7 resultados para birth length
em Universidade do Minho
Resumo:
The effects of comorbid depression and anxiety were compared to the effects of depression alone and anxiety alone on pregnancy mood states and biochemistry and on neonatal outcomes in a large multi-ethnic sample. At the prenatal period the comorbid and depressed groups had higher scores than the other groups on the depression measure. But, the comorbid group had higher anxiety, anger and daily hassles scores than the other groups, and they had lower dopamine levels. As compared to the non-depressed group, they also reported more sleep disturbances and relationship problems. The comorbid group also experienced a greater incidence of prematurity than the depressed, the high anxiety and the non-depressed groups. Although the comorbid and anxiety groups were lower birthweight than the non-depressed and depressed groups, the comorbid group did not differ from the depressed and anxiety groups on birth length. The neonates of the comorbid and depressed groups had higher cortisol and norepinephrine and lower dopamine and serotonin levels than the neonates of the anxiety and non-depressed groups as well as greater relative right frontal EEG. These data suggest that for some measures comorbidity of depression and anxiety is the worst condition (e.g., incidence of prematurity), while for others, comorbidity is no more impactful than depression alone.
Resumo:
Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.
Resumo:
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.
Resumo:
Compelling biological and epidemiological evidences point to a key role of genetic variants of the TERT and TERC genes in cancer development. We analyzed the genetic variability of these two gene regions using samples of 2,267 multiple myeloma (MM) cases and 2,796 healthy controls. We found that a TERT variant, rs2242652, is associated with reduced MM susceptibility (OR?=?0.81; 95% CI: 0.72-0.92; p?=?0.001). In addition we measured the leukocyte telomere length (LTL) in a subgroup of 140 cases who were chemotherapy-free at the time of blood donation and 468 controls, and found that MM patients had longer telomeres compared to controls (OR?=?1.19; 95% CI: 0.63-2.24; ptrend ?=?0.01 comparing the quartile with the longest LTL versus the shortest LTL). Our data suggest the hypothesis of decreased disease risk by genetic variants that reduce the efficiency of the telomerase complex. This reduced efficiency leads to shorter telomere ends, which in turn may also be a marker of decreased MM risk.
Resumo:
NIPE - WP 01/ 2016
Resumo:
New polymer electrolytes (PEs) based on chitosan and three ionic liquid (IL) families ([C2mim][CnSO3], [C2mim][CnSO4] and [C2mim][diCnPO4]) were synthesized by the solvent casting method. The effect of the length of the alkyl chain of the IL anion on the thermal, morphological and electrochemical properties of the PEs was studied. The solid polymer electrolytes (SPE) membranes were analyzed by differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray (EDX), polarized optical microscopy (POM), atomic force microscopy (AFM), complex impedance spectroscopy (ionic conductivity) and cyclic voltammetry (CV). The obtained results evidenced an influence of the alkyl chain length of the IL anion on the temperature of degradation, birefringence, surface roughness and ionic conductivity of the membranes. The DSC, XRD and CV results showed independency from the length of the IL-anion-alkyl chain. The PEs displayed an predominantly amorphous morphology, a minimum temperature of degradation of 135 °C, a room temperature (T = 25 °C) ionic conductivity of 7.78 × 10−4 S cm−1 and a wide electrochemical window of ∼ 4.0 V.
Resumo:
Objectives. To study mother-to-infant emotional involvement at birth, namely factors (socio-demographics, previous life events, type of delivery, pain at childbirth, support from partner, infant characteristics, early experiences with the newborn, and mother’s mood) that interfere with the mother’s positive, negative and not clear emotions toward the newborn. Methods. The Bonding Scale (an extended Portuguese version of the ‘New Mother-to-Infant Bonding Scale’) and the Edinburgh Postnatal Depression Scale were administrated during the first after delivery days to 315 mothers recruited at Ju´lio Dinis Maternity Hospital (MJD, Porto, Portugal). Results. A worse emotional involvement with the newborn was observed when the mother was unemployed, unmarried, had less than grade 9, previous obstetrical/psychological problems or was depressed, as well as when the infant was female, had neonatal problems or was admitted in the intensive care unit. Lower total bonding results were significantly predicted when the mother was depressed and had a lower educational level; being depressed, unemployed and single predicted more negative emotions toward the infant as well. No significant differences in the mother-to-infant emotional involvement were obtained for events related to childbirth, such as type of delivery, pain and partner support, or early experiences with the newborn; these events do not predict mother’s bonding results either. Conclusion. The study results support the need for screening and supporting depressed, unemployed and single mothers, in order to prevent bonding difficulties with the newborn at birth.