Mortality rate during professionally guided scuba diving experiences for uncertified divers, 1992–2019

2021 ◽  
Vol 51 (2) ◽  
pp. 147-151
Author(s):  
Peter Buzzacott ◽  
◽  
Al Hornsby ◽  
Karl Shreeves ◽  
◽  
...  
Keyword(s):  
Monte Carlo ◽  
Mortality Rate ◽  
Performance Improvement ◽  
Early Period ◽  
Scuba Diving ◽  
Safety Performance ◽  
Late Period ◽  
Significant Safety ◽  
Rate Improvement ◽  
The Mean

Introduction: The aim of this study was to re-examine the mortality rate among participants in the Professional Association of Diving Instructors’ (PADI)’s Discover Scuba Diving (DSD) programme. Methods: Fatalities reported to PADI as having occurred during DSD scuba dives were counted for each year between 1992 and 2019. DSD participant registrations were also counted for each year. The data were conveniently divided into two equal 14-year periods, 1992−2005 (‘early’) and 2006−2019 (‘late’). To smooth out the year-to-year variation in raw rates, Monte Carlo simulations were performed on the mean rate per 100,000 participants per year during each period. Results: There were a total of 7,118,731 DSD participant registrations and 79 fatalities during the study period. The estimated overall mean mortality rate in the early period was 2.55 per 100,000 DSD registrations whereas the estimated rate of 0.87 per 100,000 DSD registrations was significantly lower in the late period (P < 0.0001). Conclusions: PADI’s contemporary Discover Scuba Diving introductory scuba experiences, at 0.87 fatalities per 100,000 participants, have a calculated mortality rate that is less than half that calculated for 1992−2008. The late period’s rate improvement appears due either to significant under-registration in the early period, or to significant safety-performance improvement in the late period or, more likely, some combination of the two.

scholarly journals Temporal Trends and Outcome of Patients with Acute Coronary Syndrome and Prior Myocardial Infarction

2021 ◽  
Vol 10 (23) ◽  
pp. 5580
Author(s):  
Katia Orvin ◽  
Alon Shechter ◽  
Doron Zahger ◽  
Vitaly Shklovski ◽  
Tal Ovdat ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Coronary Syndrome ◽  
Mortality Rate ◽  
Medical Therapy ◽  
Temporal Trends ◽  
Early Period ◽  
High Risk Group ◽  
Late Period ◽  
Coronary Syndrome ◽  
Increased Risk

Patients who have previously had a myocardial infarction (MI) are considered a high-risk group with increased risk for cardiovascular (CV) events. During the last decade, the outcome of acute coronary syndrome (ACS) patients has improved due to advances in medical therapy and interventional techniques. We aimed to examine temporal trends and outcomes of patients with prior MI admitted due to ACS from the Acute Coronary Syndrome Israeli Survey (ACSIS). Included were 16,934 ACS patients, of whom 31.4% had prior MI. For temporal trend analysis, the cohort was divided into an early period (2000–2008) and late period (2010–2018). For patients with prior MI, patients in the late period had a higher rate of CV risk factors and were treated more frequently with revascularization and guidelines-directed medical therapy. Recurrent MI (6.7% vs. 12%, p < 0.001), MACE (10.6% vs. 21%, p < 0.001) and 1-year mortality (10.7% vs. 14.6%, p < 0.001) were significantly lower in the late period. However, the mortality rate for patients with prior MI remained higher compared with patients without prior MI (10.7% vs. 6.8% p < 0.001) with an overall higher mortality rate in the STEMI group. Thus, despite significant improvement in outcome measures in the contemporary era, ACS patients with prior MI are still at increased risk for recurrent ischemic CV events and mortality.

The global dynamics of stochastic Holling type II predator-prey models with non constant mortality rate

Filomat ◽  
2017 ◽  
Vol 31 (18) ◽  
pp. 5811-5825
Author(s):  
Xinhong Zhang
Keyword(s):  
Mortality Rate ◽  
Stochastic Model ◽  
Sufficient Conditions ◽  
Positive Periodic Solution ◽  
Global Dynamics ◽  
Type Ii ◽  
Predator Prey ◽  
Persistence In The Mean ◽  
The Mean ◽  
Predator Prey Models

In this paper we study the global dynamics of stochastic predator-prey models with non constant mortality rate and Holling type II response. Concretely, we establish sufficient conditions for the extinction and persistence in the mean of autonomous stochastic model and obtain a critical value between them. Then by constructing appropriate Lyapunov functions, we prove that there is a nontrivial positive periodic solution to the non-autonomous stochastic model. Finally, numerical examples are introduced to illustrate the results developed.

scholarly journals Country-level determinants of the severity of the first global wave of the COVID-19 pandemic: an ecological study

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e042034
Author(s):  
Tiberiu A Pana ◽  
Sohinee Bhattacharya ◽  
David T Gamble ◽  
Zahra Pasdar ◽  
Weronika A Szlachetka ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Vaccination Coverage ◽  
Urban Areas ◽  
Ecological Study ◽  
Environmental Parameters ◽  
The Philippines ◽  
International Travel ◽  
Bcg Vaccination ◽  
Country Level ◽  
The Mean

ObjectiveWe aimed to identify the country-level determinants of the severity of the first wave of the COVID-19 pandemic.DesignEcological study of publicly available data. Countries reporting >25 COVID-19 related deaths until 8 June 2020 were included. The outcome was log mean mortality rate from COVID-19, an estimate of the country-level daily increase in reported deaths during the ascending phase of the epidemic curve. Potential determinants assessed were most recently published demographic parameters (population and population density, percentage population living in urban areas, population >65 years, average body mass index and smoking prevalence); economic parameters (gross domestic product per capita); environmental parameters (pollution levels and mean temperature (January–May); comorbidities (prevalence of diabetes, hypertension and cancer); health system parameters (WHO Health Index and hospital beds per 10 000 population); international arrivals; the stringency index, as a measure of country-level response to COVID-19; BCG vaccination coverage; UV radiation exposure; and testing capacity. Multivariable linear regression was used to analyse the data.Primary outcomeCountry-level mean mortality rate: the mean slope of the COVID-19 mortality curve during its ascending phase.ParticipantsThirty-seven countries were included: Algeria, Argentina, Austria, Belgium, Brazil, Canada, Chile, Colombia, the Dominican Republic, Ecuador, Egypt, Finland, France, Germany, Hungary, India, Indonesia, Ireland, Italy, Japan, Mexico, the Netherlands, Peru, the Philippines, Poland, Portugal, Romania, the Russian Federation, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, Ukraine, the UK and the USA.ResultsOf all country-level determinants included in the multivariable model, total number of international arrivals (beta 0.033 (95% CI 0.012 to 0.054)) and BCG vaccination coverage (−0.018 (95% CI −0.034 to –0.002)), were significantly associated with the natural logarithm of the mean death rate.ConclusionsInternational travel was directly associated with the mortality slope and thus potentially the spread of COVID-19. Very early restrictions on international travel should be considered to control COVID-19 outbreaks and prevent related deaths.

scholarly journals Statistical Tests of Symbolic Dynamics

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 817
Author(s):  
Fernando López ◽  
Mariano Matilla-García ◽  
Jesús Mur ◽  
Manuel Ruiz Marín
Keyword(s):  
Monte Carlo ◽  
Symbolic Dynamics ◽  
Null Hypothesis ◽  
Statistical Tests ◽  
General Applicability ◽  
Monte Carlo Experiments ◽  
The Mean ◽  
Theoretical Application ◽  
New Statistics ◽  
General Method

A novel general method for constructing nonparametric hypotheses tests based on the field of symbolic analysis is introduced in this paper. Several existing tests based on symbolic entropy that have been used for testing central hypotheses in several branches of science (particularly in economics and statistics) are particular cases of this general approach. This family of symbolic tests uses few assumptions, which increases the general applicability of any symbolic-based test. Additionally, as a theoretical application of this method, we construct and put forward four new statistics to test for the null hypothesis of spatiotemporal independence. There are very few tests in the specialized literature in this regard. The new tests were evaluated with the mean of several Monte Carlo experiments. The results highlight the outstanding performance of the proposed test.

scholarly journals Early mortality in hip fracture patients admitted during first wave of the COVID-19 pandemic in Northern Italy: a multicentre study

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Dante Dallari ◽  
Luigi Zagra ◽  
Pietro Cimatti ◽  
Nicola Guindani ◽  
Rocco D’Apolito ◽  
...  
Keyword(s):  
Hip Fracture ◽  
Mortality Rate ◽  
Multicentre Study ◽  
Proximal Femur ◽  
Femur Fracture ◽  
Northern Italy ◽  
Proximal Femur Fracture ◽  
Time To Surgery ◽  
Fracture Management ◽  
The Mean

Abstract Background Treatment of hip fractures during the coronavirus disease 2019 (COVID-19) pandemic has posed unique challenges for the management of COVID-19-infected patients and the maintenance of standards of care. The primary endpoint of this study is to compare the mortality rate at 1 month after surgery in symptomatic COVID-positive patients with that of asymptomatic patients. A secondary endpoint of the study is to evaluate, in the two groups of patients, mortality at 1 month on the basis of type of fracture and type of surgical treatment. Materials and methods For this retrospective multicentre study, we reviewed the medical records of patients hospitalised for proximal femur fracture at 14 hospitals in Northern Italy. Two groups were formed: COVID-19-positive patients (C+ group) presented symptoms, had a positive swab for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and received treatment for COVID-19; COVID-19-negative patients (C− group) were asymptomatic and tested negative for SARS-CoV-2. The two groups were compared for differences in time to surgery, survival rate and complications rate. The follow-up period was 1 month. Results Of the 1390 patients admitted for acute care for any reason, 477 had a proximal femur fracture; 53 were C+ but only 12/53 were diagnosed as such at admission. The mean age was > 80 years, and the mean American Society of Anesthesiologists (ASA) score was 3 in both groups. There was no substantial difference in time to surgery (on average, 2.3 days for the C+ group and 2.8 for the C− group). As expected, a higher mortality rate was recorded for the C+ group but not associated with the type of hip fracture or treatment. No correlation was found between early treatment (< 48 h to surgery) and better outcome in the C+ group. Conclusions Hip fracture in COVID-19-positive patients accounted for 11% of the total. On average, the time to surgery was > 48 h, which reflects the difficulty of maintaining normal workflow during a medical emergency such as the present pandemic and notwithstanding the suspension of non-urgent procedures. Hip fracture was associated with a higher 30-day mortality rate in COVID-19-positive patients than in COVID-19-negative patients. This fact should be considered when communicating with patients and/or their family. Our data suggest no substantial difference in hip fracture management between patients with or without COVID-19 infection. In this sample, the COVID-19-positive patients were generally asymptomatic at admission; therefore, routine screening is recommended. Level of evidence Therapeutic study, level 4.

Rigorous time-domain analysis of statistically oriented graphene sheet fluctuations

2017 ◽  
Vol 36 (5) ◽  
pp. 1351-1363 ◽  
Author(s):  
Athanasios N. Papadimopoulos ◽  
Stamatios A. Amanatiadis ◽  
Nikolaos V. Kantartzis ◽  
Theodoros T. Zygiridis ◽  
Theodoros D. Tsiboukis
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Finite Difference ◽  
Surface Waves ◽  
Time Domain ◽  
Finite Difference Time Domain ◽  
Mean Value ◽  
Content Type ◽  
The Mean ◽  
Difference Time

Purpose Important statistical variations are likely to appear in the propagation of surface plasmon polariton waves atop the surface of graphene sheets, degrading the expected performance of real-life THz applications. This paper aims to introduce an efficient numerical algorithm that is able to accurately and rapidly predict the influence of material-based uncertainties for diverse graphene configurations. Design/methodology/approach Initially, the surface conductivity of graphene is described at the far infrared spectrum and the uncertainties of its main parameters, namely, the chemical potential and the relaxation time, on the propagation properties of the surface waves are investigated, unveiling a considerable impact. Furthermore, the demanding two-dimensional material is numerically modeled as a surface boundary through a frequency-dependent finite-difference time-domain scheme, while a robust stochastic realization is accordingly developed. Findings The mean value and standard deviation of the propagating surface waves are extracted through a single-pass simulation in contrast to the laborious Monte Carlo technique, proving the accomplished high efficiency. Moreover, numerical results, including graphene’s surface current density and electric field distribution, indicate the notable precision, stability and convergence of the new graphene-based stochastic time-domain method in terms of the mean value and the order of magnitude of the standard deviation. Originality/value The combined uncertainties of the main parameters in graphene layers are modeled through a high-performance stochastic numerical algorithm, based on the finite-difference time-domain method. The significant accuracy of the numerical results, compared to the cumbersome Monte Carlo analysis, renders the featured technique a flexible computational tool that is able to enhance the design of graphene THz devices due to the uncertainty prediction.

scholarly journals Patient-level and hospital-level variation and related time trends in COVID-19 case fatality rates during the first pandemic wave in England: multilevel modelling analysis of routine data

2021 ◽  
pp. bmjqs-2021-012990
Author(s):  
Alex Bottle ◽  
Puji Faitna ◽  
Paul P Aylin
Keyword(s):  
Early Period ◽  
Total Mortality ◽  
Case Fatality ◽  
Routine Data ◽  
Multilevel Modelling ◽  
Primary Diagnosis ◽  
Hospital Death ◽  
Late Period ◽  
Hospital Level ◽  
Patient Level

BackgroundA report suggesting large between-hospital variations in mortality after admission for COVID-19 in England attracted much media attention but used crude rates. We aimed to quantify these variations between hospitals and over time during England’s first wave (March to July 2020) and assess available patient-level and hospital-level predictors to explain those variations.MethodsWe used administrative data for England, augmented by hospital-level information. Admissions were extracted with COVID-19 codes. In-hospital death was the primary outcome. Risk-adjusted mortality ratios (standardised mortality ratios) and interhospital variation were calculated using multilevel logistic regression. Early-wave (March to April) and late-wave (May to July) periods were compared.Results74 781 admissions had a primary diagnosis of COVID-19, with 21 984 in-hospital deaths (29.4%); the 30-day total mortality rate was 28.8%. The crude in-hospital death rate fell in all ages and overall from 32.9% in March to 13.4% in July. Patient-level predictors included age, male gender, non-white ethnic group (early period only) and several comorbidities (obesity early period only). The only significant hospital-level predictor was daily COVID-19 admissions in the late period; we did not find a relation with staff absences for COVID-19, mechanical ventilation bed occupancies, total bed occupancies or bed occupancies for COVID-19 admissions in either period. Just 4 (3%) and 2 (2%) hospitals were high, and 5 (4%) and 0 hospitals were low funnel plot mortality outliers at 3 SD for early and late periods, respectively, after risk adjustment. We found no strong correlation between early and late hospital-level mortality (r=0.17, p=0.06).ConclusionsThere was modest variation in mortality following admission for COVID-19 between English hospitals after adjustment for risk and random variation, in marked contrast to early media reports. Early-period mortality did not predict late-period mortality.

Kinetic Monte Carlo Simulation of Impurity Effects on Nucleation and Growth of SiC Clusters on Si(100)

2013 ◽  
Vol 740-742 ◽  
pp. 393-396
Author(s):  
Maxim N. Lubov ◽  
Jörg Pezoldt ◽  
Yuri V. Trushin
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Cluster Size ◽  
Kinetic Monte Carlo ◽  
Nucleation And Growth ◽  
Nucleation Density ◽  
Nucleation Process ◽  
Impurity Effects ◽  
Kinetic Monte Carlo Simulations ◽  
The Mean

The influence of attractive and repulsive impurities on the nucleation process of the SiC clusters on Si(100) surface was investigated. Kinetic Monte Carlo simulations of the SiC clusters growth show that that increase of the impurity concentration (both attractive and repulsive) leads to decrease of the mean cluster size and rise of the nucleation density of the clusters.

scholarly journals Evaluation of Bearing Capacity of Strip Footing Using Random Layers Concept

2015 ◽  
Vol 37 (3) ◽  
pp. 31-39 ◽  
Author(s):  
Marek Kawa ◽  
Dariusz Łydżba
Keyword(s):  
Monte Carlo ◽  
Bearing Capacity ◽  
Failure Mechanism ◽  
Design Theory ◽  
Cohesive Soil ◽  
Probability Of Failure ◽  
Mean Value ◽  
Strip Footing ◽  
Random Field Theory ◽  
The Mean

Abstract The paper deals with evaluation of bearing capacity of strip foundation on random purely cohesive soil. The approach proposed combines random field theory in the form of random layers with classical limit analysis and Monte Carlo simulation. For given realization of random the bearing capacity of strip footing is evaluated by employing the kinematic approach of yield design theory. The results in the form of histograms for both bearing capacity of footing as well as optimal depth of failure mechanism are obtained for different thickness of random layers. For zero and infinite thickness of random layer the values of depth of failure mechanism as well as bearing capacity assessment are derived in a closed form. Finally based on a sequence of Monte Carlo simulations the bearing capacity of strip footing corresponding to a certain probability of failure is estimated. While the mean value of the foundation bearing capacity increases with the thickness of the random layers, the ultimate load corresponding to a certain probability of failure appears to be a decreasing function of random layers thickness.

A numerical study of the sedimentation of fibre suspensions

1998 ◽  
Vol 376 ◽  
pp. 149-182 ◽  
Author(s):  
MICHAEL B. MACKAPLOW ◽  
ERIC S. G. SHAQFEH
Keyword(s):  
Monte Carlo ◽  
Steady State ◽  
Monte Carlo Simulations ◽  
Numerical Study ◽  
Point Particle ◽  
Hydrodynamic Interactions ◽  
Dynamic Simulations ◽  
Slender Body Theory ◽  
Fibre Suspensions ◽  
The Mean

The sedimentation of fibre suspensions at low Reynolds number is studied using two different, but complementary, numerical simulation methods: (1) Monte Carlo simulations, which consider interparticle hydrodynamic interactions at all orders within the slender-body theory approximation (Mackaplow & Shaqfeh 1996), and (ii) dynamic simulations, which consider point–particle interactions and are accurate for suspension concentrations of nl3=1, where n and l are the number density and characteristic half-length of the fibres, respectively. For homogeneous, isotropic suspensions, the Monte Carlo simulations show that the hindrance of the mean sedimentation speed is linear in particle concentration up to at least nl3=7. The speed is well predicted by a new dilute theory that includes the effect of two-body interactions. Our dynamic simulations of dilute suspensions, however, show that interfibre hydrodynamic interactions cause the spatial and orientational distributions to become inhomogeneous and anisotropic. Most of the fibres migrate into narrow streamers aligned in the direction of gravity. This drives a downward convective flow within the streamers which serves to increase the mean fibre sedimentation speed. A steady-state orientation distribution develops which strongly favours fibre alignment with gravity. Although the distribution reaches a steady state, individual fibres continue to rotate in a manner that can be qualitatively described as a flipping between the two orientations aligned with gravity. The simulation results are in good agreement with published experimental data.

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