1,721,184 research outputs found
Riscontri autoptici e placche pleuriche nel Registro Mesoteliomi della Regione Friuli Venezia Giulia
No full textAims: To describe the cases of MM that occurred in the Friuli Venezia Giulia Region in the period 1995-2009 and evaluate the diagnostic contribution of autopsy findings. Methods: Via the Regional Register a search for MM cases was made following standardized criteria for diagnosis and past asbestos exposure assessment. Pleural plaques were identified by autopsy findings; the relationship between presence of pleural plaques and assessment of past asbestos exposure was analyzed. Results: 834 cases of MM were recorded and 458 autopsy findings were available; for 142 cases (15% of males and 23% of women) the first diagnosis was made at autopsy. Data were available on previous asbestos exposure in 91% (416 subjects) of cases with autopsy findings: 255 had “certain occupational exposure” (group 1), 116 “other occupational and non- occupational exposure” (group 2), 45 “negative and unknown exposure” (group 3). Logistic regression showed that significant predictors for pleural plaques were age at diagnosis (OR=1.03 each year (95% CI=1.01-1.05), asbestos exposure in group 1 versus group 2 (OR=6.8 (95% CI=4-12), and exposure in group1 versus group 3 (OR=6.4 (95% CI=3-13). Among subjects in groups 1 and 2, the presence of pleural plaques was significantly associated with latency (OR=1.03 for each year of latency; 95% CI=1.01-1.22) and asbestos exposure in group 1 versus group 2 (OR=7.8; 95% CI=4.4-13.0). Conclusions: Autopsy findings improved the diagnostic level of MM in elderly subjects, for whom reliable data on past asbestos exposure is often lacking. In subjects suffering from MM direct interview is always the best tool to evaluate past asbestos exposure; autopsy findings of pleural plaques cannot replace the anamnestic history when this is lacking, although such findings can act as a suppor
Echocardiographic evaluation of systolic and mean pulmonary artery pressure in patients with pulmonary hypertension: Reply
No full textPrognostic assessment of repeatedly measured time-dependent biomarkers, with application to dilated cardiomyopathy
Full text linkWe propose newtime-dependent sensitivity, specificity,ROCcurves and net reclassification indices that can take into account biomarkers or scores that are repeatedlymeasured at different time-points. Inference proceeds through inverse probability weighting and resampling. The newly proposed measures exploit the information contained in biomarkers measured at different visits, rather than using only the measurements at the first visits. The contribution is illustrated via simulations and an original application on patients affected by dilated cardiomiopathy. The aim is to evaluate if repeated binary measurements of right ventricular dysfunction bring additive prognostic information on mortality/urgent heart transplant. It is shown that taking into account the trajectory of the new biomarker improves risk classification, while the first measurement alone might not be sufficiently informative. The methods are
implemented in an R package (longROC), freely available on CRAN
Adding sufentanil to levobupivacaine or ropivacaine intrathecal anaesthesia affects the minimum local anaesthetic dose required.
No full textWe carried out this prospective, randomized, double-blind study in order to evaluate whether the intrathecal addition of sufentanil 3.3 mcg affects both the minimum local anaesthetic dose (MLAD) of spinal levobupivacaine and ropivacaine for a caesarean section and enhances the spinal block characteristics.One hundred and eighty women were randomly allocated into four groups: levobupivacaine (Group L), levobupivacaine plus sufentanil (Group L+S), ropivacaine (Group R) and ropivacaine plus sufentanil (Group R+S). Each received 3 ml of the study solution intrathecally as part of a combined spinal/epidural technique. The initial dose was 12 mg for Groups L and L+S, and 15 mg for Groups R and R+S. The test solution was required to achieve a visual analogue pain score (VAPS) of 30 mm or less to be considered effective at skin incision, uterine incision, birth, peritoneal closure and at the conclusion of surgery. Effective or ineffective responses determined a 0.5 mg decrease or increase of the same drug, respectively, for the next patient in the same group, using an up-down sequential allocation.Using the Dixon and Massey formula, the MLAD was 10.65 mg [confidence interval (CI) 95\%: 10.14-11.56] in Group L, 4.73 mg (CI 95\%: 4.39-5.07) in Group L+S, 14.12 mg (CI 95\%: 13.50-14.60) in Group R and 6.44 mg (CI 95\%: 5.86-7.02) in Group R+S.The addition of sufentanil reduced the MLAD of both the local anaesthetics. It did not affect their potency ratio significantly and resulted in enhanced spinal anaesthesia
Prospective validation of a predictive scoring system for deep sternal wound infection after routine bilateral internal thoracic artery grafting
No full textOBJECTIVES:
The Gatti score is a weighted scoring system based on risk factors for deep sternal wound infection (DSWI) that has been specifically created to predict DSWI risk after routine bilateral internal thoracic artery (BITA) grafting. It has not undergone an external validation. The aim of the present study was to perform this validation.
METHODS:
BITA grafts were used as skeletonized conduits in 304 (90.7%) of 335 consecutive patients with multivessel coronary artery disease who underwent isolated coronary bypass surgery at the authors' institution between January 2014 and July 2015. Baseline characteristics, operative data and immediate outcomes of every patient were prospectively collected in a computerized data registry. A score was assigned to each patient preoperatively. The goodness-of-fit and the discrimination power of both models, preoperative and combined, of the Gatti score were assessed with the Hosmer-Lemeshow test and the calculation of the area under the receiver-operating characteristic curve, respectively.
RESULTS:
Eighteen (5.9%) patients suffered from DSWI. Major differences were found between the original series whence the Gatti score has been derived and the present prospective series. The Gatti score goodness-of-fit was satisfactory for both the preoperative (P = 0.61) and the combined model (P = 0.81). The area under the receiver-operating characteristic curve was 0.82 (95% confidence interval: 0.72-0.91) for the preoperative model and 0.8 (95% confidence interval: 0.71-0.9) for the combined model.
CONCLUSIONS:
On the basis of the results of the present prospective study, the Gatti score has proved to be effective in predicting DSWI following BITA grafting despite some differences between the original and the present series of patients. More studies have to be performed in order to strengthen the evidence of this first external validation
Soluble FcγRIA expressed on monocytes (sCD64): A new serum biomarker of acute kidney injury in patients with suspected infection at emergency department admission
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Ictal clinical and scalp-EEG findings differentiating temporal lobe epilepsies from temporal 'plus' epilepsies.
No full textTemporal 'plus' epilepsies are characterized by seizures involving a complex epileptogenic network including the temporal lobe and the closed neighboured structures such as the orbito-frontal cortex, the insula, the frontal and parietal operculum and the temporo-parieto-occipital junction. Temporal 'plus' epilepsies are currently identified by means of intracerebral electrodes but whether their diagnosis can be suspected non-invasively has not been evaluated yet. The aim of this retrospective study was to address this issue in 80 consecutive patients who were thought to suffer from non-lesional temporal lobe seizures which finally proved, on the basis of stereotactic intracerebral EEG (SEEG) recordings, to be 'purely' temporal (TL group, n = 58) or temporal 'plus' (T+ group, n = 22). Our results showed that the two groups of patients were difficult to differentiate on the basis of general clinical features or MRI data. Even the presence of hippocampal sclerosis did not distinguish the two groups. Conversely, both ictal clinical symptoms and scalp-EEG findings significantly differentiated TL from T+ patients. Patients with TL epilepsies more frequently presented an ability to warn at seizure onset (P = 0.003), an abdominal aura (P = 0.05), gestural automatisms (P = 0.04) and a post-ictal amnesia (P = 0.02). Patients suffering from T+ epilepsies more frequently had gustatory hallucinations (P = 0.02), rotatory vertigo (P = 0.02) and auditory illusions (P = 0.02) at seizure onset; they exhibited more frequently contraversive manifestations of the eyes and/or head (P = 0.001), piloerection (P = 0.03) and ipsilateral tonic motor signs (P = 0.05), and they were more often dysphoric in the post-ictal phase (P = 0.0001). Cluster analysis mainly indicated that some associations of symptoms were relevant for differentiating TL cases from T+ cases. Interictal EEG of T+ patients more frequently exhibited bilateral or precentral abnormalities, while ictal EEG more frequently pointed over the anterior frontal, temporo-parietal and precentral regions. Neither TL interictal spikes, nor TL ictal EEG onset, allowed us definitely to rule out the possibility of T+ epilepsies. Our findings may be useful for identifying, among patients suffering from 'atypical' non-lesional TL epilepsies, those who should undergo invasive recordings before surgery
Mammography screening in Trieste: data quality, assessment of indicators and impact on the population
No full textIn this Section, "Statistics for screening", we want to emphasize that it is more and more important to use statistics to understand, to analyze and to evaluate the data of a screening, in order to describe the population and to take decisions and, even before, to learn to draw and design a screening itself.As highlighted by the title, using results from the project of mammography screening in the Province of Trieste, we want to focus in particular the importance of
- the quality of the data; without which it is no possible to make a correct statistics, and in this talk we show an example of the correction of the data concerning the blood group;
- the evaluation of the indicators, and here it is important to decide which are ‘informative indicators’, and how it is possible to read the output in a critical way;
- the impact of a screening on a population.
In this context it is evident the importance of a multidisciplinary work, and this is the experience started some years ago in our local reality, with the involvement of pathologists, surgeons, radiologists, radiotherapists, oncologists, physicists , mathematicians, statisticians, ... the different care and research contributions for breast disease in the province of Trieste
Interpretability of time-series deep learning models: A study in cardiovascular patients admitted to Intensive care unit
Full text linkInterpretability is fundamental in healthcare problems and the lack of it in deep learning models is currently the major barrier in the usage of such powerful algorithms in the field. The study describes the implementation of an attention layer for Long Short-Term Memory (LSTM) neural network that provides a useful picture on the influence of the several input variables included in the model.
A cohort of 10,616 patients with cardiovascular diseases is selected from the MIMIC III dataset, an openly available database of electronic health records (EHRs) including all patients admitted to an ICU at Boston’s Medical Centre. For each patient, we consider a 10-length sequence of 1-hour windows in which 48 clinical parameters are extracted to predict the occurrence of death in the next 7 days. Inspired from the recent developments in the field of attention mechanisms for sequential data, we implement a recurrent neural network with LSTM cells incorporating an attention mechanism to identify features driving model’s decisions over time.
The performance of the LSTM model, measured in terms of AUC, is 0.790 (SD = 0.015). Regard our primary objective, i.e. model interpretability, we investigate the role of attention weights. We find good correspondence with driving predictors of a transparent model (r = 0.611, 95% CI [0.395, 0.763]). Moreover, most influential features identified at the cohort-level emerge as known risk factors in the clinical context.
Despite the limitations of study dataset, this work brings further evidence of the potential of attention mechanisms in making deep learning model more interpretable and suggests the application of this strategy for the sequential analysis of EHRs
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