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.

Predicting preterm birth in maternity care by means of data mining

Worldwide, around 9% of the children are born with less than 37 weeks of labour, causing risk to the premature child, whom it is not prepared to develop a number of basic functions that begin soon after the birth. In order to ensure that those risk pregnancies are being properly monitored by the obstetricians in time to avoid those problems, Data Mining (DM) models were induced in this study to predict preterm births in a real environment using data from 3376 patients (women) admitted in the maternal and perinatal care unit of Centro Hospitalar of Oporto. A sensitive metric to predict preterm deliveries was developed, assisting physicians in the decision-making process regarding the patients’ observation. It was possible to obtain promising results, achieving sensitivity and specificity values of 96% and 98%, respectively.

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

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Pathways and bioenergetics of anaerobic carbon monoxide fermentation

Carbon monoxide can act as a substrate for different modes of fermentative anaerobic metabolism. The trait of utilizing CO is spread among a diverse group of microorganisms, including members of bacteria as well as archaea. Over the last decade this metabolism has gained interest due to the potential of converting CO-rich gas, such as synthesis gas, into bio-based products. Three main types of fermentative CO metabolism can be distinguished: hydrogenogenesis, methanogenesis, and acetogenesis, generating hydrogen, methane and acetate, respectively. Here, we review the current knowledge on these three variants of microbial CO metabolism with an emphasis on the potential enzymatic routes and bio-energetics involved.

Quality of institutional care and early childhood development

Institutional rearing adversely affects children’s development, but the extent to which specific characteristics of the institutional context and the quality of care provided contribute to problematic development remains unclear. In this study, 72 preschoolers institutionalised for at least 6 months were evaluated by their caregiver using the Child Behavior Checklist and the Disturbances of Attachment Interview. Distal and proximate indices of institutional caregiving quality were assessed using both staff reports and direct observation. Results revealed that greater caregiver sensitivity predicted reduced indiscriminate behaviour and secure-base distortions. A closer relationship with the caregiver predicted reduced inhibited attachment behaviour. Emotional and behavioural problems proved unrelated to caregiving quality. Results are discussed in terms of (non)-shared caregiving factors that influence institutionalised children’s development.

The influence of kaolin application on key metabolic pathways associated with grape berry quality: a molecular and biochemical analysis

Dissertação de mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas

Alcohol-dependent patients receiving specialised outpatient care: an overview of gender issues

OBJECTIVE: The objective of the present study, with focus on gender, was aimed at evaluating alcohol-dependent individual in terms of socio-demographic variables related to alcohol consumption and therapeutic interventions. METHODS: This is a retrospective cross-sectional study of 1,051 patients (833 men and 218 women), with diagnosis of alcohol dependence syndrome, according to ICD-10 criteria, who had sought treatment for the first time at a specialised health centre between 2000 and 2006. RESULTS: The results showed that women, compared to men, are more likely to be unemployed and without partner, in addition to having higher educational level, latter age of alcohol initiation, needing less outpatient alcohol detoxification program, consuming more fermented beverage, presenting less psychiatric comorbidities, and using less coadjutant medications during treatment. CONCLUSION: We can state that some peculiarities exist permeating both gender and alcohol consumption. A further focus on the characteristics of each population is needed to facilitate the adequate use of therapeutic interventions according to gender specificities.

Quality of life assessment of patients with schizophrenic spectrum disorders from Psychosocial Care Centers

OBJECTIVE: Assessing the quality of life and the clinical and social-demographic factors associated in schizophrenic spectrum patients (ICD-10 F20-F29) attending CAPS at the programmatic area 3.0. METHODS: A cross-sectional study was carried out in a sample of schizophrenic spectrum patients who have been enrolled in 2008 in CAPS in programmatic area (AP) 3 at Rio de Janeiro city, using MINIPLUS to assess schizophrenia spectrum disorder and use of psychoactive substances, Positive and Negative Symptoms Scale (PANSS) to assess psychiatric symptoms and Quality of Life Scale (QLS-BR) to assess the quality of life. RESULTS: Seventy nine patients were included, of whom 74 (93.7%) presented some impairment in quality of life. The most frequently affected area was occupational performance. Variables that showed a significant association with severe impairment of quality of life were: marital status, race, occupation, who patients lived with, homelessness, having children, previous psychiatric hospitalization, negative symptoms and symptoms designated as not applicable (being characterized by a lack of typical positive and negative symptoms). CONCLUSION: The knowledge of these factors should be crucial to implement health policies and psychosocial rehabilitation programs focused on improving the quality of life of these patients.

Psychiatric morbidity and quality of life of primary care attenders in two cities in Brazil

Objective: To identify the associations among quality of life (QoL), social determinants and psychological distress in primary care in two cities in Brazil. Methods: A cross-sectional study with 1,466 patients from 2009 to 2010. The statistical analysis used the t-test to compare the variables of interest to the study. Results: The prevalence of Common Mental Disorders (CMD3), severe forms of Common Mental Disorders (CMD5), anxiety and depression were 20.5%, 32%, 37% and 25.1% respectively. Thes presence of psychological distress is associated with worse QoL among the patients studied, especially those older than 40 years of age. In cases of CMD3, those with higher income and educational levels presented higher QoL in the psychical and psychological domains. For the cases of probable anxiety, those with higher educational levels presented lower scores on the physical and social relationship scores. Conclusion: Psychological distress can be associated with a worse QoL among those studied and can be influenced by socioeconomic conditions. Therefore, it is important to structure patient-centered help, which should also include patients’ social contexts.

Galanin-mediated behavioural hyperalgesia from the dorsomedial nucleus of the hypothalamus involves two independent descending pronociceptive pathways

Activation of the dorsomedial nucleus of the hypothalamus (DMH) by galanin (GAL) induces behavioural hyperalgesia. Since DMH neurones do not project directly to the spinal cord, we hypothesized that the medullary dorsal reticular nucleus (DRt), a pronociceptive region projecting to the spinal dorsal horn (SDH) and/or the serotoninergic raphe-spinal pathway acting on the spinal 5-HT3 receptor (5HT3R) could relay descending nociceptive facilitation induced by GAL in the DMH. Heat-evoked paw-withdrawal latency (PWL) and activity of SDH neurones were assessed in monoarthritic (ARTH) and control (SHAM) animals after pharmacological manipulations of the DMH, DRt and spinal cord. The results showed that GAL in the DMH and glutamate in the DRt lead to behavioural hyperalgesia in both SHAM and ARTH animals, which is accompanied particularly by an increase in heat-evoked responses of wide-dynamic range neurons, a group of nociceptive SDH neurones. Facilitation of pain behaviour induced by GAL in the DMH was reversed by lidocaine in the DRt and by ondansetron, a 5HT3R antagonist, in the spinal cord. However, the hyperalgesia induced by glutamate in the DRt was not blocked by spinal ondansetron. In addition, in ARTH but not SHAM animals PWL was increased after lidocaine in the DRt and ondansetron in the spinal cord. Our data demonstrate that GAL in the DMH activates two independent descending facilitatory pathways: (i) one relays in the DRt and (ii) the other one involves 5-HT neurones acting on spinal 5HT3Rs. In experimental ARTH, the tonic pain-facilitatory action is increased in both of these descending pathways.

Real-time monitoring of progression towards renal failure in primary care patients

First published online: December 16, 2014.

Synthetic biology approaches to engineer new pathways for the production of plant secondary metabolites

Secondary metabolites from plants are important sources of high-value chemicals, many of them being pharmacologically active. These metabolites are commonly isolated through inefficient extractions from natural biological sources and are often difficult to synthesize chemically. Therefore, their production using engineered organisms has lately attracted an increased attention. Curcuminoids, an example of such metabolites, are produced in Curcuma longa and exhibit anti-cancer and anti-inflammatory activities. Herein we report the construction of an artificial biosynthetic pathway for the curcuminoids production in Escherichia coli. Different 4-coumaroyl-CoA ligases (4CL) and polyketide synthases (diketide-CoA synthase (DCS), curcumin synthase (CURS) and curcuminoid synthase) were tested. The highest curcumin production (70 mg/L) was obtained by feeding ferulic acid and with the Arabidopsis thaliana 4CL1 and C. longa DCS and CURS enzymes. Other curcuminoids (bisdemethoxy- and demethoxycurcumin) were also produced by feeding coumaric acid or a mixture of coumaric and ferulic acids, respectively. Curcuminoids, including curcumin, were also produced from tyrosine through the caffeic acid pathway. To produce caffeic acid, tyrosine ammonia lyase and 4-coumarate 3-hydroxylase were used. Caffeoyl-CoA O-methyltransferase was used to convert caffeoyl-CoA to feruloyl-CoA. This pathway represents an improvement of the curcuminoids heterologous production. The construction of this pathway in another model organism is being considered, as well as the introduction of alternative enzymes.