An improved class of estimators for estimation of population distribution functions under stratified random sampling.

The main objective of the current study is to suggest an enhanced family of log ratio-exponential type estimators for population distribution function (DF) using auxiliary information under stratified random sampling. Putting different choices in our suggested generalized class of estimators, we found some Specific estimators. The bias and MSE expressions of the estimators have been approximated up to the first order. By using the actual and simulated data sets, we measured the performance of estimators. Based on the results, the suggested estimators for DF show better performance as compared to the preliminary estimators considered here. The suggested estimators have a advanced efficiency than the other estimators examined with the estimators F‾ˆlogPR(st)2, and F‾ˆlogPR(st)4 for both the actual and simulated data sets. The magnitude of the improvement in efficiency is noteworthy, indicating the superiority of the proposed estimators in terms of MSE.

Recurrent peri-myocarditis: A rarer but unfortunate redundant presentation of thyroid storm.

Thyroid storm represents a critical and life-threatening complication from hyperthyroidism, with a notable mortality risk. Limited literature reports have explored the correlation between thyroid storm and peri-myocarditis, although the precise pathophysiological underpinnings remain unclear. The pathophysiology of how thyroid storm and peri-myocarditis are associated is not clearly understood; however, unfavorable prognostic factors include atrial fibrillation and recurrent thyrotoxicosis. Here, we present a case concerning recurrent peri-myocarditis concomitant with a thyroid storm.

New generalized class of estimators for estimation of finite population mean based on probability proportional to size sampling using two auxiliary variables: A simulation study.

This article aims to suggest a new generalized class of estimators based on probability proportional to size sampling using two auxiliary variables. The numerical expressions for the bias and mean squared error (MSE) are derived up to the first order of approximation. Four actual data sets are used to examine the performances of a new improved generalized class of estimators. From the results of real data sets, it is examined that the suggested estimator gives the minimum MSE and the percentage relative efficiency is higher than all existing estimators, which shows the importance of the new generalized class of estimators. To check the strength and generalizability of our proposed class of estimators, a simulation study is also accompanied. The consequence of the simulation study shows the worth of newly found proposed class estimators. Overall, we get to the conclusion that the proposed estimator outperforms as compared to all other estimators taken into account in this study.

A simulation study: An enhanced generalized class of estimators for estimation of population proportion using twofold auxiliary attribute.

The article introduces a novel class of estimators designed for estimating finite population proportions. These estimators utilize dual auxiliary attributes and are applicable under simple random sampling. The proposed class of estimators includes various members with distinct characteristics. The article provides numerical terminologies for the bias and MSE of the estimators, acquire up to first order of approximation. Four actual data sets are used. Additionally, a simulation study is accompanied to perceive the presentations of estimators. The MSE criterion is used to assess how well the proposed estimator performed as likened to the preliminary estimators. The simulation analysis revealed that, in contrast to other examined estimators, the suggested class of estimators provided better results. The empirical investigation offers evidence to substantiate the findings of the argument. Theoretical research also displays that the suggested class of estimators outperforms its competitors.

Improved family of estimators for the population mean using supplementary variables under PPS sampling.

In this article, we suggest an enhanced family of estimators for estimation of population mean employing the supplementary variables under probability proportional to size sampling. Up to the first order of approximation, numerical formulations of the bias and mean square error of estimators are obtained. From our suggested improved family of estimators, we give sixteen different members. The recommended family of estimators has specifically been used to derive the characteristics of sixteen estimators based on the known population parameters of the study as well as auxiliary variables. The performances of the suggested estimators have been assessed using three actual data. Furthermore, a simulation investigation is also accompanied to evaluate the effectiveness of estimators. The proposed estimators have a smaller MSE and an advanced PRE when linked to existing estimators, which are based on actual data sets and simulation studies. Theoretically and empirically studies also reveal that the suggested estimators accomplish well than the usual estimators.

A new improved generalized class of estimators for population distribution function using auxiliary variable under simple random sampling.

This article aims to suggest a new improved generalized class of estimators for finite population distribution function of the study and the auxiliary variables as well as mean of the usual auxiliary variable under simple random sampling. The numerical expressions for the bias and mean squared error (MSE) are derived up to first degree of approximation. From our generalized class of estimators, we obtained two improved estimators. The gain in second proposed estimator is more as compared to first estimator. Three real data sets and a simulation are accompanied to measure the performances of our generalized class of estimators. The MSE of our proposed estimators is minimum and consequently percentage relative efficiency is higher as compared to their existing counterparts. From the numerical outcomes it has been shown that the proposed estimators perform well as compared to all considered estimators in this study.

A simulation study: Improved ratio-in-regression type variance estimator based on dual use of auxiliary variable under simple random sampling.

In this article, we proposed an improved finite population variance estimator based on simple random sampling using dual auxiliary information. Mathematical expressions of the proposed and existing estimators are obtained up to the first order of approximation. Two real data sets are used to examine the performances of a new improved proposed estimator. A simulation study is also recognized to assess the robustness and generalizability of the proposed estimator. From the result of real data sets and simulation study, it is examining that the proposed estimator give minimum mean square error and percentage relative efficiency are higher than all existing counterparts, which shown the importance of new improved estimator. The theoretical and numerical result illustrated that the proposed variance estimator based on simple random sampling using dual auxiliary information has the best among all existing estimators.

A generalized class of estimators for sensitive variable in the presence of measurement error and non-response.

In this paper, a general class of estimators is proposed for estimating the finite population mean for sensitive variable, in the presence of measurement error and non-response in simple random sampling. Expressions for bias and mean square error up to first order of approximation, are derived. Impact of measurement errors is examined using real data sets, including the survey conducted at Quaid-i-Azam University, Islamabad. Simulated data sets are also used to observe the performance of the proposed estimators in comparison to some other estimators. We obtain the empirical bias and MSE values for the proposed and the competing estimators.

Is COVID-19 Immune to Misinformation? A Brief Overview.

During the current COVID-19 pandemic, misinformation is a major challenge, raising several social and psychological concerns. This article highlights the prevailing misinformation as an outbreak containing hoaxes, myths, and rumours. In comparison to traditional media, online media platforms facilitate misinformation even more widely. To further affirm this ethical concern, the researchers cite relevant studies demonstrating the role of new media in misinformation and its potential consequences. Besides other significant psychosocial impacts, such as xenophobia, psychological distress, LGBT rights violation, gender-based violence, misinformation is undermining healthcare workers' psychological health and their efforts to mitigate the impact of COVID-19. In view of the adverse consequences of misinformation, this article addresses it as a massive ethical challenge during the current outbreak. Thus, the researchers make relevant suggestions to evaluate misinformation sources and mitigate the psychosocial impacts attributed to misinformation during crises. They include forming mental health teams comprising of psychologists, psychiatrists, and trained paramedical staff; rapid dissemination of authentic and updated COVID-19 situation reports regularly; establishing helpline services; and recognizing a broader range of personal needs. All health authorities should make clear that they are listening and responding to public concerns. Much effort is needed to counteract COVID-19 misinformation.

Steal and strain: A case of coronary artery fistula presenting with coronary steal syndrome and underlying bronchiectasis.

BACKGROUND: Coronary artery fistula is a relatively rare disorder with an incidence rate of 0.05-0.9%, and the majority of fistulae are detected incidentally. Most coronary artery fistulae are congenital, and the acquired variant is very rare. Herein, we present a possible acquired coronary artery to pulmonary artery fistula, most likely secondary to bronchiectasis in the adjacent lung. We will analyze the hemodynamic significance of the fistula in this case and also seek to understand the outcomes of various treatment modalities. CASE PRESENTATION: A 56-year-old male patient presented with hypoxemia secondary to acute pulmonary edema during a hypertensive emergency. He developed myocardial ischemia after treatment with diuretics and nitroglycerin, due to shunting of blood from the right coronary artery to the right lower lobe branch of the right pulmonary artery, via the fistula. This resulted in coronary steal syndrome. Coronary angiogram confirmed the fistula connecting the right coronary artery to the right lower lobe branch of the right pulmonary artery. An attempt at coil embolization was unsuccessful due to the inability to advance the microcatheter beyond the fistula. DISCUSSION: The majority of coronary artery fistulae are asymptomatic as they are hemodynamically not significant and are incidentally detected by coronary angiography, CT angiogram, echocardiogram or multi-detector row computed tomography (MDCT) with 3D reconstruction. The development of congenital fistula can be explained by the Hackensellner involution-persistence hypothesis, but the anatomy in this case and the bronchiectasis in the part of the lung adjacent to the fistula makes an acquired cause very likely due to local inflammation and the age of patient at initial diagnosis. An initial diagnosis of bronchiectasis was made at age 51, which was 5 years prior to the detection of the coronary artery fistula in this patient. Symptoms have been described mostly in the elderly and include chest pain, dyspnea, fatigue, syncope, and palpitations. Such symptomatic fistula should be treated either by percutaneous transluminal embolization or surgical ligation. CONCLUSION: This is a unique case of acquired coronary to pulmonary artery fistula in the setting of bronchiectasis in a patient in which PTE was attempted and failed. More research is required to understand the pathophysiology of acquired fistula. The decision regarding the method of closure should be individualized and decided on a case by case basis.

An Unusual Case of Bilateral Hemorrhagic Chemosis in the Intensive Care Unit.

Critically ill patients cannot complain about eye problems. Eyecare is often overlooked in the intensive care units (ICUs) because treatment is mainly focused on failures of organ which results in eye complications which are preventable. Therefore, we report a case of a patient admitted to the ICU who developed unusual bilateral hemorrhagic chemosis. Although, chemosis has been encountered often in the ICU, hemorrhagic chemosis without prior direct trauma is unusual.

Cavitary Pulmonary Infarction in a Case of Pulmonary Embolism After Successful Vascular Recanalization.

Cavity formation after pulmonary embolism can be a result of infarction; however, the data available on the incidence rate were obtained from the cases of patients treated with anticoagulation without recanalization. It is yet unknown if interventions like catheter-directed alteplase or thrombectomy reduce the risk of cavity formation. We present an interesting case of a patient who developed pulmonary cavity and possible secondary infection after successful vascular recanalization with catheter-directed alteplase and thrombectomy.

Cardiac Arrest Due to Benzonatate Overdose.

BACKGROUND Benzonatate is one of the most widely prescribed nonnarcotic antitussives to relieve cough symptoms. As a structurally similar agent to other local anesthetics, including tetracaine and procaine, the risk to the public is not fully appreciated. CASE REPORT A 37-year-old female presented to the Emergency Department (ED) status post cardiac arrest. Advanced cardiac life support (ACLS) protocol was performed, and return of spontaneous circulation (ROSC) was achieved. Total downtime was 30 minutes. The patient was intubated, sedated, and hypothermia protocol was initiated. The patient developed bradyarrhythmia and mild coagulopathy suspicious for disseminated intravascular coagulation (DIC), thus hypothermia protocol was terminated later. A review of laboratory data showed acidosis with pH of 6.87, mixed acidosis secondary to high anion gap metabolic and respiratory acidosis with elevated liver enzymes. It was reported that approximately 2 hours prior to her presentation; the patient had ingested less than 30 pills of benzonatate 200 mg capsules with alcohol. CONCLUSIONS Ingestion of benzonatate, a widely prescribed antitussive, may pose a risk to patients due to the potential for rapid development of life-threatening adverse events and limited treatment options in the overdose setting, not only in children but also in adults. Rational prescribing and patient education are needed.

Estimation of finite population mean for a sensitive variable using dual auxiliary information in the presence of measurement errors.

In this study, we propose a new improved estimator of population mean for the sensitive variable in the presence of measurement error under simple and stratified random sampling. This estimator accounts the auxiliary information as well as the ranks of the auxiliary variable. From theoretical and numerical studies it is shown that a new improved estimator performs better than the existing estimators under study.

Estimation of population mean in the presence of measurement error and non response under stratified random sampling.

In the present paper we propose an improved class of estimators in the presence of measurement error and non-response under stratified random sampling for estimating the finite population mean. The theoretical and numerical studies reveal that the proposed class of estimators performs better than other existing estimators.

Spatial Prediction and Optimized Sampling Design for Sodium Concentration in Groundwater.

Sodium is an integral part of water, and its excessive amount in drinking water causes high blood pressure and hypertension. In the present paper, spatial distribution of sodium concentration in drinking water is modeled and optimized sampling designs for selecting sampling locations is calculated for three divisions in Punjab, Pakistan. Universal kriging and Bayesian universal kriging are used to predict the sodium concentrations. Spatial simulated annealing is used to generate optimized sampling designs. Different estimation methods (i.e., maximum likelihood, restricted maximum likelihood, ordinary least squares, and weighted least squares) are used to estimate the parameters of the variogram model (i.e, exponential, Gaussian, spherical and cubic). It is concluded that Bayesian universal kriging fits better than universal kriging. It is also observed that the universal kriging predictor provides minimum mean universal kriging variance for both adding and deleting locations during sampling design.