Highlights • Low voltage (<20 μV) and burst-suppression with identical bursts EEG at 24 hours after cardiac arrest invariably predict poor outcome. • Continuous EEG patterns with physiological ...rhythms within 12 hours are strongly associated with a good outcome. • Epileptiform patterns, including electrographic status epilepticus, are of unknown significance, and treatment effects are indistinct.
Dynamic indices, including pulse pressure, systolic pressure, and stroke volume variation (PPV, SPV, and SVV), are accurate predictors of fluid responsiveness under strict conditions, for example, ...controlled mechanical ventilation using conventional tidal volumes (TVs) in the absence of cardiac arrhythmias. However, in routine clinical practice, these prerequisites are not always met. We evaluated the effect of regularly used ventilator settings, different calculation methods, and the presence of cardiac arrhythmias on the ability of dynamic indices to predict fluid responsiveness in sedated, mechanically ventilated patients.
We prospectively evaluated 47 fluid challenges in 29 consecutive cardiac surgery patients. Patients were divided into different groups based on TV. Dynamic indices were calculated in various ways: calculation over 30 s, breath-by-breath (with and without excluding arrhythmias), and with correction for TV.
The predictive value was optimal in the group ventilated with TVs >7 ml kg−1 with correction for TV, calculated breath-by-breath, and with exclusion of arrhythmias area under the curve (AUC)=0.95, 0.93, and 0.90 for PPV, SPV, and SVV, respectively. Including patients ventilated with lower TVs decreased the predictive value of all dynamic indices, while calculating dynamic indices over 30 s and not excluding cardiac arrhythmias further reduced the AUC to 0.51, 0.63, and 0.51 for PPV, SPV, and SVV, respectively.
PPV, SPV, and SVV are the only reliable predictors of fluid responsiveness under strict conditions. In routine clinical practice, factors including low TV, cardiac arrhythmias, and the calculation method can substantially reduce their predictive value.
This study compared surgical outcomes before and after implementation of a comprehensive checklist, including marking of the operative side and use of postoperative instructions. Complications ...decreased from 27 to 17 per 100 patients, and mortality decreased from 1.5 to 0.7%.
Hospitals are not the safe places we would like them to be. A systematic review has shown that 1 in every 150 patients admitted to a hospital dies as a consequence of an adverse event and that almost two thirds of in-hospital events are associated with surgical care.
1
In recognition of the disproportionate number of such events that are associated with surgical care, several interventions have been proposed to increase patient safety, including relegating surgical procedures to high-volume centers, establishing training programs for laparoscopic surgery, and improving the quality of teamwork in the operating room.
2
–
4
In addition, a number . . .
The activity of the brain during observation or imagination of movements might facilitate the relearning of motor functions after stroke. The present study examines whether there is an additional ...effect of imagination over observation-only. Eight healthy subjects observed and observed-and-imagined a movement of a hand; 64-channel EEG was used to measure brain activity. The synchronization of the theta (4–8 Hz), alpha (8–13 Hz) and beta (13–25 Hz) frequency bands was calculated and plotted in topoplots. The temporal changes of the sensorimotor area (C3, C4) and the centro-parietal cortex (Pz) were analyzed in the two experimental conditions. During observation-and-imagination, a significant larger desynchronization (
p
= 0.004) in the sensorimotor area was found compared to observation-only in all electrodes and frequency bands. In addition, temporal differences were found between observation and observation-and-imagination in the alpha frequency bands. During observation-and-imagination, modulations of EEG rhythms were stronger than during observation-only in the theta, alpha and beta frequency bands and during almost the whole activity fragment. These findings suggest an additive effect of imagination to observation in the rehabilitation after stroke.
The cellular invasion machinery of the enteric pathogen Salmonella consists of a type III secretion system (T3SS) with injectable virulence factors that induce uptake by macropinocytosis. Salmonella ...invasion at the apical surface of intestinal epithelial cells is inefficient, presumably because of a glycosylated barrier formed by transmembrane mucins that prevents T3SS contact with host cells. We observed that Salmonella is capable of apical invasion of intestinal epithelial cells that express the transmembrane mucin MUC1. Knockout of MUC1 in HT29-MTX cells or removal of MUC1 sialic acids by neuraminidase treatment reduced Salmonella apical invasion but did not affect lateral invasion that is not hampered by a defensive barrier. A Salmonella deletion strain lacking the SiiE giant adhesin was unable to invade intestinal epithelial cells through MUC1. SiiE-positive Salmonella closely associated with the MUC1 layer at the apical surface, but invaded Salmonella were negative for the adhesin. Our findings uncover that the transmembrane mucin MUC1 is required for Salmonella SiiE-mediated entry of enterocytes via the apical route.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background
In most western European countries perioperative chemotherapy is a part of standard curative treatment for gastric cancer. Nevertheless, recurrence rates remain high after multimodality ...treatment. This study examines patterns of recurrence in patients receiving perioperative chemotherapy with surgery for gastric cancer in a real-world setting.
Methods
All patients diagnosed with gastric adenocarcinoma between 2010 and 2015 who underwent at least preoperative chemotherapy and a gastrectomy with curative intent (cT1N+/cT2-4a,X; any cN; cM0) in 18 Dutch hospitals were selected from the Netherlands Cancer Registry. Additional data on chemotherapy and recurrence were collected from medical records. Rates, patterns, and timing of recurrence were examined. Multivariable Cox proportional hazard analyses were used to determine prognostic factors for recurrence.
Results
408 patients were identified. After a median follow-up of 27.8 months, 36.8% of the gastric cancer patients had a recurrence of which the majority (88.8%) had distant metastasis. The 1-year recurrence-free survival was 71.8%. The risk of recurrence was higher in patients with an ypN+ stage (HR 4.92, 95% CI 3.35–7.24), partial or no tumor regression (HR 2.63, 95% CI 1.22–5.64), 3 instead of ≥ 6 chemotherapy cycles (HR 3.04, 95% CI 1.99–4.63), R1 resection (HR 1.52, 95% CI 1.02–2.26), and < 15 resected lymph nodes (HR 1.64, 95% CI 1.14–2.37).
Conclusion
A considerable amount of gastric cancer patients who were treated with curative intent developed a recurrence despite surgery and perioperative treatment. The majority developed distant metastases, therefore, multimodality treatment approaches should be focused on the prevention of distant rather than locoregional recurrences to improve survival.
Campylobacter fetus can cause intestinal illness and, occasionally, severe systemic infections. Infections mainly affect persons at higher risk, including elderly and immunocompromised individuals ...and those with occupational exposure to infected animals. Outbreaks are infrequent but have provided insight into sources. Source attribution of sporadic cases through case-control interviews has not been reported. The reservoirs for C. fetus are mainly cattle and sheep. Products from these animals are suspected as sources for human infections. Campylobacter fetus is rarely isolated from food, albeit selective isolation methods used in food microbiology are not suited for its detection. We hypothesize that the general population is regularly exposed to C. fetus through foods of animal origin, cross-contaminated foodstuffs, and perhaps other, as yet unidentified, routes. Campylobacter fetus infection should be suspected particularly in patients with nonspecific febrile illness who are immunocompromised or who may have been occupationally exposed to ruminants.
Introduction
Early identification of delayed cerebral ischemia (DCI) in patients with aneurysmal subarachnoid hemorrhage (aSAH) is a major challenge. The aim of this study was to investigate whether ...quantitative EEG (qEEG) features can detect DCI prior to clinical or radiographic findings.
Methods
A prospective cohort study was performed in aSAH patients in whom continuous EEG (cEEG) was recorded. We studied 12 qEEG features. We compared the time point at which qEEG changed with the time point that clinical deterioration occurred or new ischemia was noted on CT scan.
Results
Twenty aSAH patients were included of whom 11 developed DCI. The alpha/delta ratio (ADR) was the most promising feature that showed a significant difference in change over time in the DCI group (median −62 % with IQR −87 to −39 %) compared to the control group (median +27 % with IQR −32 to +104 %,
p
= 0.013). Based on the ROC curve, a threshold was chosen for a combined measure of ADR and alpha variability (AUC: 91.7, 95 % CI 74.2–100). The median time that elapsed between change of qEEG and clinical DCI diagnosis was seven hours (IQR −11–25). Delay between qEEG and CT scan changes was 44 h (median, IQR 14–117).
Conclusion
In this study, ADR and alpha variability could detect DCI development before ischemic changes on CT scan was apparent and before clinical deterioration was noted. Implementation of cEEG in aSAH patients can probably improve early detection of DCI.
Highlights • Electrodes with ERs are stronger associated with SOZ than with non-SOZ electrodes. • Stimulating the SOZ evokes ERs that are associated with the seizure propagation area. • ERs evoked by ...SPES can add information for identification of epileptic cortex.
•We validate a convolutional neural network identifying abnormal EEGs in a large diverse set of 8522 EEGs.•Including age and sleep stage in the model results in minimal performance gain.•Extensive ...prediction error analysis reveals promising future research directions.
Electroencephalography (EEG) is a central part of the medical evaluation for patients with neurological disorders. Training an algorithm to label the EEG normal vs abnormal seems challenging, because of EEG heterogeneity and dependence of contextual factors, including age and sleep stage. Our objectives were to validate prior work on an independent data set suggesting that deep learning methods can discriminate between normal vs abnormal EEGs, to understand whether age and sleep stage information can improve discrimination, and to understand what factors lead to errors.
We train a deep convolutional neural network on a heterogeneous set of 8522 routine EEGs from the Massachusetts General Hospital. We explore several strategies for optimizing model performance, including accounting for age and sleep stage.
The area under the receiver operating characteristic curve (AUC) on an independent test set (n = 851) is 0.917 marginally improved by including age (AUC = 0.924), and both age and sleep stages (AUC = 0.925), though not statistically significant.
The model architecture generalizes well to an independent dataset. Adding age and sleep stage to the model does not significantly improve performance.
Insights learned from misclassified examples, and minimal improvement by adding sleep stage and age suggest fruitful directions for further research.
PDF
