Clinical Epidemiology of Buruli ulcer from Benin (2005-2013): effect of time-delay to diagnosis on clinical forms and severe phenotypes

Buruli Ulcer (BU) is a neglected infectious disease caused by Mycobacterium ulcerans that is responsible for severe necrotizing cutaneous lesions that may be associated with bone involvement. Clinical presentations of BU lesions are classically classified as papules, nodules, plaques and edematous infiltration, ulcer or osteomyelitis. Within these different clinical forms, lesions can be further classified as severe forms based on focality (multiple lesions), lesions' size (>15 cm diameter) or WHO Category (WHO Category 3 lesions). There are studies reporting an association between delay in seeking medical care and the development of ulcerative forms of BU or osteomyelitis, but the effect of time-delay on the emergence of lesions classified as severe has not been addressed. To address both issues, and in a cohort of laboratory-confirmed BU cases, 476 patients from a medical center in Allada, Benin, were studied. In this laboratory-confirmed cohort, we validated previous observations, demonstrating that time-delay is statistically related to the clinical form of BU. Indeed, for non-ulcerated forms (nodule, edema, and plaque) the median time-delay was 32.5 days (IQR 30.0-67.5), while for ulcerated forms it was 60 days (IQR 20.0-120.0) (p = 0.009), and for bone lesions, 365 days (IQR 228.0-548.0). On the other hand, we show here that time-delay is not associated with the more severe phenotypes of BU, such as multi-focal lesions (median 90 days; IQR 56-217.5; p = 0.09), larger lesions (diameter >15 cm) (median 60 days; IQR 30-120; p = 0.92) or category 3 WHO classification (median 60 days; IQR 30-150; p = 0.20), when compared with unifocal (median 60 days; IQR 30-90), small lesions (diameter =15 cm) (median 60 days; IQR 30-90), or WHO category 1+2 lesions (median 60 days; IQR 30-90), respectively. Our results demonstrate that after an initial period of progression towards ulceration or bone involvement, BU lesions become stable regarding size and focal/multi-focal progression. Therefore, in future studies on BU epidemiology, severe clinical forms should be systematically considered as distinct phenotypes of the same disease and thus subjected to specific risk factor investigation.

O quotidiano do hospital de S. Marcos de Braga na Idade Moderna

Instituição administrada pela Misericórdia de Braga desde meados do século XVI, o hospital de S. Marcos tornou-se ao longo da Idade Moderna um importante local de tratamento ao corpo e de salvação da alma para doentes pobres, recebendo enfermos de todo o arcebispado, mas também de outras partes do reino e mesmo do estrangeiro. Os cuidados prestados ao corpo e à alma exigiam equipas de trabalho, a aquisição de bens e uma administração que fizesse cumprir as regras existentes. O nosso estudo procurará analisar as relações de sociabilidade existentes no interior do hospital, a aquisição de bens, nomeadamente para as enfermarias, a cozinha e a igreja, a alimentação dos enfermos, os cuidados médicos e a caridade dispensada a quem estava doente e era pobre. Pretende-se dar a conhecer o funcionamento e as vivências de uma instituição que, progressivamente, foi ocupando um lugar cada vez mais importante na cidade.

Segmentação do tecido tumoral cerebral em imagens de ressonância magnética

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Treating the entire person

[Excerpt] A critical case from a Portuguese hospital reveals how the ultimate healthcare customer, the patient, is a complete system, not a jumble of parts. (...) The lean production philosophy has made inroads into service sectors, including medical care in the United Kingdom and the United States. Unfortunately, numerous medical organizations in those two countries and the rest of the world treat patients like they are made up of parts, not as a whole system. This leads to disjointed handoffs, bottlenecks in information flow that delay treatment, and sending the patient back and forth from department to department. The following case in Portugal shows how most of the world’s health systems still suffer from functional silos and how waste is all over the place. In this case, the missing links in communication between doctors, nurses, auxiliary staff, the patient and her family led to the patient’s death. Adopting lean healthcare with its proven tools would be a solution to many of the problems described. When a patient dies in a hospital, the family often is told that the doctors did everything they could. Normally, that is the case, as healthcare providers – doctors, nurses, auxiliary staff, therapists – do their best with the system they have.

A intervenção precoce: uma aliada dos cuidados de saúde prestados nas Unidades de Cuidados Intensivos Neonatais?

Dissertação de mestrado em Educação Especial (área de especialização em Intervenção Precoce)

Child abuse monitor system model: a health care critical knowledge monitor system

The Childhood protection is a subject with high value for the society, but, the Child Abuse cases are difficult to identify. The process from suspicious to accusation is very difficult to achieve. It must configure very strong evidences. Typically, Health Care services deal with these cases from the beginning where there are evidences based on the diagnosis, but they aren’t enough to promote the accusation. Besides that, this subject it’s highly sensitive because there are legal aspects to deal with such as: the patient privacy, paternity issues, medical confidentiality, among others. We propose a Child Abuses critical knowledge monitor system model that addresses this problem. This decision support system is implemented with a multiple scientific domains: to capture of tokens from clinical documents from multiple sources; a topic model approach to identify the topics of the documents; knowledge management through the use of ontologies to support the critical knowledge sensibility concepts and relations such as: symptoms, behaviors, among other evidences in order to match with the topics inferred from the clinical documents and then alert and log when clinical evidences are present. Based on these alerts clinical personnel could analyze the situation and take the appropriate procedures.

Clustering-based approach for categorizing pregnant women in obstetrics and maternity care

When a pregnant woman is guided to a hospital for obstetrics purposes, many outcomes are possible, depending on her current conditions. An improved understanding of these conditions could provide a more direct medical approach by categorizing the different types of patients, enabling a faster response to risk situations, and therefore increasing the quality of services. In this case study, the characteristics of the patients admitted in the maternity care unit of Centro Hospitalar of Porto are acknowledged, allowing categorizing the patient women through clustering techniques. The main goal is to predict the patients’ route through the maternity care, adapting the services according to their conditions, providing the best clinical decisions and a cost-effective treatment to patients. The models developed presented very interesting results, being the best clustering evaluation index: 0.65. The evaluation of the clustering algorithms proved the viability of using clustering based data mining models to characterize pregnant patients, identifying which conditions can be used as an alert to prevent the occurrence of medical complications.

Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.

Step towards a patient timeline in intensive care units

In Intensive Medicine, the presentation of medical information is done in many ways, depending on the type of data collected and stored. The way in which the information is presented can make it difficult for intensivists to quickly understand the patient's condition. When there is the need to cross between several types of clinical data sources the situation is even worse. This research seeks to explore a new way of presenting information about patients, based on the timeframe in which events occur. By developing an interactive Patient Timeline, intensivists will have access to a new environment in real-time where they can consult the patient clinical history and the data collected until the moment. The medical history will be available from the moment in which patients is admitted in the ICU until discharge, allowing intensivist to examine data regarding vital signs, medication, exams, among others. This timeline also intends to, through the use of information and models produced by the INTCare system, combine several clinical data in order to help diagnose the future patients’ conditions. This platform will help intensivists to make more accurate decision. This paper presents the first approach of the solution designed

Level of compliance in contact lens wearing medical doctors in Nepal

PURPOSES: To determine the level of compliance and major non-compliant behaviors in contact lens (CL) wearing medical doctors (MDs) and to compare it with age matched CL wearing normal subjects with no medical background (NS). METHODS: Thirty-nine current CL wearing MDs, who were prescribed CLs in Nepal Eye Hospital, Kathmandu, Nepal, between 2007 and 2011, were interviewed on ten modifiable compliant behaviors regarding lens care and maintenance. The level of compliance and the rate of non-compliance for each behavior were determined and compared with NS. RESULTS: Level of compliance was good, average and poor in 35.9%, 48.7% and 15.4% of MDs, respectively. There was no significant difference in compliance between MDs and NS (p=0.209). Level of compliance was not associated with age, gender and duration of lens wear (p>0.05). Compliance rate varied according to different behaviors, achieving a good compliance level of 95% for hand hygiene, avoidance of water contact and not sleeping with lenses. There was poor compliance for topping up solution (53.8%) and lens case replacement (15.4%). CONCLUSION: About one third of MDs had a good level of compliance. Level of compliance and compliance rate of different behaviors were similar in MDs and NS. Periodic lens case replacement was the most neglected behavior in CL wearers for this region.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.