Galactic Outflows and the pollution of the Galactic Environment by Supernovae

We here explore the effects of the SN explosions into the environment of star-forming galaxies like the Milky Way. Successive randomly distributed and clustered SNe explosions cause the formation of hot superbubbles that drive either fountains or galactic winds above the galactic disk, depending on the amount and concentration of energy that is injected by the SNe. In a galactic fountain, the ejected gas is re-captured by the gravitational potential and falls back onto the disk. From 3D nonequilibrium radiative cooling hydrodynamical simulations of these fountains, we find that they may reach altitudes up to about 5 kpc in the halo and thus allow for the formation of the so called intermediate-velocity-clouds (IVCs) which are often observed in the halos of disk galaxies. The high-velocity-clouds that are also observed but at higher altitudes (of up to 12 kpc) require another mechanism to explain their production. We argue that they could be formed either by the capture of gas from the intergalactic medium and/or by the action of magnetic fields that are carried to the halo with the gas in the fountains. Due to angular momentum losses to the halo, we find that the fountain material falls back to smaller radii and is not largely spread over the galactic disk. Instead, the SNe ejecta fall nearby the region where the fountain was produced, a result which is consistent with recent chemical models of the galaxy. The fall back material leads to the formation of new generations of molecular clouds and to supersonic turbulence feedback in the disk.Comment: 10 pages, 5 figures; paper of invited talk for the Procs. of the 2007 WISER Workshop (World Space Environment Forum), Alexandria, Egypt, October 2007, Spa. Sci. Rev

Community health careworkers in Guinea-Bissau: who is performing better?

In the Community Health Workers settings in Guinea-Bissau, we explore several determinants of performance. Firstly, we investigate the effect of socio-demographic characteristics like education, gender, wealth, job status and community "embededdness". We provide evidence for significant differences due to education, gender or job status and community interaction. We also research on the relation between motivation and performance, concluding extrinsically motivated agents performbetter, as opposed to agents with stronger antisocial impact perceptions, who performworse. Given the richness of our data, we also explore differences in ethnicity in terms of performance outcomes or motivation orientations, but in both cases we find few significant results

End-tidal and arterial carbon dioxide gradient in serious traumatic brain injury after prehospital emergency anaesthesia: a retrospective observational study.

OBJECTIVES: In the UK, 20% of patients with severe traumatic brain injury (TBI) receive prehospital emergency anaesthesia (PHEA). Current guidance recommends an end-tidal carbon dioxide (ETCO2) of 4.0-4.5 kPa (30.0-33.8 mm Hg) to achieve a low-normal arterial partial pressure of CO2 (PaCO2), and reduce secondary brain injury. This recommendation assumes a 0.5 kPa (3.8 mm Hg) ETCO2-PaCO2 gradient. However, the gradient in the acute phase of TBI is unknown. The primary aim was to report the ETCO2-PaCO2 gradient of TBI patients at hospital arrival. METHODS: A retrospective cohort study of adult patients with serious TBI, who received a PHEA by a prehospital critical care team in the East of England between 1 April 2015 and 31 December 2017. Linear regression was performed to test for correlation and reported as R-squared (R2). A Bland-Altman plot was used to test for paired ETCO2 and PaCO2 agreement and reported with 95% CI. ETCO2-PaCO2 gradient data were compared with a two-tailed, unpaired, t-test. RESULTS: 107 patients were eligible for inclusion. Sixty-seven patients did not receive a PaCO2 sample within 30 min of hospital arrival and were therefore excluded. Forty patients had complete data and were included in the final analysis; per protocol. The mean ETCO2-PaCO2 gradient was 1.7 (±1.0) kPa (12.8 mm Hg), with moderate correlation (R2=0.23, p=0.002). The Bland-Altman bias was 1.7 (95% CI 1.4 to 2.0) kPa with upper and lower limits of agreement of 3.6 (95% CI 3.0 to 4.1) kPa and -0.2 (95% CI -0.8 to 0.3) kPa, respectively. There was no evidence of a larger gradient in more severe TBI (p=0.29). There was no significant gradient correlation in patients with a coexisting serious thoracic injury (R2=0.13, p=0.10), and this cohort had a larger ETCO2-PaCO2 gradient, 2.0 (±1.1) kPa (15.1 mm Hg), p=0.01. Patients who underwent prehospital arterial blood sampling had an arrival PaCO2 of 4.7 (±0.2) kPa (35.1 mm Hg). CONCLUSION: There is only moderate correlation of ETCO2 and PaCO2 at hospital arrival in patients with serious TBI. The mean ETCO2-PaCO2 gradient was 1.7 (±1.0) kPa (12.8 mm Hg). Lower ETCO2 targets than previously recommended may be safe and appropriate, and there may be a role for prehospital PaCO2 measurement

Prehospital determinants of successful resuscitation after traumatic and non-traumatic out-of-hospital cardiac arrest.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is prevalent in the UK. Reported survival is lower than in countries with comparable healthcare systems; a better understanding of outcome determinants may identify areas for improvement. METHODS: An analysis of 9109 OHCA attended in East of England between 1 January 2015 and 31 July 2017. Univariate descriptives and multivariable analysis were used to understand the determinants of survival for non-traumatic cardiac arrest (NTCA) and traumatic cardiac arrest (TCA). Two Utstein outcome variables were used: survival to hospital admission and hospital discharge. RESULTS: The incidence of OHCA was 55.1 per 100 000 population/year. The overall survival to hospital admission was 27.6% (95% CI 26.7% to 28.6%) and the overall survival to discharge was 7.9% (95% CI 7.3% to 8.5%). Survival to hospital admission and survival to hospital discharge were both greater in the NTCA group compared with the TCA group: 27.9% vs 19.3% p=0.001, and 8.0% vs 3.8% p=0.012 respectively.Determinants of NTCA and TCA survival were different, and varied according to the outcome examined. In NTCA, bystander cardiopulmonary resuscitation (CPR) was associated with survival at discharge but not at admission, and the likelihood of bystander CPR was dependent on geographical socioeconomic status. An air ambulance was associated with increased survival to both hospital admission and discharge in NTCA, but only with survival to admission in TCA. CONCLUSION: NTCA and TCA are clinically distinct entities with different predictors for outcome-future OHCA reports should aim to separate arrest aetiologies. Determinants of survival to hospital admission and discharge differ in a way that likely reflects the determinants of neurological injury. Bystander CPR public engagement may be best focused in more deprived areas

ESICM LIVES 2017 : 30th ESICM Annual Congress. September 23-27, 2017.

INTRODUCTION. Unplanned readmission to intensive care is highly undesirable in that it contributes to increased variance in care, disruption, difficulty in resource allocation and may increase length of stay and mortality particularly if subject to delays. Unlike the ICU admission from the ward, readmission prediction has received relatively little attention, perhaps in part because at the point of ICU discharge, full physiological information is systematically available to the clinician and so it is expected that readmission should be largely due to unpredictable factors. However it may be that there are multidimensional trends that are difficult for the clinician to perceive that may nevertheless be predictive of readmission. OBJECTIVES. We investigated whether machine learning (ML) techniques could be used to improve on the simple published SWIFT score [1] for the prediction of unplanned readmission to ICU within 48 hours. METHODS. We extracted systolic BP, pulse pressure, heart and respiration rate, temperature, SpO2, bilirubin, creatinine, INR, lactate, white cell count, platelet count, pH, FiO2, and total Glasgow Coma Score from ICU stays of over 2000 adult patients from our hospital electronic patient record system. We trained our own custom multidimensional / time-sensitive algorithmic ML system to predict failed discharges defined as either readmission or unexpected death within 48 hours of discharge. We used 10-fold cross validation to assess performance. We also assessed the effect of augmenting our system by transfer learning (TL) with 44,000 additional cases from the MIMIC III database. RESULTS. The SWIFT score performed relatively poorly with an AUROC of around 0.6 which our ML system trained on local data was also able to match. However when augmented with an additional dataset by TL, the AUROC for the ML system improved statistically and clinically significantly to over 0.7. CONCLUSIONS. Machine learning is able to improve on predictors based on simple multiple logistic regression. Thus there is likely to be information in the trends and in combinations of variables. A disadvantage with this technique is that ML approaches require large amounts of data for training. However, ML approaches can be improved by TL. Basing prediction models on locally derived data augmented by TL is a potentially novel approach to generating tools that customised to the institution yet can exploit the potential power of ML algorithms. REFERENCES [1] Gajic O, Malinchoc M, Comfere TB, et al. The Stability and Workload Index for Transfer score predicts unplanned intensive care unit patient readmission: initial development and validation. Crit Care Med. 2008;36(3):676–82. Grant Acknowledgement This work was internally funded

Describing Self-Care in Italian Adults with Heart Failure and Identifying Determinants of Poor Self-Care

Background: Self-care improves outcomes in patients with heart failure; however, no studies have been conducted on this topic in Italy. Aims: We aimed to describe self-care in Italian adults with heart failure and to identify sociodemographic and clinical determinants of self-care. Methods: A cross-sectional design was used to study 1192 heart failure patients enrolled across Italy. We measured self-care using the Self-Care of Heart Failure Index version 6.2, which measures self-care maintenance, management and confidence. Sociodemographic and clinical data were tested as potential determinants of self-care. Results: The mean age of the sample was 72 (SD = 11) years; 58% were male. In the three areas of self-care, scores ranged from 53.18 to 55.26 and few people were adequate in self-care (14.5% to 24.4% of the sample). Self-care behaviours particularly low in this population were symptom monitoring, exercise, use of reminders to take medicines and symptom recognition. Confidence in the ability to keep oneself free of symptoms and relieve symptoms was low. Taking fewer medications, poor cognition, older age, having a caregiver, being male and having heart failure for a shorter time predicted poor self-care maintenance. Poor cognition, not being employed, being male, and having worse New York Heart Association class predicted poor self-care management. Poor cognition, taking fewer mediations, older age, and male gender predicted poor self-care confidence. Conclusion: Self-care is poor in Italian heart failure patients. Determinants of poor self-care identified in this study can help to target patients’ education. Male gender and poor cognition were consistently associated with poor self-care maintenance, management and confidence

Hemodynamic responses during and after multiple sets of stretching exercises performed with and without the Valsalva maneuver

OBJECTIVE: This study investigated the acute hemodynamic responses to multiple sets of passive stretching exercises performed with and without the Valsalva maneuver. METHODS: Fifteen healthy men aged 21 to 29 years with poor flexibility performed stretching protocols comprising 10 sets of maximal passive unilateral hip flexion, sustained for 30 seconds with equal intervals between sets. Protocols without and with the Valsalva maneuver were applied in a random counterbalanced order, separated by 48-hour intervals. Hemodynamic responses were measured by photoplethysmography pre-exercise, during the stretching sets, and post-exercise. RESULTS: The effects of stretching sets on systolic and diastolic blood pressure were cumulative until the fourth set in protocols performed with and without the Valsalva maneuver. The heart rate and rate pressure product increased in both protocols, but no additive effect was observed due to the number of sets. Hemodynamic responses were always higher when stretching was performed with the Valsalva maneuver, causing an additional elevation in the rate pressure product. CONCLUSIONS: Multiple sets of unilateral hip flexion stretching significantly increased blood pressure, heart rate, and rate pressure product values. A cumulative effect of the number of sets occurred only for systolic and diastolic blood pressure, at least in the initial sets of the stretching protocols. The performance of the Valsalva maneuver intensified all hemodynamic responses, which resulted in significant increases in cardiac work during stretching exercises

Multi-views Embedding for Cattle Re-identification

People re-identification task has seen enormous improvements in the latest years, mainly due to the development of better image features extraction from deep Convolutional Neural Networks (CNN) and the availability of large datasets. However, little research has been conducted on animal identification and re-identification, even if this knowledge may be useful in a rich variety of different scenarios. Here, we tackle cattle re-identification exploiting deep CNN and show how this task is poorly related to the human one, presenting unique challenges that make it far from being solved. We present various baselines, both based on deep architectures or on standard machine learning algorithms, and compared them with our solution. Finally, a rich ablation study has been conducted to further investigate the unique peculiarities of this task

Psychometric Testing of the Self-Care of Heart Failure Index Version 6.2

The Self‐Care of Heart Failure Index Version 6.2 (SCHFI v.6.2) is widely used, but its psychometric profile is still questioned. In a sample of 659 heart failure patients from Italy, we performed confirmatory factor analysis (CFA) to test the original construct of the SCHFI v.6.2 scales (Self‐Care Maintenance, Self‐Care Management, and Self‐Care Confidence), with limited success. We then used exploratory factor analysis to determine the presence of separate scale dimensions, followed by CFA in a separate sub‐sample. Construct validity of individual scales showed excellent fit indices: CFI = .92, RMSEA = .05 for the Self‐Care Maintenance Scale; CFI = .95, RMSEA = .07 for the Self‐Care Management Scale; CFI = .99, RMSEA = .02 for the Self‐Care Confidence scale. Contrasting groups validity, internal consistency, and test‐retest reliability were supported as well. This evidence provides a new understanding of the structure of the SCHFI v.6.2 and supports its use in clinical practice and research