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OBJECTIVE: To present a systematic review of the state of the art regarding clinical applications, main features, and outcomes of artificial intelligence (AI) in orthognathic surgery. METHODS: The PICOS strategy was performed on a systematic review (SR) to answer the following question: "What are the state of the art, characteristics and outcomes of applications with artificial intelligence for orthognathic surgery?" After registering in PROSPERO (CRD42021270789) a systematic search was performed in the databases: PubMed (including MedLine), Scopus, Embase, LILACS, MEDLINE EBSCOHOST and Cochrane Library. 195 studies were selected, after screening titles and abstracts, of which thirteen manuscripts were included in the qualitative analysis and six in the quantitative analysis. The treatment effects were plotted in a Forest-plot. JBI questionnaire for observational studies was used to asses the risk of bias. The quality of the SR evidence was assessed using the GRADE tool. RESULTS: AI studies on 2D cephalometry for orthognathic surgery, the Tau2 = 0.00, Chi2 = 3.78, p = 1.00 and I² of 0 %, indicating low heterogeneity, AI did not differ statistically from control (p = 0.79). AI studies in the diagnosis of the decision of whether or not to perform orthognathic surgery showed heterogeneity, and therefore meta-analysis was not peformed. CONCLUSION: The outcome of AI is similar to the control group, with a low degree of bias, highlighting its potential for use in various applications.

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Uno de los principales problemas durante la dentición mixta es la determinación de la futura discrepancia entre tamaño dentario y el espacio disponible. Para predecir el ancho mesiodistal de los dientes permanentes no erupcionados se han introducido diferentes métodos de análisis. Objetivo: El propósito de este estudio fue comparar el método Tanaka-Johnston con una nueva ecuación de regresión para predecir el ancho mesiodistal de caninos y premolares permanentes no erupcionados en una población de la región de Valparaíso, Chile. Material y método: Este estudio fue realizado en la Facultad de Odontología de la Universidad de Valparaíso, desde octubre de 2022 a junio de 2023 (8 meses), la muestra estuvo compuesta por 202 modelos de estudio del departamento de ortodoncia (91 hombres y 111 mujeres) en el rango de edad de 11 -20 años. Resultados: Se demostró que el método elaborado por Lara-Sandoval presenta mayor fiabilidad respecto a las medidas mesiodistales reales de los pacientes (ICC 0,773 para maxilar y 0,762 para mandíbula), en comparación con el método de Tanaka-Johnston (ICC 0,665 para maxilar y 0,623 para mandíbula). No existen diferencias significativas entre los valores reales y el método de Lara-Sandoval. Conclusión: El método de Lara-Sandoval es mejor que el propuesto por Tanaka-Johnston para determinar el ancho mesiodistal de caninos y premolares para esta muestra. Es necesario validar este método en otras regiones del país para ser utilizado con mayor seguridad que el ya existente como método estándar nacional.

One of the main orthodontic problems in mixed dentition is the determination of future tooth and size arch discrepancy. In order to predict the mesiodistal widths of unerupted permanent teeth different methods of analyses have been introduced. The aim of this study is to compare the Tanaka-Johnston analysis with a new regressive equation to predict the mesiodistal width of unerupted permanent canines and premolars in a Chilean population sample, from Valparaíso region. This study was conducted at the Universidad de Valparaíso Dental Faculty, from october 2022 to june 2023 (8 months), and the sample comprised historical dental casts from 202 patients (91 boys and 111 girls) in the age range of 11-20 from the orthodontics department. All the patients are from the Valparaíso region, Chile. The results show that the predictions of the new regressive equation method are closer to the actual mesiodistal measurements of the patients (ICC 0,773 for maxilla and 0,762 for mandible), compared to the Tanaka- Johnston method (ICC 0,665 for maxilla and 0,623 for mandible). There are no significant differences between the real values and the Lara-Sandoval method. Lara-Sandoval method is better than the one proposed by Tanaka-Johnston to determine the mesiodistal width of canines and premolars in this sample population. It is necessary to validate this method in other regions of the country to be used with greater security than the ones that already exists as a national standard method.

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The incapability to move the facial muscles is known as facial palsy, and it affects various abilities of the patient, for example, performing facial expressions. Recently, automatic approaches aiming to diagnose facial palsy using images and machine learning algorithms have emerged, focusing on providing an objective evaluation of the paralysis severity. This research proposes an approach to analyze and assess the lesion severity as a classification problem with three levels: healthy, slight, and strong palsy. The method explores the use of regional information, meaning that only certain areas of the face are of interest. Experiments carrying on multi-class classification tasks are performed using four different classifiers to validate a set of proposed hand-crafted features. After a set of experiments using this methodology on available image databases, great results are revealed (up to 95.61% of correct detection of palsy patients and 95.58% of correct assessment of the severity level). This perspective leads us to believe that the analysis of facial paralysis is possible with partial occlusions if face detection is accomplished and facial features are obtained adequately. The results also show that our methodology is suited to operate with other databases while attaining high performance, even though the image conditions are different and the participants do not perform equivalent facial expressions.

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The acceptance of artificial intelligence (AI) systems by health professionals is crucial to obtain a positive impact on the diagnosis pathway. We evaluated user satisfaction with an AI system for the automated detection of findings in chest x-rays, after five months of use at the Emergency Department. We collected quantitative and qualitative data to analyze the main aspects of user satisfaction, following the Technology Acceptance Model. We selected the intended users of the system as study participants: radiology residents and emergency physicians. We found that both groups of users shared a high satisfaction with the system's ease of use, while their perception of output quality (i.e., diagnostic performance) differed notably. The perceived usefulness of the application yielded positive evaluations, focusing on its utility to confirm that no findings were omitted, and also presenting distinct patterns across the two groups of users. Our results highlight the importance of clearly differentiating the intended users of AI applications in clinical workflows, to enable the design of specific modifications that better suit their particular needs. This study confirmed that measuring user acceptance and recognizing the perception that professionals have of the AI system after daily use can provide important insights for future implementations.

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The high prevalence of PIMs in elderly is a major healthcare concern and indicates the need for medication monitoring systems. Most PIM CDSS have shown positive effects respecting PIM prescription but these results were more consistently in hospital settings compared with ambulatory care. We describe the post-implementation evaluation of a PIM CDSS for general practitioners (GP) in the ambulatory setting and explore GP interactions with the PIM alerts. The CDSS generated 3218 unique alerts and involved 2863 elderly patients. Benzodiazepines was the drug with the most alerts triggered. Only 129 (4 %) were opened by GP during patient appointments. We need to develop an understanding of how alerts should be designed and display information to support the workflow of general practitioners. Pos-implementation evaluations are the key of CDSS improvements.

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BACKGROUND: The restrictions imposed by the COVID-19 pandemic reduced health service access by patients with chronic diseases. The discontinuity of care is a cause of great concern, mainly in vulnerable regions. OBJECTIVE: This study aimed to assess the impact of the COVID-19 pandemic on people with hypertension and diabetes mellitus (DM) regarding the frequency of consultations and whether their disease was kept under control. The study also aimed to develop and implement a digital solution to improve monitoring at home. METHODS: This is a multimethodological study. A quasiexperimental evaluation assessed the impact of the pandemic on the frequency of consultations and control of patients with hypertension and DM in 34 primary health care centers in 10 municipalities. Then, an implementation study developed an app with a decision support system (DSS) for community health workers (CHWs) to identify and address at-risk patients with uncontrolled hypertension or DM. An expert panel assessment evaluated feasibility, usability, and utility of the software. RESULTS: Of 5070 patients, 4810 (94.87%) had hypertension, 1371 (27.04%) had DM, and 1111 (21.91%) had both diseases. There was a significant reduction in the weekly number of consultations (107, IQR 60.0-153.0 before vs 20.0, IQR 7.0-29.0 after social restriction; P<.001). Only 15.23% (772/5070) of all patients returned for a consultation during the pandemic. Individuals with hypertension had lower systolic (120.0, IQR 120.0-140.0 mm Hg) and diastolic (80.0, IQR 80.0-80.0 mm Hg) blood pressure than those who did not return (130.0, IQR 120.0-140.0 mm Hg and 80.0, IQR 80.0-90.0 mm Hg, respectively; P<.001). Also, those who returned had a higher proportion of controlled hypertension (64.3% vs 52.8%). For DM, there were no differences in glycohemoglobin levels. Concerning the DSS, the experts agreed that the CHWs can easily incorporate it into their routines and the app can identify patients at risk and improve treatment. CONCLUSIONS: The COVID-19 pandemic caused a significant drop in the number of consultations for patients with hypertension and DM in primary care. A DSS for CHW has proved to be feasible, useful, and easily incorporated into their routines.

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Objective: Medication-related errors in patients are among the leading causes of preventable health damage and harm worldwide. In the United States, these errors cause at least one death a day and damage approximately 1.3 million people annually. According to the World Health Organization, the global expenditure on medication-related errors is estimated to be U$ 42 billion per year. In Brazil, the rate of potential drug interactions varies between 28% and 63.6% for primary care patients. The prevalence of drug interactions has increased following an aging population, increased chronic conditions, combined use of different drugs, and increased prescription drugs per patient. Methods: The data used for this study were obtained through the database from Nexodata do Brasil S.A a private health technology company with an electronic prescription system and a data intelligence area. Results: 65,867 electronic prescriptions were evaluated during 2019. Of these, 4,828 prescriptions had an average of 2.5 interactions. These interactive prescriptions were generated by 197 different doctors, totaling 24.5 prescriptions with interaction per doctor over 12 months. A total of 12,005 interactions were identified, 15.6% classified as mild, 70.9% as moderate, and 13.5% as severe. Conclusion: By implementing an electronic prescription tool, a reduction of 32.9% in the number of prescriptions with drug interaction was observed.

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Introdução: A pandemia da COVID-19 representa um grande desafio para os sistemas de saúde de todo o mundo, com demandas sem precedentes em todos os níveis de atenção à saúde. Na atenção primária, além do cuidado dos indivíduos com sintomas gripais, a descontinuidade do acompanhamento de pacientes com doenças crônicas é causa de grande preocupação. Na atenção hospitalar, a necessidade imediata de assistir pacientes com formas graves e críticas da COVID-19, exigiu ampliação de leitos convencionais e de cuidados intensivos, recursos tecnológicos para suporte avançado de vida e capacitação em tempo recorde, à medida que avançavam os conhecimentos sobre a doença. Objetivos: O presente trabalho possui dois objetivos principais. Objetivo 1: Avaliar o impacto da pandemia da COVID-19 em uma coorte de pessoas com hipertensão e diabetes na atenção primária, além de desenvolver e implementar uma solução digital para melhorar o monitoramento no domicílio. Objetivo 2: Avaliar se o escore de risco ABC2-SPH é capaz de predizer a necessidade de ventilação mecânica em pacientes com COVID-19 e comparar seu desempenho ao de outros escores desenvolvidos para predizer ventilação mecânica, mortalidade e outros desfechos, inclusive em pacientes não COVID. Métodos: Para alcançar o objetivo 1: Foi desenvolvido um estudo multimetodológico. Uma avaliação quasi-experimental analisou o impacto da pandemia na frequência de consultas e controle de pacientes com hipertensão e diabetes em 34 unidades básicas de saúde (UBS) em 10 municípios do Vale do Mucuri, Minas Gerais, entre junho de 2017 e dezembro de 2020, considerando como ponto de corte o dia 14 de março de 2020, quando as medidas de restrição social tiveram início. Em seguida, um estudo de factibilidade desenvolveu um aplicativo com um sistema de apoio à decisão (SAD) para agentes comunitários de saúde (ACS) para identificar, durante a visita domiciliar, pacientes com hipertensão arterial (HAS) e/ou diabetes mellitus (DM) não controlados e referenciá-los para atendimento presencial na UBS. Um painel de especialistas avaliou a viabilidade, usabilidade e utilidade do aplicativo através de questionário específico. Para alcançar o objetivo 2: Estudo de coorte retrospectiva, derivado do estudo originalmente chamado "Avaliação do perfil laboratorial, radiológico e sintomatológico de pacientes infectados com o novo coronavírus 2019 (SARS-CoV-2) em hospitais do estado de Minas Gerais" que se tornou um estudo multicêntrico, realizado em 31 hospitais, em 17 cidades de cinco estados. O estudo incluiu pacientes que foram internados em dois períodos: março a setembro de 2020 e março a dezembro de 2021, com diagnóstico de COVID-19 confirmado. Neste estudo, o escore de risco ABC2-SPH, desenvolvido para predição de mortalidade intra-hospitalar por COVID-19, foi avaliado quanto à possibilidade de predizer a necessidade de ventilação mecânica e comparado a outros escores: CALL, PREDI-CO, SUM, STSS, COVID_IRS_NLR, CURB-65, SOFA e 4C Mortality Score. Resultados: Objetivo 1: Dos 5070 pacientes, 4810 (94,9%) tinham HAS, 1371 (27,4%) tinham DM e 1111 (23,1%) tinham as duas doenças. Houve redução significativa no número de consultas semanais quando comparados o período antes e depois do início das medidas de restrição social (107 [IQR 60,0, 153,0] vs 20,0 [IQR 7,0, 29,0], respectivamente, p <0,001. Apenas 15,2% de todos os pacientes retornaram para consulta durante a pandemia. Indivíduos com HAS que retornaram tinham níveis de pressão arterial sistólica (120,0 [IQR 120,0-140,0]) e diastólica (80,0 [IQR 80,0-80,0]) menores do que os níveis apresentados antes da pandemia por aqueles que não retornaram (130,0 [IQR 120,0-140,0] e 80,0 [IQR 80,0-90,0]), p<0,001. Além disso, aqueles que retornaram tiveram uma proporção maior de HAS controlada (64,3% vs 52,8%). Para o DM, não houve diferenças nos níveis de glicohemoglobina. Em relação ao SAD, os especialistas concordaram que os ACS podem incorporá-lo facilmente em suas rotinas e o aplicativo pode identificar pacientes em risco e melhorar o tratamento. Objetivo 2: Ao longo do estudo, foram incluídos 4.831 pacientes, com idade mediana de 59,0 (IQR 48,0, 70,0) anos e 46,3% do sexo feminino. Destes, 34,2% necessitaram de tratamento intensivo, 26,6% necessitaram de VMI e 18,7% faleceram. Os pacientes que necessitaram de VMI apresentaram maior prevalência de HAS, DM, obesidade e mortalidade quando comparados aos que não necessitaram (64,3% vs 2,3%, p<0,001). Com base no conjunto de dados imputados, o ABC2-SPH apresentou AUROC 0,677 (IC 95% 0,681-0,694). Considerando apenas os casos completos, a AUROC foi de 0,70 (IC 95% 0,68-0,72), tendo o melhor desempenho entre os escores com amostras maiores de casos completos. No geral, as discriminações dos escores foram de regular a ruim. O SOFA Score teve a maior sensibilidade, 0,84 (IC 95% 0,81-0,86). O escore SOFA teve a maior sensibilidade 0,84 (IC 95% 0,81-0,86). Conclusões: A pandemia da COVID-19 causou uma queda significativa no número de consultas de pacientes com HAS e DM na atenção primária. Um SAD para ACS mostrou-se viável e útil para identificar pacientes descontrolados em casa. O escore ABC2-SPH demonstrou melhor desempenho do que os outros escores, mas não com precisão suficiente para prever com segurança a necessidade de ventilação mecânica em pacientes hospitalizados com COVID-19. Novos estudos devem ser realizados para desenvolver escores fáceis de aplicar que tenham melhor calibração e discriminação para auxiliar na difícil decisão de instituir o suporte ventilatório avançado.

Introduction: The COVID-19 pandemic represents a major challenge for health systems around the world, with unprecedented demands on all levels of health care. In primary care, in addition to the care of individuals with flu-like symptoms, the discontinuity of monitoring patients with chronic diseases is a cause of great concern. In hospital care, the immediate need to assist patients with severe and critical forms of COVID-19 required the expansion of conventional and intensive care beds, technological resources for advanced life support and training in record time, as knowledge about the disease evolved. Objectives: The present study has two main objectives. Objective 1: To assess the impact of the COVID-19 pandemic on a cohort of people with hypertension and diabetes in primary care, and to develop and implement a digital solution to improve home monitoring. Objective 2: To assess whether the ABC2-SPH risk score can predict the need for invasive mechanical ventilation (IMV) in patients with COVID-19 and to compare its performance with other scores developed to predict IMV, mortality and other outcomes, including in non-COVID patients. Methods: To achieve objective 1: A multi-methodological study was developed. A quasi-experimental evaluation analyzed the impact of the pandemic on the frequency of consultations and control of patients with hypertension and diabetes in 34 primary health care centers (PHCC) in 10 municipalities in Mucuri Valley (Vale do Mucuri), Minas Gerais, between June 2017 and December 2020, considering March 14, 2020, as the cut-off point, when social restriction measures began. Then, a feasibility study developed an application with a decision support system (DSS) for community health workers (CHW) to identify, during home visits, patients with uncontrolled hypertension and/or diabetes and refer them for in person consultation at the PHCC. A panel of experts evaluated the app's feasibility, usability and usefulness through a specific questionnaire. To achieve objective 2: Retrospective cohort study, derived from the study originally called "Evaluation of the laboratory, radiological and symptomatologic profile of patients infected with the new coronavirus 2019 (SARS-CoV-2) in hospitals in the state of Minas Gerais", which became a multicenter study, carried out in 31 hospitals, in 17 cities in five states The study included patients who were hospitalized in two periods: March to September 2020 and March to December 2021, with a confirmed diagnosis of COVID-19 . In this study, the ABC2-SPH risk score, developed to predict in-hospital mortality from COVID-19, was evaluated for the possibility of predicting the need for mechanical ventilation and compared to other scores: CALL, PREDI-CO, SUM, STSS, COVID_IRS_NLR, CURB-65, SOFA and 4C Mortality Score Results: Objective 1: Of 5070 patients, 4810 (94.9%) had hypertension, 1371 (27.4%) had DM, and 1111 (23.1%) had both diseases. There was a significant reduction in the weekly number of consultations (107, IQR 60.0-153.0 before vs 20.0, IQR 7.0-29.0) after social restriction; P<.001. Only 15.2% (772/5070) of all patients returned for a consultation during the pandemic. Individuals with hypertension had lower systolic (120.0, IQR 120.0-140.0 mm Hg) and diastolic (80.0, IQR 80.0-80.0 mmHg) blood pressure than those who did not return (130.0, IQR 120.0-140.0 mm Hg) and (80.0, IQR 80.0-90.0 mm Hg; P<.001). Also, those who returned had a higher proportion of controlled hypertension (64.3% vs 52.8%). For DM, there were no differences in glycohemoglobin levels. Concerning the DSS, the experts agreed that the CHWs can easily incorporate it into their routines and the app can identify patients at risk and improve treatment. Objective 2: Throughout the study, 4831 patients were included, median age 59.0 (IQR 48.0, 70.0) years-old and 46.3% female. Of those, 34.2 % required intensive care treatment, 26.6% required IMV and 18.7% died. Patients who required IMV had higher prevalence of hypertension, diabetes, obesity, and mortality when compared to those who did not require it (64.3% vs 2.3%, p<0.001). Based on the imputed dataset, the ABC2-SPH AUROC was 0.677 (95% CI 0.681-0.694). Considering only complete cases, the AUROC was 0.70, having the best performance among scores that had larger samples of complete cases. When the data were imputed, was 0.67. Considering only complete cases, the AUROC was 0.70 (95% CI 0.68-0.72, having the best performance among scores that had larger samples of complete cases. Overall, the score discriminations ranged from poor to fair. The SOFA Score had the highest sensitivity, 0.84 (95% CI 0.81-0.86). Conclusions: The COVID-19 pandemic caused a significant drop in the number of consultations of patients with hypertension and diabetes in primary care. An SSD for CHW proved to be feasible and useful for identifying uncontrolled patients at home. ABC2-SPH demonstrated better performance than the other scores, but not accurately enough to reliably predict the need for IMV COVID-19 hospitalized patients. Research should continue to develop easy-to-use scores with better calibration and discrimination, given the importance of assisting clinicians in decision-making when initiating advanced ventilatory support.

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Patient safety.Estudo transversal. Objetivo: avaliar a sensibilidade e especificidade de sistemas de rastreamento de acesso aberto para interações medicamentosas potenciais (IMp) em comparação com o DRUG-REAX® system e analisar o impacto clínico potencial das IMp de gravidades "Contraindicada" e "Maior" não detectadas. Métodos: amostra composta por 140 pacientes em acompanhamento em um ambulatório especializado no atendimento a pessoas com doenças crônicas não transmissíveis (DCNT) de um hospital universitário. As IMp foram identificadas e classificadas no DRUG-REAX® System e em oito sistemas de rastreamento de acesso aberto. As IMp de gravidade "Contraindicada" e "Maior" foram analisadas segundo o impacto clínico. Utilizou-se estatística descritiva e calculou-se sensibilidade e especificidade dos sistemas de rastreamento na identificação das IMp. Resultados: Os sistemas de acesso aberto pertencentes as bases Drugs.com, UCLA School of Health e CVC Caremark apresentaram sensibilidade e especificidade > 70%. A totalidade dos sistemas de acesso aberto não detectou os pares ciprofibrato + estatinas e metformina + sitagliptina, cujos impactos clínicos incluíram risco de miopatia e rabdomiólise e hipoglicemia, respectivamente. Cerca de um terço (37,5%) dos sistemas de acesso aberto não detectou a IMp ácido acetilsalicílico + hidroclorotiazida, capaz de ocasionar nefrotoxicidade. Conclusão: A maioria dos pares de IMp integra o rol terapêutico de pacientes com DCNT e cujos impactos clínicos são tempo-dependentes. A combinação de julgamento clínico, revisão periódica do plano terapêutico e os atributos de precisão (sensibilidade e especificidade) são fundamentais para garantir a segurança do paciente, sobretudo no contexto ambulatorial. (AU)

This study aims to evaluate the sensitivity and specificity of open-access screening systems in detecting potential drug-drug interactions (PDDIs) compared to the DRUG-REAX® system and analyze the potential clinical impact of PDDIs of "Contraindicated" and "Major" severities not detected. A cross-sectional study was conducted in an outpatient clinic specialized in caring for patients with noncommunicable diseases (NCDs) of a university hospital. PDDIs were identified and classified in the DRUG-REAX® System and eight open-access screening systems. The "Contraindicated" and "Major" severity PDDIs were analyzed according to clinical impact. Descriptive statistics were used and the sensitivity and specificity of the screening systems were calculated to identify the PDDIs. Results: The open-access systems Drugs.com, UCLA School of Health and CVC Caremark showed sensitivity and specificity > 70%. All open access systems did not detect the pairs ciprofibrate + statins and metformin + sitagliptin, whose clinical impacts included the risk of myopathy/ rhabdomyolysis and hypoglycemia, respectively. About a third (37.5%) of open-access systems did not detect PDDI acetylsalicylic acid + hydrochlorothiazide, which is capable of causing nephrotoxicity. Conclusion: Most pairs of PDDIs are part of the therapeutic role of patients with NCDs and whose clinical impacts are time-dependent. The combination of clinical judgment, periodic review of the therapeutic plan and the attributes of precision (sensitivity and specificity) are essential to ensure patient safety, especially in the outpatient setting. (AU)

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OBJECTIVES: Advanced clinical decision support tools, such as real-time risk analytic algorithms, show promise in assisting clinicians in making more efficient and precise decisions. These algorithms, which calculate the likelihood of a given underlying physiology or future event, have predominantly been used to identify the risk of impending clinical decompensation. There may be broader clinical applications of these models. Using the inadequate delivery of oxygen index, a U.S. Food and Drug Administration-approved risk analytic algorithm predicting the likelihood of low cardiac output state, the primary objective was to evaluate the association of inadequate delivery of oxygen index with success or failure of weaning vasoactive support in postoperative cardiac surgery patients. DESIGN: Multicenter retrospective cohort study. SETTING: Three pediatric cardiac ICUs at tertiary academic children's hospitals. PATIENTS: Infants and children greater than 2 kg and less than 12 years following cardiac surgery, who required vasoactive infusions for greater than 6 hours in the postoperative period. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Postoperative patients were identified who successfully weaned off initial vasoactive infusions (n = 2,645) versus those who failed vasoactive wean (required reinitiation of vasoactive, required mechanical circulatory support, renal replacement therapy, suffered cardiac arrest, or died) (n = 516). Inadequate delivery of oxygen index for final 6 hours of vasoactive wean was captured. Inadequate delivery of oxygen index was significantly elevated in patients with failed versus successful weans (inadequate delivery of oxygen index 11.6 [sd 19.0] vs 6.4 [sd 12.6]; p < 0.001). Mean 6-hour inadequate delivery of oxygen index greater than 50 had strongest association with failed vasoactive wean (adjusted odds ratio, 4.0; 95% CI, 2.5-6.6). In patients who failed wean, reinitiation of vasoactive support was associated with concomitant fall in inadequate delivery of oxygen index (11.1 [sd 18] vs 8.9 [sd 16]; p = 0.007). CONCLUSIONS: During the de-escalation phase of postoperative cardiac ICU management, elevation of the real-time risk analytic model, inadequate delivery of oxygen index, was associated with failure to wean off vasoactive infusions. Future studies should prospectively evaluate utility of risk analytic models as clinical decision support tools in de-escalation practices in critically ill patients.

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PURPOSE: To analyze the accuracy of nursing diagnoses determined by users of a clinical decision support system (CDSS) and to identify the predictive factors of high/moderate diagnostic accuracy. METHODS: This is an exploratory-descriptive study carried out from September 2017 to January 2018. Participants were nurses, resident nurses, and senior year undergraduates. Two written case studies provided the participants with the clinical data to fill out the assessment forms in the CDSS. The accuracy of the selected diagnostic labels was determined by a panel of experts using the Diagnostic Accuracy Scale, Version 2. Descriptive statistics were used to describe the level of accuracy according to each group of participants. Analysis of variance was used to compare the mean percentages of accuracy categories across groups. A linear regression model was used to identify the predictors of diagnostic accuracy. The significance level was 5%. The study was approved by the Ethics Committee. RESULTS: Fifteen undergraduates, 10 residents, and 22 nurses were enrolled in the study. Although resident nurses and students had selected predominantly highly accurate diagnoses (51.8 ± 19.1 and 48.9 ± 27.4, respectively), and nurses had selected mostly diagnoses of moderate accuracy (54.7 ± 14.7), there were no differences in the accuracy level of selected diagnoses across groups. According to the linear regression model, each diagnosis added by the participants decreased the diagnostic accuracy by 2.09% (p = .030), and no experience or a low level of experience using the system decreased such diagnostic accuracy by 5.41% (p = .022). CONCLUSIONS: The CDSS contributes to decision making about diagnoses of less experienced people. Adding diagnoses not indicated by the CDSS and experience with the system are predictors of diagnostic accuracy. CLINICAL RELEVANCE: In-service education regarding the use of CDSSs seems to be crucial to improve users' clinical judgment and decision making.

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BACKGROUND: The low levels of control of hypertension and diabetes mellitus are a challenge that requires innovative strategies to surpass barriers of low sources, distance, and quality of health care. OBJECTIVE: The aim of this study is to develop a clinical decision support system (CDSS) for diabetes and hypertension management in primary care, to implement it in a resource-constrained region, and to evaluate its usability and health care practitioner satisfaction. METHODS: This mixed methods study is a substudy of HealthRise Brazil Project, a multinational study designed to implement pilot programs to improve screening, diagnosis, management, and control of hypertension and diabetes among underserved communities. Following the identification of gaps in usual care, a team of clinicians established the software functional requirements. Recommendations from evidence-based guidelines were reviewed and organized into a decision algorithm, which bases the CDSS reminders and suggestions. Following pretesting and expert panel assessment, pilot testing was conducted in a quasi-experimental study, which included 34 primary care units of 10 municipalities in a resource-constrained area in Brazil. A Likert-scale questionnaire evaluating perceived feasibility, usability, and utility of the application and professionals' satisfaction was applied after 6 months. In the end-line assessment, 2 focus groups with primary care physicians and nurses were performed. RESULTS: A total of 159 reminders and suggestions were created and implemented for the CDSS. At the 6-month assessment, there were 1939 patients registered in the application database and 2160 consultations were performed by primary care teams. Of the 96 health care professionals who were invited for the usability assessment, 26% (25/96) were physicians, 46% (44/96) were nurses, and 28% (27/96) were other health professionals. The questionnaire included 24 items on impressions of feasibility, usability, utility, and satisfaction, and presented global Cronbach α of .93. As for feasibility, all professionals agreed (median scores of 4 or 5) that the application could be used in primary care settings and it could be easily incorporated in work routines, but physicians claimed that the application might have caused significant delays in daily routines. As for usability, overall evaluation was good and it was claimed that the application was easy to understand and use. All professionals agreed that the application was useful (score 4 or 5) to promote prevention, assist treatment, and might improve patient care, and they were overall satisfied with the application (median scores between 4 and 5). In the end-line assessment, there were 4211 patients (94.82% [3993/4211] with hypertension and 24.41% [1028/4211] with diabetes) registered in the application's database and 7960 consultations were performed by primary health care teams. The 17 participants of the focus groups were consistent to affirm they were very satisfied with the CDSS. CONCLUSIONS: The CDSS was applicable in the context of primary health care settings in low-income regions, with good user satisfaction and potential to improve adherence to evidence-based practices.

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BACKGROUND: Displeasure with the functionality of clinical decision support systems (CDSSs) is considered the primary challenge in CDSS development. A major difficulty in CDSS design is matching the functionality to the desired and actual clinical workflow. Computer-interpretable guidelines (CIGs) are used to formalize medical knowledge in clinical practice guidelines (CPGs) in a computable language. However, existing CIG frameworks require a specific interpreter for each CIG language, hindering the ease of implementation and interoperability. OBJECTIVE: This paper aims to describe a different approach to the representation of clinical knowledge and data. We intended to change the clinician's perception of a CDSS with sufficient expressivity of the representation while maintaining a small communication and software footprint for both a web application and a mobile app. This approach was originally intended to create a readable and minimal syntax for a web CDSS and future mobile app for antenatal care guidelines with improved human-computer interaction and enhanced usability by aligning the system behavior with clinical workflow. METHODS: We designed and implemented an architecture design for our CDSS, which uses the model-view-controller (MVC) architecture and a knowledge engine in the MVC architecture based on XML. The knowledge engine design also integrated the requirement of matching clinical care workflow that was desired in the CDSS. For this component of the design task, we used a work ontology analysis of the CPGs for antenatal care in our particular target clinical settings. RESULTS: In comparison to other common CIGs used for CDSSs, our XML approach can be used to take advantage of the flexible format of XML to facilitate the electronic sharing of structured data. More importantly, we can take advantage of its flexibility to standardize CIG structure design in a low-level specification language that is ubiquitous, universal, computationally efficient, integrable with web technologies, and human readable. CONCLUSIONS: Our knowledge representation framework incorporates fundamental elements of other CIGs used in CDSSs in medicine and proved adequate to encode a number of antenatal health care CPGs and their associated clinical workflows. The framework appears general enough to be used with other CPGs in medicine. XML proved to be a language expressive enough to describe planning problems in a computable form and restrictive and expressive enough to implement in a clinical system. It can also be effective for mobile apps, where intermittent communication requires a small footprint and an autonomous app. This approach can be used to incorporate overlapping capabilities of more specialized CIGs in medicine.

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30% of the Argentinian population and 58% of Plan de Salud HIBA patients are unaware of their HIV status. The Ministry of Health and US Preventive Service Task recommends physicians to assess HIV infection in persons aged 15 to 65. An HIV screening reminder integrated in an electronic health record (EHR) was created using FHIR to represent clinical information and CDS-Hooks to represent the exchange of information with a CDS service. The tool had a 1% intervention rate, and 67.4% acceptance rate. The number of HIV screening tests requested during the weeks after the CDSS implementation and in the same period in 2017 were obtained. 575 orders were requested in the 2017 period and 893 in the 2018. 89 (almost 10%) of these came from the electronic tool. The preliminary results indicate that this non disruptive, action oriented reminder can contribute to increased HIV screening orders.

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Clinical evaluation of the patient and the follow-up of the rehabilitation process are pillars of physical therapy care. The SIAVA-FIS decision support system is presented, which accesses graphical evaluation and evolution data, allowing physical therapists to follow the results of the therapeutic procedures in a mobile and web platform. Results indicate that SIAVA-FIS meets physical therapists' needs and that usability presents effectiveness, efficiency and satisfaction in the use of tasks evaluated by users.

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BACKGROUND: Clinical reasoning is an essential skill in physicians, required to address the challenges of accurate patient diagnoses. The goal of the study was to compare the diagnostic accuracy in Family Medicine residents, with and without the use of a clinical decision support tool (DXplain http://www.mghlcs.org/projects/dxplain). METHODS: A total of 87 first-year Family Medicine residents, training at the National Autonomous University of Mexico (UNAM) Postgraduate Studies Division in Mexico City, participated voluntarily in the study. They were randomized to a control group and an intervention group that used DXplain. Both groups solved 30 clinical diagnosis cases (internal medicine, pediatrics, gynecology and emergency medicine) in a multiple-choice question test that had validity evidence. RESULTS: The percent-correct score in the Diagnosis Test in the control group (44 residents) was 74.1±9.4 (mean±standard deviation) whereas the DXplain intervention group (43 residents) had a score of 82.4±8.5 (p<0.001). There were significant differences in the four knowledge content areas of the test. CONCLUSIONS: Family Medicine residents have appropriate diagnostic accuracy that can improve with the use of DXplain. This could help decrease diagnostic errors, improve patient safety and the quality of medical practice. The use of clinical decision support systems could be useful in educational interventions and medical practice.

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Resumen: Se desarrolló un sistema basado en árboles de decisión con factores de peso heurísticos orientados al diagnóstico mediante termografía mamaria. El sistema de apoyo a la toma de decisiones clínicas propuesto incluye árboles de decisión binarios para la clasificación estadística de algunas patologías de la glándula mamaria. Dentro de ellos, se incluyen factores de peso constantes encontrados a través de la correlación de las variables involucradas en el desarrollo de los padecimientos mamarios de acuerdo al apego estadístico de las características termográficas, así como de la información clínica complementaria (historial clínico, parámetros físicos, carga genética y hábitos, entre otros), con respecto a su incidencia diagnóstica. La certeza del sistema para los trastornos inflamatorios es de 96 %, para mastopatía fibroquística de 78 %, para necrosis grasa de 62 % y para cáncer de seno de 86 %. El 14 % de error se asocia a microcalcificaciones mismas que con la técnica termográfica reportada no es posible diferenciar. Por lo tanto, es posible catalogar el riesgo de una paciente a padecer alguna afección según los resultados arrojados después de llevar a cabo el examen térmico. Con este sistema de apoyo a la decisión se mejora la posibilidad de aplicación de pruebas de detección temprana en la población que sufre de contraindicaciones para realizarse los exámenes con otros métodos, además permite un diagnóstico integral para las demás pacientes.

Abstract: A decision tree based system with heuristic weight factors oriented to diagnosis by thermography was developed. The proposed clinical decision support system (CDSS) includes binary decision trees for statistical classification of some diseases of the mammary gland. These include weight constant factors found by the correlation of the variables involved in the development of breast disorders according to the statistical attachment of the thermal features, as well as complementary clinical information (medical history, physical parameters, genetic load and habits, among others), regarding its diagnostic incidence. The certainty of the system for inflammatory disorders is 96%, for fibrocystic mastopathy is 78 %, for fat necrosis is 62% and for breast cancer is 86%. The 14% error is associated to microcalcifications that with the reported thermographic technique it is not possible to differentiate. Thus, it is possible to catalog the risk of a patient having a condition according to the results obtained after conducting a thermal test. Then, with the CDSS the possibility of applying early detection tests in the population suffering from contraindications to perform the others is improved, in addition it allows a comprehensive diagnosis for other patients.

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OBJECTIVES: The objective of this study was to evaluate whether the severity of deformities in patients with adolescent idiopathic scoliosis contributes to patients’ decision regarding whether to undergo an operation. METHODS: We evaluated body image factors in adolescent idiopathic scoliosis patients. We evaluated the magnitude of the main scoliotic curve, gibbosity (magnitude and location), shoulder height asymmetry and patient’s age. We analyzed the correlation of these data with the number of years the patient was willing to trade for surgery, as measured by the time-trade-off method. RESULTS: A total of 52 patients were studied. We did not find a correlation between any of the parameters that were studied and the number of years that the patient would trade for the surgery. CONCLUSIONS: The magnitude of body deformities in patients with adolescent idiopathic scoliosis does not interfere with the decision to undertake surgical treatment.

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BACKGROUND: This literature review covers original journal papers published between 2011 and 2015. These papers review the current status of research on the application of human factors and ergonomics in risk assessment systems' design to cope with the complexity, singularity, and danger in patient triage in primary health care. OBJECTIVE: This paper presents a systematic literature review that aims to identify, analyze, and interpret the application of available evidence from human factors and ergonomics to the design of tools, devices, and work processes to support risk assessment in the context of health care. METHODS: Electronic search was performed on 7 bibliographic databases of health sciences, engineering, and computer sciences disciplines. The quality and suitability of primary studies were evaluated, and selected papers were classified according to 4 classes of outcomes. RESULTS: A total of 1845 papers were retrieved by the initial search, culminating in 16 selected for data extraction after the application of inclusion and exclusion criteria and quality and suitability evaluation. CONCLUSIONS: Results point out that the study of the implications of the lack of understanding about real work performance in designing for risk assessment in health care is very specific, little explored, and mostly focused on the development of tools.

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BACKGROUND: COPD is a major cause of death and morbidity worldwide, and is characterized by persistent airflow obstruction. The evaluation of obstruction is critically dependent on sensitive methods for lung-function testing. A wide body of knowledge has been accumulated in recent years showing that these methods have been significantly refined and seems promising for detection of early disease. OBJECTIVES: This review focuses on research on pulmonary function analysis in COPD performed in Brazil during this century. MATERIALS AND METHODS: The literature was searched using a systematic search strategy limited to English language studies that were carried out in Brazil from the year 2000 onward, with study objectives that included a focus on lung function. RESULTS: After we applied our inclusion and exclusion criteria, 94 articles addressed our stated objectives. Among the new methods reviewed are the forced-oscillation technique and the nitrogen-washout test, which may provide information on small-airway abnormalities. Studies investigating the respiratory muscles and thoracoabdominal motion are also discussed, as well as studies on automatic clinical decision-support systems and complexity measurements. We also examined important gaps in the present knowledge and suggested future directions for the cited research fields. CONCLUSION: There is clear evidence that improvements in lung-function methods allowed us to obtain new pathophysiological information, contributing to improvement in our understanding of COPD. In addition, they may also assist in the diagnosis and prevention of COPD. Further investigations using prospective and longitudinal design may be of interest to elucidate the use of these new methods in the diagnosis and prevention of COPD.

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