATC) Index and the World Health Organization (WHO) Access, Watch, Reserve (AWaRe) groups. For the most prevalent antibiotics, the deviation of PDD from DDD was determined. Results: Three hundred thirty-two patients from 35 ICUs were analyzed. The prevalence of antibiotic use was 52.4%. The patients in use of antibiotics were predominantly over 60 years of age (81.6%) with pulmonary infections (45.8%). A predominance of empirical regimens was observed (62.6%) among antibiotic therapies. The highest frequencies of prescriptions observed were for piperacillin + tazobactam (16.1%), meropenem (13.3%), amoxicillin + clavulanate (7.2%), azithromycin (7.2%), and teicoplanin (6.1%). The watch (64.2%) and reserve (9.6%) categories of the AWaRe classification accounted for 73.8% of all antibiotics, and they were prescribed alone or in combinations. High variability of doses was observed for the most prescribed antibiotics, and large deviations of PDD from the DDD were observed for meropenem, teicoplanin, and tigecycline. Conclusions: The high prevalence of antibiotic prescription was related to a predominance of empirical regimens and antibiotics belonging to the WHO Watch classification. High variability of doses and large deviations of PDD from DDD for meropenem, teicoplanin, and tigecycline was observed, suggesting that DDD may be insufficient to monitor the consumption of these antibiotics in the ICU population. The variability of doses found for the most prescribed antibiotics suggests the need for monitoring and intervention targets for antibiotic stewardship teams.

Clinical features, electroencephalogram, and biomarkers in pediatric sepsis-associated encephalopathy.

To date, no specific diagnostic criteria for sepsis-associated encephalopathy (SAE) have been established. We studied 33 pediatric patients with sepsis prospectively and evaluated the level of consciousness, the presence of delirium, electroencephalographic (EEG) findings, and plasma levels of neuron-specific enolase and S100-calcium-binding protein-B. A presumptive diagnosis of SAE was primarily considered in the presence of a decreased level of consciousness and/or delirium (clinical criteria), but specific EEG abnormalities were also considered (EEG criteria). The time course of the biomarkers was compared between groups with and without clinical or EEG criteria. The Functional Status Scale (FSS) was assessed at admission, discharge, and 3-6 months post-discharge. Clinical criteria were identified in 75.8% of patients, EEG criteria in 26.9%, both in 23.1%, and none in 23.1%. Biomarkers did not differ between groups. Three patients had an abnormal FSS at discharge, but no one on follow-up. A definitive diagnostic pattern for SAE remained unclear. Clinical criteria should be the basis for diagnosis, but sedation may be a significant confounder, also affecting EEG interpretation. The role of biomarkers requires a better definition. The diagnosis of SAE in pediatric patients remains a major challenge. New consensual diagnostic definitions and mainly prognostic studies are needed.

Central nervous system infection in the intensive care unit: Development and validation of a multi-parameter diagnostic prediction tool to identify suspected patients.

BACKGROUND: Central nervous system infections (CNSI) are diseases with high morbidity and mortality, and their diagnosis in the intensive care environment can be challenging. Objective: To develop and validate a diagnostic model to quickly screen intensive care patients with suspected CNSI using readily available clinical data. METHODS: Derivation cohort: 783 patients admitted to an infectious diseases intensive care unit (ICU) in Oswaldo Cruz Foundation, Rio de Janeiro RJ, Brazil, for any reason, between 01/01/2012 and 06/30/2019, with a prevalence of 97 (12.4%) CNSI cases. Validation cohort 1: 163 patients prospectively collected, between 07/01/2019 and 07/01/2020, from the same ICU, with 15 (9.2%) CNSI cases. Validation cohort 2: 7,270 patients with 88 CNSI (1.21%) admitted to a neuro ICU in Chicago, IL, USA between 01/01/2014 and 06/30/2019. Prediction model: Multivariate logistic regression analysis was performed to construct the model, and Receiver Operating Characteristic (ROC) curve analysis was used for model validation. Eight predictors-age <56 years old, cerebrospinal fluid white blood cell count >2 cells/mm3, fever (≥38°C/100.4°F), focal neurologic deficit, Glasgow Coma Scale <14 points, AIDS/HIV, and seizure-were included in the development diagnostic model (P<0.05). RESULTS: The pool data's model had an Area Under the Receiver Operating Characteristics (AUC) curve of 0.892 (95% confidence interval 0.864-0.921, P<0.0001). CONCLUSIONS: A promising and straightforward screening tool for central nervous system infections, with few and readily available clinical variables, was developed and had good accuracy, with internal and external validity.

Proteomics reveals disturbances in the immune response and energy metabolism of monocytes from patients with septic shock.

Sepsis results from a dyshomeostatic response to infection, which may lead to hyper or hypoimmune states. Monocytes are central regulators of the inflammatory response, but our understanding of their role in the genesis and resolution of sepsis is still limited. Here, we report a comprehensive exploration of monocyte molecular responses in a cohort of patients with septic shock via proteomic profiling. The acute stage of septic shock was associated with an impaired inflammatory phenotype, indicated by the down-regulation of MHC class II molecules and proinflammatory cytokine pathways. Simultaneously, there was an up-regulation of glycolysis enzymes and a decrease in proteins related to the citric acid cycle and oxidative phosphorylation. On the other hand, the restoration of immunocompetence was the hallmark of recovering patients, in which an upregulation of interferon signaling pathways was a notable feature. Our results provide insights into the immunopathology of sepsis and propose that, pending future studies, immunometabolism pathway components could serve as therapeutic targets in septic patients.

Neuroinflammation in Sepsis: Molecular Pathways of Microglia Activation.

Frequently underestimated, encephalopathy or delirium are common neurological manifestations associated with sepsis. Brain dysfunction occurs in up to 80% of cases and is directly associated with increased mortality and long-term neurocognitive consequences. Although the central nervous system (CNS) has been classically viewed as an immune-privileged system, neuroinflammation is emerging as a central mechanism of brain dysfunction in sepsis. Microglial cells are major players in this setting. Here, we aimed to discuss the current knowledge on how the brain is affected by peripheral immune activation in sepsis and the role of microglia in these processes. This review focused on the molecular pathways of microglial activity in sepsis, its regulatory mechanisms, and their interaction with other CNS cells, especially with neuronal cells and circuits.

Brazilian guidelines for the management of brain-dead potential organ donors. The task force of the Associação de Medicina Intensiva Brasileira, Associação Brasileira de Transplantes de Órgãos, Brazilian Research in Critical Care Network, and the General Coordination of the National Transplant System. / Diretrizes brasileiras para o manejo de potenciais doadores de órgãos em morte encefálica. Uma força-tarefa composta por Associação de Medicina Intensiva Brasileira, Associação Brasileira de Transplantes de Órgãos, Brazilian Research in Critical Care Network e Coordenação Geral do Sistema Nacional de Transplantes.

OBJECTIVE: To contribute to updating the recommendations for brain-dead potential organ donor management. METHODS: A group of 27 experts, including intensivists, transplant coordinators, transplant surgeons, and epidemiologists, answered questions related to the following topics were divided into mechanical ventilation, hemodynamics, endocrine-metabolic management, infection, body temperature, blood transfusion, and checklists use. The outcomes considered were cardiac arrests, number of organs removed or transplanted as well as function / survival of transplanted organs. The quality of evidence of the recommendations was assessed using the Grading of Recommendations Assessment, Development, and Evaluation system to classify the recommendations. RESULTS: A total of 19 recommendations were drawn from the expert panel. Of these, 7 were classified as strong, 11 as weak and 1 was considered a good clinical practice. CONCLUSION: Despite the agreement among panel members on most recommendations, the grade of recommendation was mostly weak.

OBJETIVO: Fornecer recomendações para nortear o manejo clínico do potencial doador em morte encefálica. MÉTODOS: O presente documento foi formulado em dois painéis compostos por uma força tarefa integrada por 27 especialistas de diferentes áreas que responderam a questões dirigidas aos seguintes temas: ventilação mecânica, hemodinâmica, suporte endócrino-metabólico, infecção, temperatura corporal, transfusão sanguínea, e uso de checklists. Os desfechos considerados foram: parada cardíaca, número de órgãos retirados ou transplantados e função/sobrevida dos órgãos transplantados. A qualidade das evidências das recomendações foi avaliada pelo sistema Grading of Recommendations Assessment, Development, and Evaluation. RESULTADOS: Foram geradas 19 recomendações a partir do painel de especialistas. Dessas, 7 foram classificadas como fortes, 11 fracas e uma foi considerada boa prática clínica. CONCLUSÃO: Apesar da concordância entre os membros do painel em relação à maior parte das recomendações, o grau de recomendação é fraco em sua maioria.

Estimating COVID-19 Pneumonia Extent and Severity From Chest Computed Tomography.

BACKGROUND: COVID-19 pneumonia extension is assessed by computed tomography (CT) with the ratio between the volume of abnormal pulmonary opacities (PO) and CT-estimated lung volume (CTLV). CT-estimated lung weight (CTLW) also correlates with pneumonia severity. However, both CTLV and CTLW depend on demographic and anthropometric variables. PURPOSES: To estimate the extent and severity of COVID-19 pneumonia adjusting the volume and weight of abnormal PO to the predicted CTLV (pCTLV) and CTLW (pCTLW), respectively, and to evaluate their possible association with clinical and radiological outcomes. METHODS: Chest CT from 103 COVID-19 and 86 healthy subjects were examined retrospectively. In controls, predictive equations for estimating pCTLV and pCTLW were assessed. COVID-19 pneumonia extent and severity were then defined as the ratio between the volume and the weight of abnormal PO expressed as a percentage of the pCTLV and pCTLW, respectively. A ROC analysis was used to test differential diagnosis ability of the proposed method in COVID-19 and controls. The degree of pneumonia extent and severity was assessed with Z-scores relative to the average volume and weight of PO in controls. Accordingly, COVID-19 patients were classified as with limited, moderate and diffuse pneumonia extent and as with mild, moderate and severe pneumonia severity. RESULTS: In controls, CTLV could be predicted by sex and height (adjusted R 2 = 0.57; P < 0.001) while CTLW by age, sex, and height (adjusted R 2 = 0.6; P < 0.001). The cutoff of 20% (AUC = 0.91, 95%CI 0.88-0.93) for pneumonia extent and of 50% (AUC = 0.91, 95%CI 0.89-0.92) for pneumonia severity were obtained. Pneumonia extent were better correlated when expressed as a percentage of the pCTLV and pCTLW (r = 0.85, P < 0.001), respectively. COVID-19 patients with diffuse and severe pneumonia at admission presented significantly higher CRP concentration, intra-hospital mortality, ICU stay and ventilatory support necessity, than those with moderate and limited/mild pneumonia. Moreover, pneumonia severity, but not extent, was positively and moderately correlated with age (r = 0.46) and CRP concentration (r = 0.44). CONCLUSION: The proposed estimation of COVID-19 pneumonia extent and severity might be useful for clinical and radiological patient stratification.