Identify successful restrictions in suppressing the early outbreak of COVID-19 in Arizona, United States: Interrupted time series analysis.

COVID-19 was responsible for many deaths and economic losses around the globe since its first case report. Governments implemented a variety of policies to combat the pandemic in order to protect their citizens and save lives. Early in 2020, the first cases were reported in Arizona State and continued to rise until the discovery of the vaccine in 2021. A variety of strategies and interventions to stop or decelerate the spread of the pandemic has been considered. It is recommended to define which strategy was successful for disease propagation prevention and could be used in further similar situations. This study aimed to evaluate the effect of people's contact interventions strategies which were implemented in Arizona State and their effect on reducing the daily new COVID-19 cases and deaths. Their effect on daily COVID-19 cases and deaths were evaluated using an interrupted time series analysis during the pandemic's first peaks to better understand the onward situation. Canceling the order of staying at home (95% CI, 1718.52 to 6218.79; p<0.001) and expiring large gatherings (95% CI, 1984.99 to 7060.26; p<0.001) on June 30 and August 17, 2020, respectively, had a significant effect on the pandemic, leading to the daily cases to grow rapidly. Moreover, canceling the stay at home orders led to an increase in the number of COVID-19 daily deaths by 67.68 cases (95% CI, 27.96 to 107.40; p<0.001) after about 21 days while prohibiting large gatherings significantly decreased 66.76 (95% CI: 20.56 to 112.96; p = 0.004) the number of daily deaths with about 21 days' lag. The results showed that strategies aimed at reducing people's contact with one another could successfully help fight the pandemic. Findings from this study provide important evidence to support state-level policies that require observance of social distancing by the general public for future pandemics.

Application of distributed lag models and spatial analysis for comparing the performance of the COVID-19 control decisions in European countries.

Over the past three years, the COVID-19 outbreak has become a major worldwide problem, affecting the health systems and economies of countries. The mean delays, the expected time to observe the average effect of the number of new cases on the number of deaths, are gold times for decision-making regarding disease control and treatment facilities to reduce the fatality rate. The interest of the present study is estimating the mean delays and adjusted fatality rates of COVID-19 with the new application of Distributed Lag Models (DLM) and their spatial distributions. The daily cases and deaths data of COVID-19 for 39 European countries was obtained from two sources; the "European Centre for Disease Prevention and Control" and the "Our World in Data" database. The mean delay and the Adjusted Fatality Rate (AFR) for each country at three-time intervals; the first and subsequent peaks before and after vaccination were estimated by the Distributed Lag Models. The spatial analysis was applied to find the spatial correlation of the mean delays and adjusted fatality rates among European countries. In the three-time intervals, the first and the subsequent peaks before vaccination, and after vaccination, the median and interquartile range of the mean delays; and AFRs were: 1.1 (0.4, 3.2); 0.024 (0.016, 0.044), 9.2 (6.2, 12.40); 0.013 (0.005, 0.020) and 7.3 (4.4, 11.0); 0.001 (0.001, 0.005), respectively. In the subsequent peaks before vaccination, the mean delays considerably increased, and the AFRs decreased for most European countries. After vaccination, the AFRs decreased considerably. Except for the first peak, the spatial correlations of AFRs were not significant among neighboring countries. Consecutive outcomes will occur with delays in outbreaks of infectious disease. Also, the fatality rates for these outcomes should be adjusted on delays. Estimating the mean delays and adjusted fatality rates by Distributed lag Models and the spatial distributions of theme in outbreaks showed that prevention and medical policies after the first peak as well as vaccination were effective to reduce the fatality rate of COVID-19, but these effects were different between countries. These results recommended policymakers and governments assign prevention and medical resources more effectively.

Comparison of decision tree with common machine learning models for prediction of biguanide and sulfonylurea poisoning in the United States: an analysis of the National Poison Data System.

BACKGROUND: Biguanides and sulfonylurea are two classes of anti-diabetic medications that have commonly been prescribed all around the world. Diagnosis of biguanide and sulfonylurea exposures is based on history taking and physical examination; thus, physicians might misdiagnose these two different clinical settings. We aimed to conduct a study to develop a model based on decision tree analysis to help physicians better diagnose these poisoning cases. METHODS: The National Poison Data System was used for this six-year retrospective cohort study.The decision tree model, common machine learning models multi layers perceptron, stochastic gradient descent (SGD), Adaboosting classiefier, linear support vector machine and ensembling methods including bagging, voting and stacking methods were used. The confusion matrix, precision, recall, specificity, f1-score, and accuracy were reported to evaluate the model's performance. RESULTS: Of 6183 participants, 3336 patients (54.0%) were identified as biguanides exposures, and the remaining were those with sulfonylureas exposures. The decision tree model showed that the most important clinical findings defining biguanide and sulfonylurea exposures were hypoglycemia, abdominal pain, acidosis, diaphoresis, tremor, vomiting, diarrhea, age, and reasons for exposure. The specificity, precision, recall, f1-score, and accuracy of all models were greater than 86%, 89%, 88%, and 88%, respectively. The lowest values belong to SGD model. The decision tree model has a sensitivity (recall) of 93.3%, specificity of 92.8%, precision of 93.4%, f1_score of 93.3%, and accuracy of 93.3%. CONCLUSION: Our results indicated that machine learning methods including decision tree and ensembling methods provide a precise prediction model to diagnose biguanides and sulfonylureas exposure.

The effect of topical olive oil application on the symptoms of infantile colic: A randomized, double-blind, placebo-controlled clinical trial.

Background and Aims: Infantile colic is one of the most common disorders in the first months of infants' lives. This condition hurts parents' moods. This study was carried out to investigate the effect of the topical use of olive oil on infantile colic symptoms. Methods: The study was carried out on 80 infants 1-3 months old, randomly allocated into two groups, receiving abdominal massage with olive oil thrice a day in the intervention group (n = 40) and the same procedure with liquid paraffin in the placebo group (n = 40), for 14 successive days. During this period, the parents recorded the episodes of colic, duration of colic, crying intensity, and episodes of defecation. These variables were assessed and compared at the beginning and on the 7th and 14th days. Results: The mean crying duration changed from 4.05 ± 2.44 to 1.41 ± 1.03 h/day (65% decrease) in the olive oil group and from 3.85 ± 1.37 to 1.60 ± 1.32 h/day (58% decrease) in the paraffin group (p = 0.38). The episodes of crying were reduced from 5.79 ± 4.56 to 2.51 ± 4.93 episodes/day (↓57%) in the olive group and from 6.01 ± 3.40 to 3.01 ± 2.40 episodes/day (↓50%) in the paraffin oil group (p = 0.14). Furthermore, the intensity of crying was decreased from 9.04 ± 1.54 to 4.48 ± 2.17 (p < 0.001) in the olive oil group and from 9.0 ± 1.20 to 4.77 ± 1.68 (p < 0.001) in the paraffin oil group. On the 14th day, the crying intensity showed no significant difference between the two groups. Conclusion: Abdominal massage with olive oil has the same effect as massage with paraffin oil in reducing the symptoms of infantile colic.

Predictors of in-hospital mortality among patients with symptoms of stroke, Mashhad, Iran: an application of auto-logistic regression model.

BACKGROUND: Stroke is the second leading cause of death in adults worldwide. There are remarkable geographical variations in the accessibility to emergency medical services (EMS). Moreover, transport delays have been documented to affect stroke outcomes. This study aimed to examine the spatial variations in in-hospital mortality among patients with symptoms of stroke transferred by EMS, and determine its related factors using the auto-logistic regression model. METHODS: In this historical cohort study, we included patients with symptoms of stroke transferred to Ghaem Hospital of Mashhad, as the referral center for stroke patients, from April 2018 to March 2019. The auto-logistic regression model was applied to examine the possible geographical variations of in-hospital mortality and its related factors. All analysis was performed using the Statistical Package for the Social Sciences (SPSS, v. 16) and R 4.0.0 software at the significance level of 0.05. RESULTS: In this study, a total of 1,170 patients with stroke symptoms were included. The overall mortality rate in the hospital was 14.2% and there was an uneven geographical distribution. The results of auto-logistic regression model showed that in-hospital stroke mortality was associated with age (OR = 1.03, 95% CI: 1.01-1.04), accessibility rate of ambulance vehicle (OR = 0.97, 95% CI: 0.94-0.99), final stroke diagnosis (OR = 1.60, 95% CI: 1.07-2.39), triage level (OR = 2.11, 95% CI: 1.31-3.54), and length of stay (LOS) in hospital (OR = 1.02, 95% CI: 1.01-1.04). CONCLUSION: Our results showed considerable geographical variations in the odds of in-hospital stroke mortality in Mashhad neighborhoods. Also, the age- and sex-adjusted results highlighted the direct association between such variables as accessibility rate of an ambulance, screening time, and LOS in hospital with in-hospital stroke mortality. Thus, the prognosis of in-hospital stroke mortality could be improved by reducing delay time and increasing the EMS access rate.

The Effect of Pomegranate Juice and Sumac Consumption in the Treatment of Outpatients with COVID-19.

Introduction: COVID-19, an epidemic of coronavirus infection, has become a major global threat. The coronavirus mainly targets the human respiratory system, followed by cytokine storm, and altered immune responses associated with disease progression and adverse outcomes. Sumac and pomegranate juice are rich in bioactive compounds, which potentially have antiviral activities. This study is aimed at investigating the effect of a diet based on the use of sumac and pomegranate juice on the treatment of outpatients with COVID-19. Methods: In this study, 182 outpatients with COVID-19 were randomly divided into two groups receiving a diet containing pomegranate juice and sumac along with standard treatment and the control group (group 2) receiving standard treatment. Results: Consumption of a diet containing pomegranate juice and sumac in outpatients with COVID-19, who were receiving standard-of-care treatment, led to a significant decrease in fever, chills, cough, weakness, smell and taste disorders, shortness of breath, diarrhea, nausea and vomiting, and abdominal pain compared with outpatients with COVID-19 who received only standard treatment. Conclusion: Clinical trials of outpatients have limitations such as patients' resilience to post-COVID-19 follow-up. However, the use of pomegranate juice and sumac can be efficacious in reducing COVID-19 symptoms. This trial is registered with IRCT20190406043175N3.

Distinguishing characteristics of exposure to biguanide and sulfonylurea anti-diabetic medications in the United States.

OBJECTIVES: Biguanides and sulfonylureas are anti-hyperglycemic drugs commonly used in the United States. Poisoning with these drugs may lead to serious consequences. The diagnosis of biguanide and sulfonylurea poisoning is based on history, clinical manifestations, and laboratory studies. METHODS: This study is a six-year retrospective cohort analysis based on the National Poison Data System. Clinical effects of 6183 biguanide and sulfonylurea exposures were identified using binary logistic regression. RESULTS: The mean age of patients with biguanide and sulfonylurea exposure was 39.27 ± 28.91 and 28.91 ± 30.41 years, respectively. Sulfonylurea exposure is most commonly seen via unintentional exposure, while biguanide exposure frequently occurs as a result of intentional ingestion. Minor and moderate outcomes commonly developed following biguanide and sulfonylurea exposure, respectively. Sulfonylurea exposure was less likely to develop clinical effects abdominal pain, metabolic acidosis, diarrhea, nausea, vomiting, and elevated creatinine than patients ingesting biguanides. However, sulfonylurea exposure was more likely to cause dizziness or vertigo, tremor, drowsiness or lethargy, agitation, diaphoresis, and hypoglycemia. CONCLUSIONS: Our study is the first to use a wide range of national data to describe the clinical characteristics that differentiate the toxicologic exposure to biguanides and sulfonylureas. Sulfonylurea exposure is commonly seen via unintentional exposure, while metformin exposure is frequently seen via intentional exposure. Sulfonylurea toxicity is more likely to cause agitation, dizziness or vertigo, tremor, diaphoresis, and hypoglycemia, while metformin exposure induces abdominal pain, acidosis, diarrhea, nausea, vomiting, and elevated creatinine.

Comparison of Thyroid Function in Lead-Poisoned Patients and Healthy Individuals in Eastern Iran.

Lead (Pb) is a prevalent environmental toxic metal that may harmfully affect the function of the thyroid gland. Our information about the effects of lead on thyroid function in lead poisoning is limited. The present study aimed to evaluate thyroid function in lead-poisoned patients compared with the healthy group. In this study, two groups of lead poisoning subjects (lead concentrations ≥ 25 µg/dL) (n = 56) (HBLC group) and randomly selected age and gender-matched healthy individuals with lower blood lead concentrations (BLC < 10 µg/dL) (n = 58) (LBLC group) were included. Thyroid function tests, including thyroxine (T4), triiodothyronine (T3), and thyroid-stimulating hormone (TSH) concentration, were measured for each patient in both groups (for the HBLC group, it was taken on admission). The linear regression model was used to investigate the effects of lead poisoning on thyroid function tests. A p-value of less than 0.05 was considered significant. Our study showed no significant difference between the two groups in terms of age and gender. The mean concentration of T3 and TSH in the HBLC group was significantly lower than the LBLC group, but the mean levels of T4 were significantly higher in the HBLC group (p < 0.05). Based on the linear regression model results, the T3 and TSH levels in the LBLC group were significantly higher by 13.86 and 0.43 units than the HBLC group, respectively. The current study results showed that lead poisoning affects thyroid function, reduces TSH, and increases T4.

Prognostic factors of acetaminophen exposure in the United States: An analysis of 39,000 patients.

Acetaminophen is a frequently used over-the-counter or prescribed medication in the United States. Exposure to acetaminophen can lead to acute liver cytolysis, acute liver failure, acute kidney injury, encephalopathy, and coagulopathy. This retrospective cohort study (1/1/2012 to 12/31/2017) investigated the clinical outcomes of intentional and unintentional acetaminophen exposure using the National Poison Data System data. The frequency of outcomes, chronicity, gender, route of exposure, the reasons for exposure, and treatments as described. Binary logistic regression was used to estimate the prognostic factors and odds ratios (OR) with 95% confidence intervals (CI) for outcomes. This study included 39,022 patients with acetaminophen exposure. Our study demonstrated that the likelihood of developing severe outcomes increased by aging (OR = 1.12, 95% CI: 1.08-1.015) and was lower in females (OR = 0.88, 95% CI: 0.78-0.99). Drowsiness/lethargy (OR = 1.48, 95% CI: 1.22-1.82), agitation (OR = 1.66, 95% CI: 1.11-2.50), coma (OR = 23.95, 95% CI: 17.05-33.64), bradycardia (OR = 2.29, 95% CI: 1.22-4.32), rhabdomyolysis (OR = 8.84, 95% CI: 3.71-21.03), hypothermia (OR = 4.1, 95% CI: 1.77-9.51), and hyperthermia 2.10 (OR = 2.10, 95% CI: 1.04-4.22) were likely associated with major outcomes or death. Treatments included intravenous N-acetylcysteine (61%), oral N-acetylcysteine (10%), vasopressor (1%), hemodialysis (0.7%), fomepizole (0.1%), hemoperfusion (0.03%), and liver transplant (0.1%). In conclusion, it is important to consider clinical presentations of patients with acetaminophen toxicity that result in major outcomes and mortality to treat them effectively.

Toxic alcohol poisoning characteristics and treatments from 2000 to 2017 at a United States regional poison center.

BACKGROUND: Toxic alcohol exposures are an ongoing concern in the United States. In the US, few studies characterize the local epidemiology of toxic alcohols over time. OBJECTIVES: The objective was to examine the incidence of toxic alcohol ingestions and changes in management over time. METHODS: This retrospective cohort study evaluates toxic alcohol ingestion phone calls to a regional poison center in the United States covering four states. Data were queried for this poison center from the National Poison Data System (NPDS) using generic codes for each toxic alcohol. Inclusion criteria were ingestion of toxic alcohol, age ≥ 13 years, from January 1, 2000 to Dec 31, 2017. Exclusion criteria were unrelated effects coded in the medical outcome, duplicate data, or incomplete demographic data. RESULTS: Of 926 subjects (adults and teenagers), 71.5% were male, and the mean age was 34.5 years. Toxic alcohol ingestion was more common in individuals younger than 40 years, with a significant relationship between age and intentional abuse or misuse (p = 0.001). There was also a significant relationship between age and reason for ingestion, with younger patients more likely to be suicidal (p < 0.001). Ethyleneglycol was the most common toxic alcohol. There was no change in the incidence of toxic alcohol ingestions over the study period. The mortality rate was 1.7%, and 31.2%of patients were hospitalized in a critical care unit. Major effects and death were more common in younger patients (p < 0.001). There was a significant difference in medical outcomes based on the type of toxic alcohol(p = 0.03). Fomepizole was the most common treatment. A Poisson regression model found no change in fomepizole use during the study period (p = 0.1). Ethanol administration over the study period increased (p = 0.02), while hemodialysis decreased (p = 0.02). CONCLUSION: Data obtained from a single regional United States poison center showed low mortality related to toxic alcohol ingestions. The most prevalent toxic alcohol was Ethylene glycol. In all cases, toxic alcohol ingestion was higher in the 20-29-year-old age group. Reasons for ingestion, in most cases, were suicidal. Fomepizole was the most common treatment, ethanol administration as an antidote is rising, and hemodialysis utilization is decreasing. Data may not be nationally representative.

Effects of government policies and the Nowruz holidays on confirmed COVID-19 cases in Iran: An intervention time series analysis.

BACKGROUND: Public health policies with varying degrees of restriction have been imposed around the world to prevent the spread of coronavirus disease 2019 (COVID-19). In this study, we aimed to evaluate the effects of the implementation of government policies and the Nowruz holidays on the containment of the COVID-19 pandemic in Iran, using an intervention time series analysis. METHODS: Daily data on COVID-19 cases registered between February 19 and May 2, 2020 were collected from the World Health Organization (WHO)'s website. Using an intervention time series modeling, the effect of two government policies on the number of confirmed cases were evaluated, namely the closing of schools and universities, and the implementation of social distancing measures. Furthermore, the effect of the Nowruz holidays as a non-intervention factor for the spread of COVID-19 was also analyzed. RESULTS: The results showed that, after the implementation of the first intervention, i.e., the closing of universities and schools, no statistically significant change was found in the number of new confirmed cases. The Nowruz holidays was followed by a significant increase in new cases (1,872.20; 95% CI, 1,257.60 to 2,476.79; p<0.001)), while the implementation of social distancing measures was followed by a significant decrease in such cases (2,182.80; 95% CI, 1,556.56 to 2,809.04; p<0.001). CONCLUSION: The Nowruz holidays and the implementation of social distancing measures in Iran were related to a significant increase and decrease in COVID-19 cases, respectively. These results highlight the necessity of measuring the effect of health and social interventions for their future implementations.

Serum 25-OH Vitamin D Level in Psoriatic Patients and Comparison With Control Subjects.

BACKGROUND: Vitamin D has been shown to have immunomodulatory effects, and previous studies have proposed a role of vitamin D deficiency in multiple autoimmune diseases, including psoriasis. OBJECTIVES: The aim of this study was to investigate serum vitamin D levels in psoriatic patients and compare them with levels in controls. METHODS: This study was carried out in 50 psoriasis patients. Serum vitamin D was measured by enzyme-linked immunosorbent assay. RESULTS: The mean serum vitamin D levels in psoriatic patients and controls were 14.92 ± 6.31 and 12.52 ± 4.54 ng/mL, respectively. The difference was not statistically significant (P = .06). The prevalence of vitamin D deficiency (<20 ng/mL) was 84.0% in psoriatic patients and 93.0% in controls (P = .21). CONCLUSIONS: Most of the patients with psoriasis had vitamin D deficiency, which may have contributed to the evolution of their psoriasis. However, considering the high prevalence of vitamin D deficiency in Iran, no difference was noted between the psoriatic patients and the controls.