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The significant increase in patients during the COVID-19 pandemic presented the healthcare system with a variety of challenges. The intensive care unit is one of the areas particularly affected in this context. Only through extensive infection control measures as well as an enormous logistical effort was it possible to treat all patients requiring intensive care in Germany even during peak phases of the pandemic, and to prevent triage even in regions with high patient pressure and simultaneously low capacities. Regarding pandemic preparedness, the German Parliament passed a law on triage that explicitly prohibits ex post (tertiary) triage. In ex post triage, patients who are already being treated are included in the triage decision and treatment capacities are allocated according to the individual likelihood of success. Legal, ethical, and social considerations for triage in pandemics can be found in the literature, but there is no quantitative assessment with respect to different patient groups in the intensive care unit. This study addressed this gap and applied a simulation-based evaluation of ex ante (primary) and ex post triage policies in consideration of survival probabilities, impairments, and pre-existing conditions. The results show that application of ex post triage based on survival probabilities leads to a reduction in mortality in the intensive care unit for all patient groups. In the scenario close to a real-world situation, considering different impaired and prediseased patient groups, a reduction in mortality of approximately 15% was already achieved by applying ex post triage on the first day. This mortality-reducing effect of ex post triage is further enhanced as the number of patients requiring intensive care increases. [ABSTRACT FROM AUTHOR]

ABSTRACT: Greater longevity is associated with lower replacement costs, higher average milk production, and fewer replacement heifers needed. Longevity data are obtained late in life, and for this reason stayability, defined as the probability of survival from birth until a certain age, can be used as an alternative measure. The objective of this study was to evaluate the effects of different type traits, inbreeding, and production level on the stayability of Jersey cows to various ages, and to assess trends over time. Data consisted of 460,172 to 204,658 stayability records, depending on length of the opportunity period, for survival from birth until 36, 48, 60, 72, or 84 mo of age. Threshold models were used to analyze the stayability traits, including different type traits, inbreeding coefficient, and within-herd production level as explanatory variables. Heritability estimates for stayability traits ranged from 0.05 (36 mo) to 0.22 (84 mo). As expected, the probability of survival decreased as age increased. Highly productive cows were more likely to survive than their poor-producing contemporaries regardless of age and the type trait evaluated. Our data indicate that farmers' selection decisions tend to punish poor production at early ages and reward high production at later stages. Inbreeding negatively affected the probability of survival, especially when inbreeding coefficients exceeded 10%, and this impact was most noticeable at 48 mo of age or later. Some type traits, such as stature and foot angle, had little effect on the probability of survival. Other type traits, such as strength, dairy form, rump width, and rear legs, showed higher probability of survival at intermediate scores, whereas other type traits, such as fore udder attachment, rear udder height, udder depth, and final score, showed higher probability of survival at higher scores. Finally, our results indicate that the probability of survival has decreased in the last decade, probably due to a greater number of heifers available and, therefore, higher culling rates.

The significant increase in patients during the COVID-19 pandemic presented the healthcare system with a variety of challenges. The intensive care unit is one of the areas particularly affected in this context. Only through extensive infection control measures as well as an enormous logistical effort was it possible to treat all patients requiring intensive care in Germany even during peak phases of the pandemic, and to prevent triage even in regions with high patient pressure and simultaneously low capacities. Regarding pandemic preparedness, the German Parliament passed a law on triage that explicitly prohibits ex post (tertiary) triage. In ex post triage, patients who are already being treated are included in the triage decision and treatment capacities are allocated according to the individual likelihood of success. Legal, ethical, and social considerations for triage in pandemics can be found in the literature, but there is no quantitative assessment with respect to different patient groups in the intensive care unit. This study addressed this gap and applied a simulation-based evaluation of ex ante (primary) and ex post triage policies in consideration of survival probabilities, impairments, and pre-existing conditions. The results show that application of ex post triage based on survival probabilities leads to a reduction in mortality in the intensive care unit for all patient groups. In the scenario close to a real-world situation, considering different impaired and prediseased patient groups, a reduction in mortality of approximately 15% was already achieved by applying ex post triage on the first day. This mortality-reducing effect of ex post triage is further enhanced as the number of patients requiring intensive care increases. [ABSTRACT FROM AUTHOR]

Greater longevity is associated with lower replacement costs, higher average milk production, and fewer replacement heifers needed. Longevity data are obtained late in life, and for this reason stayability, defined as the probability of survival from birth until a certain age, can be used as an alternative measure. The objective of this study was to evaluate the effects of different type traits, inbreeding, and production level on the stayability of Jersey cows to various ages, and to assess trends over time. Data consisted of 460,172 to 204,658 stayability records, depending on length of the opportunity period, for survival from birth until 36, 48, 60, 72, or 84 mo of age. Threshold models were used to analyze the stayability traits, including different type traits, inbreeding coefficient, and within-herd production level as explanatory variables. Heritability estimates for stayability traits ranged from 0.05 (36 mo) to 0.22 (84 mo). As expected, the probability of survival decreased as age increased. Highly productive cows were more likely to survive than their poor-producing contemporaries regardless of age and the type trait evaluated. Our data indicate that farmers' selection decisions tend to punish poor production at early ages and reward high production at later stages. Inbreeding negatively affected the probability of survival, especially when inbreeding coefficients exceeded 10%, and this impact was most noticeable at 48 mo of age or later. Some type traits, such as stature and foot angle, had little effect on the probability of survival. Other type traits, such as strength, dairy form, rump width, and rear legs, showed higher probability of survival at intermediate scores, whereas other type traits, such as fore udder attachment, rear udder height, udder depth, and final score, showed higher probability of survival at higher scores. Finally, our results indicate that the probability of survival has decreased in the last decade, probably due to a greater number of heifers available and, therefore, higher culling rates. [ABSTRACT FROM AUTHOR]

Yucca treculeana L. (YT) is increasingly being considered by researchers worldwide as a replacement option for synthetic fibers such as glass fibers. The objective of this study is to determine the tensile quasi-static room temperature mechanical parameters of YT fibers with gauge lengths (GL) of 10, 20, 30, and 40 mm. A comprehensive tensile test program was conducted on 120 fibers grouped in four series to determine the influence of their variability on the tensile strength, ultimate strain at break and elastic Young’s modulus of the YT fibers. The values of the tensile mechanical properties of YT fibers exhibit a large dispersion of results, which is a characteristic of natural fibers, therefore requiring statistical study. For the purpose of studying this dispersion, some statistical tools such as two- and three-parameter Weibull distribution at 95% CI confidence level and one-way analysis of variance (ANOVA) were used.

Yucca treculeana L. (YT) is increasingly being considered by researchers worldwide as a replacement option for synthetic fibers such as glass fibers. The objective of this study is to determine the tensile quasi-static room temperature mechanical parameters of YT fibers with gauge lengths (GL) of 10, 20, 30, and 40 mm. A comprehensive tensile test program was conducted on 120 fibers grouped in four series to determine the influence of their variability on the tensile strength, ultimate strain at break and elastic Young's modulus of the YT fibers. The values of the tensile mechanical properties of YT fibers exhibit a large dispersion of results, which is a characteristic of natural fibers, therefore requiring statistical study. For the purpose of studying this dispersion, some statistical tools such as two- and three-parameter Weibull distribution at 95% CI confidence level and one-way analysis of variance (ANOVA) were used. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study on single particle breakage behavior of crushable weathered sands by a number of single particle uniaxial compression tests to comprehensively investigate the characteristics of single particle breakage, the probability of survival of single particle, and the effects of particle size and weathering on single particle strengths. The behavior of single particle under uniaxial compression falls into the mixed five phases: damage by chipping, elastic deformation, fragmentation by partial fracture, breakage by splitting, and the residuals, demonstrating the complexity and variability of the tensile strengths of single particles. The behavior of single particle breakage was quantified herein by the initial fracture and failure strengths of single particle. The probability of survival decreased as the characteristic stresses increased. An increase in the particle size or weathering number of single particle resulted in a reduction in the probability of survival of single particle. For a given probability of survival, the difference in the initial fracture characteristic stress and failure characteristic stress decreased with increasing particle size but showed a complex change with increasing weathering number. The probability of survival showed greater variability for the normalized initial fracture characteristic stress than for the normalized failure characteristic stress, implying that the initial fracture stresses of single particles diverged more than the failure stresses of the particles. The average initial fracture and failure characteristic stresses, and the initial fracture and failure characteristic stresses corresponding to 1/e (37%) survival of single particles decreased while increasing particle size or weathering number, but the decrease showed a sharper rate for smaller single particles with a lower weathering number. The ln-ln coordinates showed a linear representation of the failure characteristic stress and particle size, verifying the applicability of Weibull theory to single particle breakage. However, weathering resulted in downward translation and slight rotation of the linear relation of the failure characteristic stress and particle size in the ln-ln coordinates. [ABSTRACT FROM AUTHOR]

Tissue injury and hemorrhage induced by trauma lead to degradation of the endothelial glycocalyx, causing syndecan-1 (SDC-1) to be shed into the blood. In this study, we investigated whether serum SDC-1 is useful for evaluating trauma severity in patients. A single-center, retrospective, observational study was conducted at Gifu University Hospital. Patients transported to the emergency room for trauma and subsequently admitted to the intensive care unit from January 2019 to December 2021 were enrolled. A linear regression model was constructed to evaluate the association of serum SDC-1 with injury severity score (ISS) and probability of survival (Ps). A total of 76 trauma patients (54 men and 22 women) were analyzed. ISS was significantly associated with serum SDC-1 level in trauma patients. Among the six body regions defined in the AIS used to calculate the ISS score, “chest” and “abdominal or pelvic contents” were significantly associated with serum SDC-1 level, and “extremities or pelvic girdle” also tended to show an association with serum SDC-1 level. Moreover, increasing serum SDC-1 level was significantly correlated with decreasing Ps. Serum SDC-1 may be a useful biomarker for monitoring the severity of trauma in patients. Further large-scale studies are warranted to verify these results.

For the fatigue design of offshore structures, it is essential to understand and use the S-N curves specified in various industry standards and codes. This study compared the characteristics of the S-N curves for five major codes. The codes reviewed in this paper were DNV Classification Rules (DNV GL, 2016), ABS Classification Rules (ABS, 2003), British Standards (BSI, 2015), International Welding Association Standards (IIW, 2008), and European Standards (BSI, 2005). Types of stress, such as nominal stress, hot-spot stress, and effective notch stress, were analyzed according to the code. The basic shape of the S-N curve for each code was analyzed. A review of the survival probability of the basic design S-N curve for each code was performed. Finally, the impact on the conservatism of the design was analyzed by comparing the S-N curves of three grades D, E, and F by the five codes. The results presented in this paper are considered to be a good guideline for the fatigue design of offshore structures because the S-N curves of the five most-used codes were analyzed in depth.

This study evaluated the probability of survival, failure mode, and stress distribution of narrow diameter implants (NDIs) with internal implant–abutment conical connection comprised of different taper angles and thread designs. Sixty‐three NDIs (Ø 3.5 × 8.5 mm) were divided according to the taper angle (TA), internal diameter (ID), and trapezoidal thread design (TD) (n = 21/group), as follows: (a) 11.5°U (11.5° TA; ID: 2.5 mm; TD: dual threaded); (b) 11.5°S (11.5° TA; ID: 2.5 mm; TD: single threaded); (c) 16°S (16° TA; ID: 2.72 mm; TD: single threaded). They were subjected to step‐stress accelerated life testing. The reliability and use‐level probability Weibull curves were calculated at 50, 100, and 150 N for a mission of 100,000 cycles and the failure mode was analyzed using a scanning electron microscope. For finite element analysis the von‐Mises stress (σvM) was calculated for the abutment and implant. All groups showed high reliability (above 84%) and failures occurred predominantly in the abutment. In the FEA, 11.5°U showed higher σvM for the implant. All NDIs showed high reliability at clinically challenging loads. The system with greater taper angle showed lower σVm in the implant, and dual threaded implants showed a higher stress concentration in the implant and cortical bone. [ABSTRACT FROM AUTHOR]

We propose a sequential Monte Carlo-based cardinalized probability hypothesis density (SMC-CPHD) filter with adaptive survival probability for multiple frequency tracking to enhance the tracking performance. The survival probability of the particles in the filter is adjusted using the pre-designed exponential function related to the distribution of the estimated particle points. In order to ensure whether the proposed survival probability affects the stability of the filter, the error bounds in the prediction process are analyzed. Moreover, an inverse covariance intersection-based compensation method is added to enhance cardinality tracking performance by integrating two types of cardinality information from the CPHD filter and data clustering process. To evaluate the proposed method's performance, MATLAB-based simulations are performed. As a result, the tracking performance of the multiple frequencies has been confirmed, and the accuracy of cardinality estimates are improved compared to the existing filters. [ABSTRACT FROM AUTHOR]

As reported by the World Health Organization (WHO), the world is currently facing a devastating pandemic of a novel coronavirus (COVID-19), which started as an outbreak of pneumonia of unknown cause in the Wuhan city of China in December 2019. Since then, the respiratory disease has exponentially spread to over 210 countries. By the end of April, COVID-19 had caused over three million confirmed cases of infections and over 200,000 fatalities globally. The trend poses a huge threat to global public health. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. We employed a SEIHQRD delay differential mathematical transmission model with reported Kenyan data on cases of COVID-19 to estimate how transmission varies over time and which population to target for mass testing. The model is concise in structure, and successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak and the vulnerable populations. The results show that, the government should target population in the informal settlement for mass testing and provide affordable sanitizers and clean water to this population. The model results also indicate that people with pre-existing non-communicable diseases (NCDs) should be identified and given special medical care. Given the absence of vaccine at the moment, non-pharmaceutical intervention is needed to effectively reduce the final epidemic size. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the characteristic strength of pillars in mining contexts, taking into account the effects of size and shape. The characteristic strength is estimated in terms of the probability of exceeding a specific value of pressure; when once exceeding, the failure appears. Also, the higher number of defects leads to a high probability of failure. In this study, a new analytical formula is applied, which considers the effect of scale (size and shape) with the notion of probability in evaluating the risk of failure to assess the condition of the mine pillars without resorting to pillar level experiments, which would reduce costs and efforts. It is used a data set from an underground mine (rock samples of zinc) in Setif-Algeria. The results shows the strength's decrease with an increase in volume. Furthermore, the pillars with a higher width to height ratio (w/h) have more strength than a slender one. One of the advantages of the probabilistic strength measurement is its functional relation with the deformation at the pillars' level and the progress of the mining sites' works. It is necessary to choose an optimal critical size for the pillars to ensure good operation and safety. [ABSTRACT FROM AUTHOR]

We propose a sequential Monte Carlo-based cardinalized probability hypothesis density (SMC-CPHD) filter with adaptive survival probability for multiple frequency tracking to enhance the tracking performance. The survival probability of the particles in the filter is adjusted using the pre-designed exponential function related to the distribution of the estimated particle points. In order to ensure whether the proposed survival probability affects the stability of the filter, the error bounds in the prediction process are analyzed. Moreover, an inverse covariance intersection-based compensation method is added to enhance cardinality tracking performance by integrating two types of cardinality information from the CPHD filter and data clustering process. To evaluate the proposed method’s performance, MATLAB-based simulations are performed. As a result, the tracking performance of the multiple frequencies has been confirmed, and the accuracy of cardinality estimates are improved compared to the existing filters.

To quantify the fatigue behaviour of materials, a Wöhler diagram is required. The state of the art shows that, over the years, numerous approaches suitable for determining Wöhler curves have been devised and validated through large fatigue data sets. The variation in experimental fatigue data elicits the use of statistics for analysis and design purposes. By focusing on the medium-cycle fatigue regime (i.e., failures in the range 103÷107 cycles to failure), this paper reviews relevant statistical approaches, particularly the methods suggested by the American Society for Testing Materials (ASTM) as well as the International Institute of Welding (IIW) and the so-called Linear Regression Method (LRM). Their responses were assessed on virtual data sets tailored to satisfy specific statistical requirements as well as experimental fatigue data sets from the literature. While the scatter bands at two times or less of the spread are similar for all approaches, the ASTM approach is seen to be the most conservative. • Statistical approaches to estimate fatigue design curves are reviewed. • The problem of estimating mean fatigue curves is analysed. • Strategies recommended to be used to determine scatter bands are reviewed. • Standard approaches are assessed based on virtual data sets. [ABSTRACT FROM AUTHOR]

Due to the ageing of the population, public pension plans are increasingly being implemented by private savings schemes. This therefore gives rise to a wide range of innovative schemes to meet the varying needs of savers and financial institutions. Therefore, the aim of this paper is to propose a savings operation which includes the randomness derived from the contingency which supposes the eventual but unpredictable death of the saver. We have developed this type of operation by applying a financial-actuarial methodology and thereby deducing a way of calculating all amounts resulting from the savings operation, and introducing a new quantity derived from this randomness, namely the risk quota. Similarly, we have indicated how to calculate different measures of (gross and net) profitability, in random terms and the part corresponding to this randomness.

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Introduction This study focused on estimating the probability of survival and the specific time to survival from COVID-19 among patients who had COVID-19 in Osun state, Nigeria. Also, we examined some factors associated with the time to survival among COVID-19 patients in Osun state, Nigeria. Methods The retrospective data of 2596 records of COVID-19 patients in Osun state were analysed in this study. The outcome variable was the "COVID-19 treatment outcome (survived=1, dead=0)". The time date used in the survival analysis was treatment duration (in days). The explanatory variables were demographic characteristics, type of health facility, vaccination status, symptoms, and mode of admission. The descriptive statistics was computed and presented. Kaplan Meier was used to estimate the median time to survival. Bivariate analysis and multivariate analysis were done using the Log-Rank test and Cox regression, respectively. P values were set at P<0.05. Results The mean age was observed to be 40 (SD=17.51) years, ranging from mostly, 2 months to 98 years old. More (56.1%) of the participants were males. Most (99.5%) of them were Nigerians. Only 1.4% were vaccinated. The survival rate from COVID-19 was 98.1% in Osun State. The median time for survival was 14 (IQR= 14- 16) days. COVID-19 reduces as the number of days for being on treatment increases. Unvaccinated (HR=0.93, 95%CI: 0.43-2.03) and those whose vaccination status was unknown (HR=0.52, 95%CI: 0.37-0.74) were less likely to survive COVID-19 diseases. Conclusion The Survival rate was high, the observed median time to survival was 14 days, and the probability of survival reduces as the number of days of being on treatment for COVID-19 increases. Also, gender, vaccination, type of care, and ethnicity were associated with survival time. Similarly, unvaccinated and inpatients were less likely to rapidly survive COVID-19. This study recommends that the COVID-19 vaccine should be encouraged among patients who have the COVID-19 virus. Also, home care may be further explored to assess its effectiveness in caring for COVID-19 patients. In the same vein, COVID-19 data capturing, and databases need strengthening in Nigeria., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Determining the probability of survival after injury is important as it can inform triage, clinical research and audit. A number of methods have been reported for determining the probability of survival after injury. However, these have shortcomings and thus further developments are needed to improve their reliability and accuracy. In this study, a Bayesian method called Predictive Statistical Diagnosis (PSD) was developed to determine probability of survival in 4124 adults (age: mean = 67.9 years, standard deviation = 21.6 years) with traumatic brain injuries (TBI). In total, 86.2% of cases had survived and 13.8% of cases had not survived their injuries. The parameters considered as inputs to PSD were age, abbreviated injury score (AIS), Glasgow coma score (GCS), pulse rate (PR), systolic blood pressure (SBP) and respiration rate (RR). PSD statistically modeled the TBI cases and their associated injury outcomes, i.e., survived or not survived. The model was calibrated on randomly selected, roughly 2/3 (number 2676), of the cases and its performance was validated on the remaining cases (number 1448, i.e., validation dataset). The effectiveness of PSD in determining the probability of survival was compared with a method called Ps14 that uses regression modeling. With all parameters (i.e., age, AIS, GCS, SBP, RR and PR) included as inputs to PSD, it correctly identified 90.8% of survivors and 50.0% of non-survivors in the validation dataset while Ps14 identified 97.4% of survivors and 40.2% of non-survivors in the validation dataset. When age, AIS and GCS were used on their own as inputs to PSD, it correctly identified 82.4% of the survivors and 65.0% of non-survivors in the validation dataset. Age affected the performance of PSD in determining the survival outcomes. The number of non-surviving cases included in this study may have not been sufficiently high to indicate the full potential of PSD and a further study with a larger number of cases would be beneficial.

OBJECTIVE: To determine the survival rate according to the main findings of emergency electroencephalography (EEGs) of patients treated in a tertiary hospital. METHOD: In this prospective study, the findings of consecutive emergency EEGs performed on inpatients in Hospital de Base in São José do Rio Preto, Brazil were correlated with survival utilizing Kaplan-Meyer survival curves. RESULTS: A total of 681 patients with an average age of 42 years old (1 day to 96 years) were evaluated, of which 406 were male. The main reasons for EEGs were epileptic seizures (221 cases), hepatic encephalopathy [116 cases of which 85 (73.3%) were men, p-value=0.001], status epilepticus (104 cases) and impaired consciousness (78 cases). The underlying disease was confirmed in 578 (84.3%) cases with 119 (17.5%) having liver disease [91 (76.0%) were men, p-value=0.001], 105 (15.4%) suffering strokes, 67 (9.9%) having metabolic disorders, 51 (7.5%) central nervous system infections and 49 (7.2%) epilepsy. In the three months following EEG, a survival rate of 75% was found in patients with normal, discreet slow activity or intermittent rhythmic delta activity EEGs, of 50% for those with continuous delta activity and generalized epileptiform discharges, and of 25% for those with burst-suppression, diffuse depression, and in alpha/theta-pattern coma. Death was pronounced immediately in patients with isoelectric EEGs. CONCLUSION: The main findings of EEGs, differentiated different survival rates and are thus a good prognostic tool for patients examined in emergencies.OBJETIVO: Determinar a taxa de sobrevivência (TS), segundo os principais achados de eletrencefalograma de urgência (E-EEG), dos pacientes atendidos nas emergências de hospital de alta complexidade. MÉTODO: Estudo prospectivo, por ordem de chegada, da correlação entre os achados de E-EEG, feitos nos pacientes à beira do leito, com TS, utilizando-se as curvas de sobrevidas de Kaplan Meyer no Hospital de Base de São José do Rio Preto, São Paulo/Brasil. RESULTADOS: Foram estudados 681 pacientes, dos quais 406 (59,6%) masculinos, com idade média de 42 anos (1 dia a 96 anos). As principais motivações para o E-EEG foram crises epilépticas (221 casos), encefalopatia hepática [(116 casos, dos quais 85 masculinos (73,3%), p= 0,001]; estado de mal epiléptico 104 e rebaixamento de consciência 78. O diagnóstico da doença de base foi confirmado em 578 (84,3%), sendo 119 (17,5%) hepatopatia, dos quais 91 (76,%) masculinos, p= 0,001; 105 (15,4%) acidente vascular encefálico; 67 (9,9%) distúrbio metabólico; 51 (7,5%) infecção do sistema nervoso central e 49 (7,2%) epilepsia. TS de 75% nos três primeiros meses foi encontrada nos pacientes com E-EEG com alentecimento discreto ou com atividade delta rítmica intermitente. TS por volta de 50% nos três meses foi encontrado nos pacientes com E-EEG com delta contínuo, crítico e com descargas periódicas. A TS foi menor que 25% nos dois primeiros meses após E-EEG, nos pacientes com E-EEG com surto/supressão, com depressão difusa e com comas alfa/teta e 0% nos E-EEG iselétricos. CONCLUSÃO: O E-EEG, com seus principais achados, foi capaz de diferenciar as diversas taxas de sobrevivências na amostra estudada, constituindo-se, portanto, bom instrumento de prognóstico para pacientes atendidos nas unidades de emergência hospitalar.

Background: Quality improvement (QI) programs have shown to reduce preventable mortality in trauma care. Detailed review of all trauma deaths is a time and resource consuming process and calculated probability of survival (Ps) has been proposed as audit filter. Review is limited on deaths that were 'expected to survive'. However no Ps-based algorithm has been validated and no study has examined elements of preventability associated with deaths classified as 'expected'. The objective of this study was to examine whether trauma performance review can be streamlined using existing mortality prediction tools without missing important areas for improvement.Methods: We conducted a retrospective study of all trauma deaths reviewed by our trauma QI program. Deaths were classified into non-preventable, possibly preventable, probably preventable or preventable. Opportunities for improvement (OPIs) involve failure in the process of care and were classified into clinical and system deviations from standards of care. TRISS and PS were used for calculation of probability of survival. Peer-review charts were reviewed by a single investigator.Results: Over 8 years, 626 patients were included. One third showed elements of preventability and 4% were preventable. Preventability occurred across the entire range of the calculated Ps band. Limiting review to unexpected deaths would have missed over 50% of all preventability issues and a third of preventable deaths. 37% of patients showed opportunities for improvement (OPIs). Neither TRISS nor PS allowed for reliable identification of OPIs and limiting peer-review to patients with unexpected deaths would have missed close to 60% of all issues in care.Conclusions: TRISS and PS fail to identify a significant proportion of avoidable deaths and miss important opportunities for process and system improvement. Based on this, all trauma deaths should be subjected to expert panel review in order to aim at a maximal output of performance improvement programs. [ABSTRACT FROM AUTHOR]

Background/Purpose Congenital diaphragmatic hernia (CDH) is associated with high mortality. Survival is influenced by the extent of pulmonary hypoplasia and additional congenital defects. The purpose of this study was to assess the association of congenital anomalies and admission capillary carbon dioxide levels (PcCO 2 ), as a measure of extent of pulmonary hypoplasia, on survival in neonates with CDH. Methods This is a retrospective review of neonates with CDH admitted to a tertiary neonatal intensive care unit between 1990 and 2014. Logistic regression was used to assess whether hospital survival was associated with admission PcCO 2 or associated anomalies (isolated CDH, CDH with cardiovascular anomalies, and CDH with noncardiac anomalies). The probabilities of survival (POS) score, based on birth weight and 5-min Apgar as defined by the Congenital Diaphragmatic Hernia Study Group were included as a covariate. Results Of 97 patients, 55 had additional malformations (cardiovascular n = 12, noncardiac anomalies n = 43). POS was lower in CDH with other anomalies compared to isolated CDH. Survival rate was 61.9%, 53.5% and 41.7% in isolated CDH, CDH with noncardiac anomalies and CDH with cardiovascular anomalies, respectively. After adjusting for POS score the likelihood of survival in CDH groups with additional anomalies was similar to isolated CDH (OR 0.95, 95% CI 0.22–4.15, and 1.10, 0.39–3.08, for CDH with and without cardiovascular anomalies, respectively). After adjusting for POS score, lower PcCO 2 levels (OR = 1.25 per 5 mmHg decrease, P = 0.003) were associated with better survival. Conclusions Neonates with CDH have a high prevalence of congenital malformations. However, after adjusting for POS score the presence of additional anomalies was not associated with survival. The POS score and admission PcCO 2 were important prognosticating factors for survival. [ABSTRACT FROM AUTHOR]