Protecting brains and saving futures guidelines: A prospective, multicenter, and observational study on the use of telemedicine for neonatal neurocritical care in Brazil

Background Management of high-risk newborns should involve the use of standardized protocols and training, continuous and specialized brain monitoring with electroencephalography (EEG), amplitude integrated EEG, Near Infrared Spectroscopy, and neuroimaging. Brazil is a large country with disparities in health care assessment and some neonatal intensive care units (NICUs) are not well structured with trained personnel able to provide adequate neurocritical care. To reduce this existing gap, an advanced telemedicine model of neurocritical care called Protecting Brains and Saving Futures (PBSF) Guidelines was developed and implemented in a group of Brazilian NICUs. Methods A prospective, multicenter, and observational study will be conducted in all 20 Brazilian NICUs using the PBSF Guidelines as standard-of-care. All infants treated accordingly to the guidelines during Dec 2021 to Nov 2024 will be eligible. Ethical approval was obtained from participating centers. The primary objective is to describe adherence to the PBSF Guidelines and clinical outcomes, by center and over a 3-year period. Adherence will be measured by quantification of neuromonitoring, neuroimaging exams, sub-specialties consultation, and clinical case discussions and videoconference meetings. Clinical outcomes of interest are detection of seizures during hospitalization, use of anticonvulsants, inotropes, and fluid resuscitation, death before hospital discharge, length of hospital stay, and referral of patients to specialized follow-up. Discussion The study will provide evaluation of PBSF Guidelines adherence and its impact on clinical outcomes. Thus, data from this large prospective, multicenter, and observational study will help determine whether neonatal neurocritical care via telemedicine can be effective. Ultimately, it may offer the necessary framework for larger scale implementation and development of research projects using remote neuromonitoring. Trial registration NCT03786497, Registered 26 December 2018, https://www.clinicaltrials.gov/ct2/show/NCT03786497?term=protecting+brains+and+saving+futures&draw=2&rank=1.

Pre-Operative Point-of-Care Assessment of Left Ventricular Diastolic Dysfunction, an Observational Study

Background Left ventricular (LV) diastolic dysfunction is an acknowledged peri-operative risk factor that should be identified before surgery. This study aimed to evaluate a simplified echocardiographic method using e’ and E/e’ for identification and grading of diastolic dysfunction pre-operatively. Methods 96 ambulatory surgical patients were consecutively included to this prospective observational study. Pre-operative transthoracic echocardiography was conducted prior to surgery, and diagnosis of LV diastolic dysfunction was established by comprehensive and simplified assessment, and the results were compared. The accuracy of e’-velocities in order to discriminate patients with diastolic dysfunction was established by calculating accuracy, efficiency, positive (PPV) and negative predictive (NPV) values, and area under the receiver operating characteristic curve (AUROC). Results Comprehensive assessment established diastolic dysfunction in 77% (74/96) of patients. Of these, 22/74 was categorized as mild dysfunction, 43/74 as moderate dysfunction and 9/74 as severe dysfunction. Using the simplified method with e’ and E/e’, diastolic dysfunction was established in 70.8% (68/96) of patients. Of these, 8/68 was categorized as mild dysfunction, 36/68 as moderate dysfunction and 24/68 as severe dysfunction. To discriminate diastolic dysfunction of any grade, e’-velocities (mean<9 cm s−1) had an AUROC of 0.901 (95%CI 0.840-0.962), with a PPV of 55.2%, a NPV of 90.9% and a test efficiency of 0.78. Conclusions The results of this study indicate that a simplified approach with tissue Doppler e’-velocities may be used to rule out patients with diastolic dysfunction pre-operatively, but together with E/e’ ratio the severity of diastolic dysfunction may be overestimated. Trial registration: Clinicaltrials.gov, Identifier: NCT 03349593. Date of registration 2017-11-21. https://clinicaltrials.gov.

Facility and care provider emergency preparedness for neonatal resuscitation in Kano, Nigeria

Introduction The knowledge, attitude, and practice of emergency neonatal resuscitation are critical requirements in any facility that offers obstetric and neonatal services. This study aims to conduct a needs assessment survey and obtain individual and facility-level data on expertise and readiness for neonatal resuscitation. We hypothesize that neonatal emergency preparedness among healthcare providers in Kano, Nigeria is associated with the level of knowledge, attitudinal disposition, practice and equipment availability at the facility level. Methods A semi-structured, self-administered questionnaire was administered to a cross-section of health providers directly involved with neonatal care (n = 112) and attending a neonatal resuscitation workshop in Kano state. Information regarding knowledge, attitude, practice and facility preparedness for neonatal resuscitation was obtained. Bloom’s cut-off score and a validated basic emergency obstetric and neonatal care assessment tool were adopted to categorize outcomes. Multivariable logistic regression was employed to determine independent predictors of knowledge and practice. Results Almost half (48% and 42% respectively) of the respondents reported average level of self-assessed knowledge and comfort during resuscitation. Only 7% (95% CI:3.2–13.7) and 5% (95% CI:2.0–11.4) of health providers demonstrated good knowledge and practice scores respectively, with an overall facility preparedness of 46%. Respondents’ profession as a physician compared to nurses and midwives predicted good knowledge (aOR = 0.08, 95% CI: 0.01–0.69; p = 0.01), but not practice. Conclusion Healthcare provider’s knowledge and practice including facility preparedness for emergency neonatal resuscitation were suboptimal, despite the respondents’ relatively high self-assessed attitudinal perception. Physicians demonstrated higher knowledge compared to other health professionals. The low level of respondents’ awareness, practice, and facility readiness suggest the current weak state of secondary health systems in Kano.

Avaliação da atenção primária em saúde no Brasil: principais características, limitações e potencialidades entre PMAQ e PCATool

Introdução: A Atenção Primária em Saúde (APS) teve o Programa de Melhoria do Acesso e da Qualidade da Atenção Básica (PMAQ-AB) como principal instrumento para avaliar sua qualidade até o fim de 2019. Sendo substituído pelo Primary Care Assessment Tool (PCATool) a partir de 2020. Essa mudança se justificou devido diversas fragilidades nos instrumentos de avaliação e sua aplicação. Objetivo: Identificar as principais características dos instrumentos de avaliação do PMAQ e PCATool, bem como suas potencialidades e limitações no Brasil. Material e método: Trata-se de uma revisão de literatura, de abordagem qualitativa, feita a partir da análise e interpretação dos instrumentos oficiais de avaliação da APS (PMAQ e PCATool), disponibilizados pelo Ministério da Saúde – Brasil, e produções científicas sobre a temática. Resultados e discussão: Percebeu-se como principais diferenças entre os instrumentos, o quantitativo, o formato/tipo, a organização dos itens/questões, bem como o tratamento e análise dos respectivos dados. Quanto as principais similaridades, destaca-se as bases de fundamentação serem relacionadas ao processo de trabalho das equipes e a organização dos serviços. Ambos são aplicados à usuários e profissionais da APS, apesar que o PCATool não inclui o Núcleo de Apoio a Saúde da Família. Conclusão: O instrumento do PMAQ foi considerado mais extenso e complexo que o do PCATool no que tange suas variáveis e aplicação. Não foram encontrados referenciais teóricos que alicerçaram o instrumento do PMAQ. A validação externa das amostras e propriedade psicométricas, além da alta comparabilidade internacional denotam maior robustez e efetividade do PCATool.

Avaliação dos atributos da Atenção Primária à Saúde na perspectiva dos idosos

RESUMO Objetivo avaliar os atributos da Atenção Primária à Saúde na perspectiva dos idosos, na cidade de Sinop em Mato Grosso. Método pesquisa avaliativa, de abordagem quantitativa e delineamento transversal. Utilizou-se o instrumento Primary Care Assessment Tool para entrevista aos 345 idosos. Após entrevista com o instrumento Primary Care Assessment Tool -Brasil, versão usuários, estimou-se o nível de qualidade dos atributos essenciais e derivados sendo considerado satisfatório o escore ≥ 6,6 e insatisfatório < 6,6. A análise foi feita no programa SPSS, versão 19.0. Resultados os atributos Longitudinalidade, Coordenação e Integralidade obtiveram avaliações satisfatórias. O Acesso de Primeiro Contato obteve a pior avaliação na perspectiva dos idosos. Conclusão verifica-se que o acesso de primeiro contato constitui uma barreira a ser transposta na busca de atender às necessidades dos idosos.

Pengaruh token ekonomi untuk meningkatkan kemampuan rawat diri pada individu dengan gangguan skizoafektif

The subject was a 41-year-old woman with a diagnosis of schizoaffective disorder. Subjects showed the symptoms of schizoid that made them less interested in daily activities, less concerned with hygiene and self-care. Assessment methods used are observations, interviews, and psychological tests in the form of WAIS, graphic tests (DAP, BAUM, &HTP), TAT, WWQ and WHODAS questionnaire. Interventions are made to deal with the lack of ability in self-care, using behavior modification therapy with the token economy method. The results showed that Token Economy was effective to improve the subject's ability to care for themselves, they became more motivated to perform basic activities such as self-cleaning.

The Role of AI in Characterizing the DCM Phenotype

Dilated Cardiomyopathy is conventionally defined by left ventricular dilatation and dysfunction in the absence of coronary disease. Emerging evidence suggests many patients remain vulnerable to major adverse outcomes despite clear therapeutic success of modern evidence-based heart failure therapy. In this era of personalized medical care, the conventional assessment of left ventricular ejection fraction falls short in fully predicting evolution and risk of outcomes in this heterogenous group of heart muscle disease, as such, a more refined means of phenotyping this disease appears essential. Cardiac MRI (CMR) is well-placed in this respect, not only for its diagnostic utility, but the wealth of information captured in global and regional function assessment with the addition of unique tissue characterization across different disease states and patient cohorts. Advanced tools are needed to leverage these sensitive metrics and integrate with clinical, genetic and biochemical information for personalized, and more clinically useful characterization of the dilated cardiomyopathy phenotype. Recent advances in artificial intelligence offers the unique opportunity to impact clinical decision making through enhanced precision image-analysis tasks, multi-source extraction of relevant features and seamless integration to enhance understanding, improve diagnosis, and subsequently clinical outcomes. Focusing particularly on deep learning, a subfield of artificial intelligence, that has garnered significant interest in the imaging community, this paper reviews the main developments that could offer more robust disease characterization and risk stratification in the Dilated Cardiomyopathy phenotype. Given its promising utility in the non-invasive assessment of cardiac diseases, we firstly highlight the key applications in CMR, set to enable comprehensive quantitative measures of function beyond the standard of care assessment. Concurrently, we revisit the added value of tissue characterization techniques for risk stratification, showcasing the deep learning platforms that overcome limitations in current clinical workflows and discuss how they could be utilized to better differentiate at-risk subgroups of this phenotype. The final section of this paper is dedicated to the allied clinical applications to imaging, that incorporate artificial intelligence and have harnessed the comprehensive abundance of data from genetics and relevant clinical variables to facilitate better classification and enable enhanced risk prediction for relevant outcomes.

Measuring What Matters Across International Long-Term Care Settings

Measuring what matters most to residents, relatives and staff in residential long-term care settings is critical, yet underdeveloped in our predominantly frailty and deficits-focused measurement frameworks. The Worldwide Elements to Harmonize Research in Long-Term Care Living Environments (WE-THRIVE) consortium has previously prioritized measurement concepts in the areas of care outcomes, workforce and staffing, person-centered care, and care context. These concepts include knowing the resident and what matters most to the resident, and outcomes such as quality of life, and personhood. We present findings of our currently recommended measures, including both general population and dementia-specific measures, such as the Person-Centered Care Assessment Tool (PCAT), the Personhood in Dementia Questionnaire (PDQ), and the ICEpop CAPability Measure for Older People (ICECAP-O). We also describe remaining gaps in existing measures that will need to be addressed to fully specify common data elements focused on measuring what matters most to residents, relatives and staff.