The Estimation of (Covid-19) Cases in Kurdistan Region Using Nelson Aalen Estimator

It is described how the Nelson–Aalen estimator may be used to control the rate of a nonparametric estimate of the cumulative hazard rate function based on right censored as well as left condensed survival data, furthermore how the Nelson–Aalen estimator can be utilized to estimate various amounts. This technique is mostly applied to survival data and product quality data similar to the incorporated relative mortality in a multiplicative model with outer rates and the cumulative infection rate in a straightforward epidemic model. It is shown that tallying measures produce a structure that permits to a brought together treatment of all these different conditions, and the main little and massive sample properties of the assessor are summarized. This estimator is a weighted average of the Nelson-Aalen reliability estimates over two time periods. The suggested estimator's suitability and utility in model selection are reviewed. And a real-world dataset is evaluated to demonstrate the proposed estimator's suitability and utility. This work proposes a simple and nearly unbiased estimator to fill this gap. The information was gathered from the Ministry of Health's website between October 1, 2020, and February 28, 2021. The results of the Nelson Allen Estimator demonstrated that the odds of surviving were higher during a short period of time after being exposed to the virus. As time passes, the possibilities become slimmer. The closer the estimate comes to value 1 from 0.5 upward, the greater the chances of surviving the infection.

Monitoring the newly infected cases of COVID-19 data weekly: A Survival Data Analysis (SDA) perspective

This paper attempts to fit the best survival model distribution for the Malaysian COVID-19 new infections experience of Wave I/II and Wave III using the well-known Survival Data Analysis (SDA) procedures. The purpose of fitting such models is to reduce the complexity and frequency of the COVID-19 new infections data into a single measure of scale and shape parameters to enable monitoring of weekly trends, undertake short term forecasts and estimate duration when the virality will be contained. The analysis showed a Weibull distribution is the best statistical fit for Malaysia’s new infections COVID-19 data. The estimates of scale and shape parameters for Wave I/II was 0.05901 and 2.48956 and for Wave III was 0.06463 and 2.5693, respectively. Much higher hazard force in Wave III is due to weaker control in the implementation of cordon sanitaire measures imposed in containing the virality spread. Based on the survival function the short-term forecasts showed that the number of new infections projected to decline from 23,282 cases in 28th week to 22,017 cases in 31st week. Similarly, based on the cumulative hazard function the duration estimated for containing the virality completely projected to stretch over another 19.6 weeks under the prevailing conditions.

Assessment of cognitive screening tests as predictors of driving cessation: A prospective cohort study of a median 4-year follow-up

Background Assessing fitness to drive and predicting driving cessation remains a challenge for primary care physicians using standard screening procedures. The objective of this study was to prospectively evaluate the properties of neuropsychological screening tests, including the Trail Making Test (TMT), Clock Drawing Test (CDT), Montreal Cognitive Assessment (MoCA), Useful Field of View (UFOV), and Timed Up and Go (TUG) test, in predicting driving cessation for health reasons in drivers older than 70 years of age. Design and methods This prospective cohort study, with a median follow-up of 4 years for drivers of 70 years old or older with an active driving license in Switzerland, included 441 participants from a driving refresher course dedicated to volunteer senior drivers. Cases were drivers reported in the national driving registry who lost their license following a health-related accident, who were reported as unfit to drive by their physician or voluntarily ceased driving for health reasons. Survival analysis was used to measure the hazard ratio of driving cessation by adjusting for age and sex and to evaluate the predictive value of combining 3 or more positive tests in predicting driving cessation during a 4-year follow-up. Results A total of 1738 person-years were followed-up in the cohort, with 19 (4.3%) having ceased driving for health reasons. We found that participants with a TMT-A < 54 sec and TMT-B < 150 sec at baseline had a significantly lower cumulative hazard of driving cessation in 4 years than those with slower performance (adjusted HR 3, 95% CI: 1.16–7.78, p = 0.023). Participants who performed a CDT ≥ 5 had a significantly lower cumulative hazard of driving cessation (adjusted HR 2.89, 95% CI: 1.01–7.71, p = 0.033). Similarly, an MoCA score ≥ 26, TUG test <12 sec or a UFOV of low risk showed a lower but not significant cumulative risk at a median follow-up of 4 years. When using tests as a battery, those with three or more positive tests out of five were 3.46 times more likely to cease driving (95% CI: 1.31–9.13, p = 0.012). Conclusions The CDT and the TMT may predict driving cessation in a statistically significant way, with a better performance than the UFOV and MoCA tests during a median 4-year follow-up. Combining tests may increase the predictability of driving cessation. Although our results are consistent with current evidence, they should be interpreted with precaution; more than 95% of the participants above the set threshold were able to continue driving for 4 years without any serious incident.

Ventriculoperitoneal shunt failure in pediatric patients: an analysis of a national hospitalization database in Thailand

OBJECTIVE Shunt failure is common among patients undergoing ventriculoperitoneal shunting for treatment of hydrocephalus. The present study examined long-term shunt failure and associated risk factors in pediatric patients by using a national hospitalization database of Thailand. METHODS Patients 17 years or younger who had been admitted to 71 public hospitals in 2012–2017 for first-time ventriculoperitoneal shunting for diseases with known etiology and discharged alive were followed through 2019 to ascertain shunt failure. Shunt survivals were calculated using Kaplan-Meier estimates and time to failure was analyzed to identify risk factors for the first failure by using Cox proportional hazards regression. Differences in risks of subsequent failures with respect to place in the order of failures (i.e., first, second, third) were determined using a cumulative hazard function. RESULTS Over a median follow-up of 29.9 months, shunt failure occurred in 33.7% of 2072 patients (median age 8.8 months), with a higher proportion in patients < 1 year than in patients 1–17 years (37.8% vs 28.9%, p < 0.001), and ranged from 26.1% of those having posttraumatic hydrocephalus to 35.9% of those having infectious diseases. The shunt failure rates at 3, 6, and 12 months were 11.5%, 19.0%, and 25.2%, respectively. Patients < 1 year had a higher risk of the first failure than patients 1–17 years (hazard ratio 1.45, 95% CI 1.20–1.76). Among those with shunt failure, 35.8% had multiple failures and 52.9% failed within 180 days after the index shunting. The cumulative hazard of subsequent failure was consistently higher than that of an earlier failure regardless of age and etiology, and the cumulative hazard of the second failure in the patients with 180-day failure was higher than that in the patients in whom shunts failed beyond 180 days. CONCLUSIONS Shunt failure occurred more frequently in younger pediatric patients. Much attention should be placed on the initial shunt operation so as to mitigate the failure risk. Close follow-up was crucial once patients had developed the failure, because the risk of subsequent failure was more likely than an earlier one among those with multiple failures.

OptBand: optimization-based confidence bands for functions to characterize time-to-event distributions

Classical simultaneous confidence bands for survival functions (i.e., Hall–Wellner, equal precision, and empirical likelihood bands) are derived from transformations of the asymptotic Brownian nature of the Nelson–Aalen or Kaplan–Meier estimators. Due to the properties of Brownian motion, a theoretical derivation of the highest confidence density region cannot be obtained in closed form. Instead, we provide confidence bands derived from a related optimization problem with local time processes. These bands can be applied to the one-sample problem regarding both cumulative hazard and survival functions. In addition, we present a solution to the two-sample problem for testing differences in cumulative hazard functions. The finite sample performance of the proposed method is assessed by Monte Carlo simulation studies. The proposed bands are applied to clinical trial data to assess survival times for primary biliary cirrhosis patients treated with D-penicillamine.

Statistical Approach to Crystal Nucleation in Glass-Forming Liquids

In this work, methods of description of crystal nucleation by using the statistical approach are analyzed. Findings from classical nucleation theory (CNT) for the average time of formation of the first supercritical nucleus are linked with experimental data on nucleation in glass-forming liquids stemming from repetitive cooling protocols both under isothermal and isochronal conditions. It is shown that statistical methods of lifetime analysis, frequently used in medicine, public health, and social and behavioral sciences, are applicable to crystal nucleation problems in glass-forming liquids and are very useful tools for their exploration. Identifying lifetime with the time to nucleate as a random variable in homogeneous and non-homogeneous Poisson processes, solutions for the nucleation rate under steady-state conditions are presented using the hazard rate and related parameters. This approach supplies us with a more detailed description of nucleation going beyond CNT. In particular, we show that cumulative hazard estimation enables one to derive the plotting positions for visually examining distributional model assumptions. As the crystallization of glass-forming melts can involve more than one type of nucleation processes, linear dependencies of the cumulative hazard function are used to facilitate assignment of lifetimes to each nucleation mechanism.

Uveitis as a potential predictor of acute myocardial infarction in patients with Behcet’s disease: a population-based cohort study

ObjectivesTo investigate whether uveitis is a predictor of acute myocardial infarction (AMI) among patients with Behcet’s disease (BD).DesignRetrospective cohort study.SettingPatients with BD were retrieved from the whole population of the Taiwan National Health Insurance Research Database from 1 January 2001 to 31 December 2013.ParticipantsAmong the 6508 patients with BD, 2517 (38.7%) were in the uveitis group and 3991 were in the non-uveitis group.Primary and secondary outcome measuresKaplan-Meier curves were generated to compare the cumulative hazard of AMI in the uveitis and non-uveitis groups. Multivariate Cox regression analysis was used to estimate the adjusted HRs and 95% CI of AMI, and was adjusted for age, gender, systemic comorbidities (eg, hypertension, diabetes, hyperlipidaemia, smoking) and clinical manifestation of BD (eg, oral ulcers, genital ulcers, skin lesions, arthritis and gastrointestinal involvement).ResultsThe mean age of the BD cohort was 38.1±15.1 years. Compared with non-uveitis patients, uveitis patients were significantly younger and male predominant. There was no significant difference between the two groups for most proportions of systemic comorbidities and clinical manifestations. The Kaplan-Meier method with the log-rank test showed that the uveitis group had a significantly higher cumulative hazard for patients with AMI compared with the non-uveitis group (p<0.0001). In the multivariable Cox regression after adjustment for confounding factors, patients with uveitis had a significantly higher risk of AMI (adjusted HR 1.87; 95% CI 1.52 to 2.29). Other significant risk factors for AMI were age, hypertension, smoking, and skin lesions.ConclusionsStatistical analyses from the nationwide database demonstrated that uveitis is a potential predictor of AMI in patients with BD.