logistic models

It could be beneficial to accelerate the hospitalization of patients with the identified clinical risk factorsof intensive care unit (ICU) admission, in order to control and reduce COVID-19-related mortality. This study aimedto determine the clinical risk factors associated with ICU hospitalization of COVID-19 patients.

The currentresearch was a cross-sectional study. The study recruited 7182 patients who had positive PCR tests between February 23,2020, and September 7, 2021 and were admitted to Afzalipour Hospital in Kerman, Iran, for at least 24 hours. Their demo-graphic characteristics, underlying diseases, and clinical parameters were collected. In order to analyze the relationshipbetween the studied variables and ICU admission, multiple logistic regression model, classification tree, and supportvector machine were used.

It was found that 14.7 percent (1056 patients) of the study participants were admit-ted to ICU. The patients’ average age was 51.25±21 years, and 52.8% of them were male. In the study, some factors suchas decreasing oxygen saturation level (OR=0.954, 95%CI: 0.944-0.964), age (OR=1.007, 95%CI: 1.004-1.011), respiratorydistress (OR=1.658, 95%CI: 1.410-1.951), reduced level of consciousness (OR=2.487, 95%CI: 1.721-3.596), hypertension(OR=1.249, 95%CI: 1.042-1.496), chronic pulmonary disease (OR=1.250, 95%CI: 1.006-1.554), heart diseases (OR=1.250,95%CI: 1.009-1.548), chronic kidney disease (OR=1.515, 95%CI: 1.111-2.066), cancer (OR=1.682, 95%CI: 1.130-2.505),seizures (OR=3.428, 95%CI: 1.615-7.274), and gender (OR=1.179, 95%CI: 1.028-1.352) were found to significantly affectICU admissions.

As evidenced by the obtained results, blood oxygen saturation level, the patient’s age, andtheir level of consciousness are crucial for ICU admission.

Laryngeal damages after chemoradiation therapy (RT) in nonlaryngeal head‑and‑neck cancers (HNCs) can cause voice disorders and finally reduce the patient’s quality of life (QOL). The aim of this study was to evaluate voice and predict laryngeal damages using statistical binary logistic regression (BLR) models in patients with nonlaryngeal HNCs.

This cross‑section experimental study was performed on seventy patients (46 males, 24 females) with an average age of 50.43 ± 16.54 years, with nonlaryngeal HNCs and eighty individuals with assumed normal voices. Subjective and objective voice assessment was carried out in three stages including before, at the end, and 6 months after treatment. Eventually, the Enter method of the BLR was used to measure the odds ratio of independent variables.

In objective evaluation, the acoustic parameters except for F0 increased significantly (P < 0.001) at the end treatment stage and decreased 6 months after treatment. The same trend can be seen in the subjective evaluations, whereas none of the values returned to pretreatment levels. Statistical models of BLR showed that chemotherapy (P < 0.05), mean laryngeal dose (P < 0.05), V50 Gy (P = 0.002), and gender (P = 0.008) had the greatest effect on incidence laryngeal damages. The model based on acoustic analysis had the highest percentage accuracy of 84.3%, sensitivity of 87.2%, and the area under the curve of 0.927.

Voice evaluation and the use of BLR models to determine important factors were the optimum methods to reduce laryngeal damages and maintain the patient’s QOL.

Health companies need investment for development. Due to the high risk of their activities, it is very difficult to attract investment for this field, but this lack of financial resources leads to the failure of these companies, so providing a model for predicting profits and losses in companies is very important and functional.

In this study, a combination of two logistic regression al gorithms and differential analysis were used to design a profit and loss forecasting model. Also, the information of 20 companies in the field of health was used to evaluate the proposed model. 10 profitable companies and 10 loss - making companies were sele cted and for each company, nine variables independent of the financial information of these companies were collected.

The designed prediction model was implemented on the data in this study. To do this, the data were divided into two sets: trainin g and testing. The prediction model was implemented on training data and evaluated by test data and reached 99.65% sensitivity, 94.75% specificity and 96.28% accuracy. The proposed model was then compared with the methods of decision tree C4.5, Bayesian, s upport vector machine, nearest neighborhood and multilayer neural network and it was found to have a better output.

In this study, it was found that the risk in the field of health investment can be reduced, so the profit and loss situation of health companies can be predicted with appropriate accuracy. It was also found that the combination of logistic regression and differential analysis algorithms can increase the accuracy of the prediction model.

One of the main health problems in the world is hepatitis B virus (HBV) infection. Vaccination and other factors can affect HBV infection. As various effective factors have been reported in different regions and studies, this study aimed to investigate the association between HBV infection and routine vaccination and other effective factors 25 years since the launch of the national vaccination program in Iran. This cross-sectional study, conducted in 2017 in Shiraz (Iran), investigated factors such as demographic variables such as gender, education, and occupation, vaccination status, and the potential risk factors for HBV infection. Hepatitis B surface antigen (HBsAg) and anti-hepatitis B core antibody (HBc Ab) tests were performed to determine HBV infection status. The data were analyzed using R software (version 3.5.2), using multivariate logistic regressions and machine learning methods. The level of significance was considered below 0.05. A total of 2720 individuals were enrolled in the study (194 cases with HBV infection). Based on the logistic regression analyses, factors such as a family history of the disease (OR=2.53, p <0.001), vaccination (OR=0.57, P=0.004), a history of high-risk behaviors (OR=1.48, P=0.022), and occupation (OR=1.80, P=0.035) were significantly associated with HBV infection. Based on the conditional tree method, a family history of infection (p <0.001) and vaccination (P=0.023) were two important factors in classifying individuals for HBV infection. Based on the different methods applied in this study, HBV infection was affected by factors such as a family history of the disease, national HBV vaccination, and occupation. It appears that HBV vaccination, launched by the Iranian Ministry of Health and Medical Education in 1993, has reduced HBV infection.

The Gail model is the most well-known tool for breast cancer risk assessment worldwide. Although it was validated in various Western populations, inconsistent results were reported from Asian populations. We used data from a large case-control study and evaluated the discriminatory accuracy of the Gail model for breast cancer risk assessment among the Iranian female population.

We used data from 942 breast cancer patients and 975 healthy controls at the Cancer Institute of Iran, Tehran, Iran, in 2016. We refitted the Gail model to our case-control data (the IR-Gail model). We compared the discriminatory power of the IR-Gail with the original Gail model, using ROC curve analyses and estimation of the area under the ROC curve (AUC).

Except for the history of biopsies that showed an extremely high relative risk (OR=9.1), the observed ORs were similar to the estimates observed in Gail's study. Incidence rates of breast cancer were extremely lower in Iran than in the USA, leading to a lower average absolute risk among the Iranian population (2.78, ±SD 2.45). The AUC was significantly improved after refitting the model, but it remained modest (0.636 vs. 0.627, ΔAUC = 0.009, bootstrapped P=0.008). We reported that the cut-point of 1.67 suggested in the Gail study did not discriminate between breast cancer patients and controls among the Iranian female population.

Although the coefficients from the local study improved the discriminatory accuracy of the model, it remained modest. Cohort studies are warranted to evaluate the validity of the model for Iranian women.

Alcohol use and drug injection are prevalent among homeless youths. The aim of this study wasto identify the associated factors of alcohol consumption and drug injection among homeless youths aged18-29 years.

Data on 202 homeless youths (111 males and 91 females) were collected using a standardizedquestionnaire and face-to-face interview. Lasso logistic regression was applied to determine the impact ofassociated factors on alcohol consumption and drug injection.

The mean age of the participants was 26.30 ± 3.19 years. Also, the prevalence of alcoholconsumption and drug injection was 33.0% [95% confidence interval (CI): 30-36] and 4.0% (95% CI: 0-8),respectively; 6 people (3.0%) consumed alcohol and injected drugs at the same time. Correlates of alcoholconsumption and drug injection were male sex [odds ratio (OR)Alc = 5.7], age (ORAlc = 0.96 and ORDI = 0.98),bachelor or higher education level (ORAlc = 1.34), non-Iranian nationality (ORAlc = 0.05 and ORDI = 0.18),food score (ORDI = 0.92), smoking (ORAlc = 2.05), substance use (ORAlc = 1.12), opposite sex relationship(ORAlc = 1.6), homosexual relationship (ORAlc = 3.56 and ORDI = 2.69), and mental disorder (ORAlc = 0.99).

Based on our findings, it seems that the homeless youth are more desired to use alcohol and druginjection, whereas the prevalence of alcohol consumption and drug injection in homeless youth was higherthan general youth population in Iran. Therefore, some suitable solutions are needed to prevent thehomelessness. Also, the effective variables that were identified in this study for alcohol use and drug injectioncan help design and implement beneficial interventions.

One of the most reliable sources of financing healthcare costs is healthinsurance. Covering all the services by basic health insurance is not affordable economically, so that some services are covered by supplementary health insurances. This study aimed to determine the factors influencing buying the different levels of Kowsar supplementary health insurance by the staff of Shiraz University of Medical Sciences in 2014-2015.

This is a cross-sectional study. Two data collection forms were used to collect thedata. A sample size of 500 was determined using the rule of thumb. The individuals wereselected via using two-stage stratified and systematic sampling. To do the estimation, theordinal logistic regression model (link function was logit) was specified by the one-sidedsignificant variable tests at the first step. Then, the independent variables were examined by the link test, and the linear relationship among variables was also investigated. The software Excel 2010 and STATA 11.0 (stata corp LLC) were used in this paper.

 The findings showed that among the people with supplementary insurance, themajority were males (60%), married (85%), with the basic Tamin Ejtemaei insurance (72.3%). Among those who have not chosen the supplementary health insurance, the largest number were women (69%), unmarried (53%), and insured by Tamin Ejtemaei (80%), respectively. The findings suggest that some factors such as the age, gender, income and cost of insurance packages are the most influential factors on buying different levels of health care insurance. In the first model that included people with supplementary insurance, the income elasticity was significant and positive (Beta=3, P=0.047) and price elasticity of demand was negative (Beta=-0.06, P=0.001). In the second model that complemented those with and without supplementary insurance, the income elasticity was insignificant (Beta=2.46, P=0.085), and the demand price elasticity was negative (Beta=-0.06, P=0.001).

 The economic factor seems to be the most influential factor in choosingsupplementary insurance. Since this problem causes the low-income households not to usethe insurance; therefore, the government is required to allocate some subsidies for low income household to be covered by supplementary health insurance for special services.

General medical degree (GMD) curriculum usually causes significant psychological distress for medical students, especially in transition periods between preclinical, clerkship, and internship periods. This study was conducted to assess the effect of curricular change in GMD program on mental health of medical students in internship period. This study evaluated mental health of 2 concurrent groups of medical students under reformed and non-reformed GMD curriculum. In this study, 120 out of 180 interns in the non-reform GMD program and 60 interns in the reformed GMD program were selected and their mental health status evaluated using Symptom Checklist-90-Revised (SCL-90-R) questionnaire. The cut-off point of 0.7 was used for Global Severity Index (GSI) score. SPSS software, version 14 (SPSS Inc, Chicago, Il, USA) was used for analysis. Chi-square, Fisher’s exact test, t student, Mann–Whitney U, one-way ANOVA, and Kruskal-Wallis tests were used when appropriate. Logistic regression was used to estimate odds ratios for various determinants of students’ mental health. About half of the participants in the 2 groups were male (P = 0.63), and the mean age of the students in the reformed and non-reformed programs was 24.8 (1.97) and 24.7(1.80), respectively (P = 0.9). About 20% of participants in the non-reformed and less than 2% of those in the reformed program had GSI score of more than 0.7. Medical students in the reformed program had lower scores in total GSI and 9 its dimensions (P<0.001). The results obtained from the logistic regression analysis indicated that reformed curriculum and good economic status were significant independent variables contributing to decreased psychological distress (OR = 0.016 and 0.11, respectively). The results revealed that curricular changes which were based on World Federation of Medical Education recommendation, could be associated with improvement in mental health status of medical students.

This retrospective study aimed to investigate the physicochemical properties of drinking water sources in Ethiopia and compare the water quality with the health-based target. For this purpose, the water quality database of Ethiopian Public Health Institute (EPHI) from 2010 to 2016 was used. The concentration and other properties of the water samples were analyzed according to the Standard Methods of Water and Wastewater analysis. Quality control and quality assurance were applied in all stages following our laboratory standard operation procedures (SOPs). The concentration of the selected parameters varied based on the type of water sources. The mean concentration of turbidity was higher in spring water (21.3 NTU) compared to tap (12.6 NTU) and well (3.9 NTU) water sources. The mean concentration of total dissolved solids (TDS), electrical conductivity (EC), sodium (Na+), and sulfate (SO4-2) was found to be higher in spring water sources than tap and well water sources. Comparably, the concentration of hardness, calcium, and magnesium was found to be higher in well water sources than spring and tap water sources. The bivariate analysis indicated that out of 845 analyzed water samples, more than 50% of the samples from Oromia region had turbidity, pH, TDS, hardness, Ca++, K+, and Na+ within an acceptable limit. In addition, the logistic regression analysis showed that water quality parameters were strongly associated with the type of water sources and regional administration at P < 0.05. More than 80% of the samples analyzed from drinking water sources were in agreement with WHO guidelines and national standards. However, the remaining 20% specifically, pH (25%), calcium (20%), hardness (18.1%), TDS (15.5%), and turbidity (13.3%) analyzed from improved water sources did not comply with these recommendations. Due to objectionable or unpleasant taste, people may force to look for alternative unprotected water sources that lead to health concerns.

US adolescent obesity rates have quadrupled over the past 3 decades. Research examining complex factors associated with obesity is limited. The purpose of this study was to utilize a representative sample of students (grades 6 - 8) in Tennessee to determine the co-occurrence of risk behaviors with adolescent obesity prevalence and to analyze variations by strata. Patients and Methods: The 2010 youth risk behavior survey dataset was used to examine associations of obesity with variables related to sample demographics, risk and protective behaviors, and region. Hierarchical logistic regression analyses stratified by demographics and region were conducted to evaluate variation in obesity risk occurring on three hierarchical levels: class, school and district. The sample consisted of 60715 subjects. The overall obesity rate was 22%. High prevalence of obesity existed in males, non-white race, those ever smoked and was positively correlated with age. Across three state regions, race, gender, and specific behaviors (smoking, weight misperception, disordered eating, +3 hours TV viewing, and no sports team participation) persisted as significant predictors of adolescent obesity, although variations by region and demographics were observed. Multilevel analyses indicate that < 1%, 0 - 1.97% and 4.03 - 13.06% of the variation in obesity was associated with district, school and class differences, respectively, when stratifying the sample by demographic characteristics or region. Uniform school-based prevention efforts targeting adolescent obesity risk may have limited impact if they fail to respond to geographical and demographic nuances that hierarchal modeling can detect. Study results reveal that stratified hierarchical analytic approaches to examine adolescent obesity risk have tremendous potential to elucidate significant prevention insights.

Awareness of the food security status of rural population and its influencing factors is essential for policy makers, public health institutions and the development of rural programs. This descriptive cross-sectional study was conducted in 2017 on 384 rural households in Bam city. The data was collected via the 6-item USDA questionnaire. Logistic regression was used to determine the relationship between social, economic and health factors with food security. The results indicate that 35.67% of households had full food security status, 24.47% had medium food security status and 7.04% had food insecurity status. Despite the high level of food insecurity in Bam rural households, creating employment opportunities for increasing household income, reforming inappropriate food habits, and increasing households’ nutritional awareness might be effective in promoting food security.

Since injury-related mortality is preventable, identifying factors that inversely affect trauma outcome are important initial steps towards reducing injury burden..
This study aims to determine independent risk factors of early/late in-hospital mortality among adult trauma victims with equal injury characteristics and severity at Shahid Rajaee (Emtiaz) Hospital during 2013 and 2014..
Patients and A cross-sectional study of adult trauma patients (age ≥ 15 years) sustaining injury through traffic accidents, violence, and unintentional incidents was conducted. Information was retrieved from three hospital administrative databases. Data on demographics, injury mechanisms, injured body regions, injury descriptions, outcomes of hospitalization, and development of nosocomial infections were recorded. Injury severity score was calculated by cross walking from international classification of diseases (ICD-10) injury diagnosis codes to abbreviated injury scale (AIS-98) severity codes. Two multiple logistic regression models were employed to reflect the partial effect of each covariate on early (within 48 hours) and late (beyond 48 hours) deaths..
There were 47,295 hospitalized patients (male/female ratio: 2.7:1.0) with a median age of 30 years (interquartile range 23 - 44 years). A crude mortality rate of 1% (454 cases) was observed and 52% of deaths occurred within 48 hours of hospital arrival. One percent developed a nosocomial infection in the course of admission. After adjusting for covariates, sustaining a thoracic injury (OR 8.5, 95% CI [4.7 - 15.2]), ISS over 16 (OR 6.4, 95% CI [3.6 - 11.4]) and age over 65 years (OR 5.1, 95% CI [3.0 - 8.8]) were the most important independent risk factors of early trauma death. Presence of a hospital-acquired infection (OR 12.7, 95% CI [8.9 - 18.1]), age over 65 years (OR 7.4 95% CI [4.5 - 12.1]), and ISS of more than 16 (OR 14.6, 95% CI [6.2 - 34.3]) were independent predictors of late death..
Age, injury severity, injured body region, and hospital-acquired infections are important determinants of trauma outcome in our center. Timely recognition of factors affecting trauma mortality is crucial for monitoring changes of trauma quality of care. Our findings suggest the need to allocate resources for trauma prevention along with a potential focus on reducing in-hospital complications..

Family physician plans in Iran face several challenges, one of which is developing attractive and efficient contracts that motivate physicians to participate in the plan.
This study aimed to elicit GPs’ preferences for family physician contracts.
Patients and In a cross-sectional study using the conjoint analysis technique, 580 GPs selected from the family physician database in Iran in 2014. Through qualitative and quantitative methods, 18 contract scenarios were developed via orthogonal design i.e., the impact of each attribute is measured independently from changes in other attributes and a questionnaire was developed. Data were collected through this questionnaire and analyzed using the ordered logistic regression (OLR) model.
The results show that “quotas for admission to specialized courses” is the strongest preference of GPs (β = 1.123). In order of importance, the other preferences are having the right to provide services outside of the specified package (β = 0.962), increased number of covered population (β = 0.814), capitation payment 15% bonus (β = 0.644), increased catchment area to 5 km (β = 0.349), and increased length of contract to five years (β = 0.345).
The conjoint analysis results show that GPs concerned about various factors of family physician contracts. These results can be helpful for policy-makers as they complete the process of creating family physician plans, which can help increase the motivation of GPs to participate in the plan.