Publications by authors named "Laleh Gharacheh"

3 Publications

  • Page 1 of 1

The Comparison of Direct Laryngoscopy and Video Laryngoscopy in Pediatric Airways Management for Congenital Heart Surgery: A Randomized Clinical Trial.

Anesth Pain Med 2020 Jun 9;10(3):e99827. Epub 2020 Jun 9.

Student Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.

Background: Airway management in patients with hereditary heart disease is an important therapeutic intervention.

Objectives: The purpose of this study was to compare direct laryngoscopy (DL) with video laryngoscopy (VL) in pediatric airways management for congenital heart surgery.

Methods: This study was designed as a prospective randomized clinical trial. Two consecutive groups of 30 patients undergoing elective noncyanotic congenital heart surgery. The patients were divided into direct laryngoscopy versus video laryngoscopy for intubation of the trachea. The main outcomes were the number of success rate in the first attempt, and the secondary outcomes were the duration of successful intubation and complications, such as desaturation and bradycardia.

Results: Intubation procedure time was measured as 51.13 ± 17.88 seconds for the group with direct laryngoscopy and 59.66 ± 45.91 seconds for group with VL that was significant (P = 0.006). In DL group, 22 patients were intubated on the first attempt, 8 patients on the second attempt, and 6 patients on the third attempt, compared to 24, 6, and 2 respectively, in VL group. The differences were significant only in the third attempt between groups (P = 0.033). The important difference established in heart rate (HR) and SpaO amounts between the two groups at any time (P < 0.05).

Conclusions: VL can produce better visualization for intubation of trachea in congenital heart disease, but this is time-consuming. Indeed, training in the use of the VL should be increased to reduce the time required for performance. Moreover, further studies are recommended to approve these helpful findings.
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http://dx.doi.org/10.5812/aapm.99827DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472645PMC
June 2020

Comparison of Responsiveness Level in Iranian Public and Private Physiotherapy Clinics: a Cross-Sectional Multi-center Study.

Mater Sociomed 2017 Sep;29(3):172-175

Musculoskeletal Rehabilitation Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

Introduction: Responsiveness is a main goal of health systems. Responsiveness focus on the non-medical aspects of health services delivery. This study was aimed to assess responsiveness level in public and private physiography clinics.

Methods: In this multicenter cross sectional study, 403 patients refers to 16 public and 64 private physical therapy clinics were studied randomly in Ahvaz, Iran, from 2013 to 2014. Data were collected based on a valid health system responsiveness questionnaire that was developed by WHO. Health system responsiveness questionnaire for outpatients care includes seven components and 25 questions. Statistical relationship between responsiveness level of centers and patients characteristics was analyzed using Pearson coefficient, Independent t-test and one-way ANOVA.

Results: Out of 403 patients, 299 (74.19%) patients were women. The mean (±SD) age of the patients was 42(±14.18) years and 92.1% of patients were 65> years. Responsiveness status in private and public physiotherapy clinics was assessed excellent (26.93±5.2) and very well (21.08±5.8) respectively. In private clinics, the mean score of communication dimension (3.96±1) and autonomy dimension (3.95±0.9) was higher than other dimensions. In public clinics the mean score of dignity (3.30±0.8), autonomy (3.16±0.9), and prompt attention (3.12±1) was higher than other areas respectively. In public and private clinics, quality of basic amenities area had the lowest score.

Conclusions: The results showed that the some patients and center characteristics such as gender and work shift were factors affecting assessment of responsiveness. Responsiveness level in private centers was better than publics.
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http://dx.doi.org/10.5455/msm.2017.29.172-175DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5644192PMC
September 2017

Comparison of Statistical Models of Predict the Factors Affecting the Length of Stay (LOS) in the Intensive Care Unit (ICU) of a Teaching Hospital.

Mater Sociomed 2017 Jun;29(2):88-91

Department of Internal Medicine, Imam Khomeini hospital, Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

Introduction: Modeling can be a useful tool to find out how the distributions of hospital length of stay (LOS) and the factors affecting the length of stay. The present study aims to determine factors affecting the length of stay and selecting suitable statistical models.

Material And Method: this is a cross - sectional study of 565 patients who were treated in the intensive care unit of Imam Khomeini hospital in Ahwaz. Preliminary data were collected retrospectively through the medical records of all patients admitted on intensive care units of Ahwaz Imam Khomeini Hospital in 2015. Statistical analysis and multivariate regression models were done using of SPSS 21 and STATA 7 software.

Results: Average length of stay in ICU was 8.16±0.75 days. The Mean and Median age of patients were 58.61±20 and 61 respectively, The Mean LOS for females (16.44±9.37 days) was more than the men (11.5±5.35 days) (p<0.01). The maximum and minimum lengths of stay belonged to patients with endocrine disorders (14.7±3.1 days) and patients with gastrointestinal disorders (5.53±1.1 days) respectively (p<0.01). The goodness of fit for Gamma model showed that this model was more suitable and powerful than Log-normal model to predict the factors affecting the patient's length of stay in intensive care units of hospital.

Conclusion: Gamma regression model was more robust to predict factors regarding the hospital length of stay. According to Gamma model the key factor in predicting the length of stay in ICU was the type of disease diagnosis. The result of statistical modeling can help managers and policy makers to estimate hospital resources and allocate them for different hospital services.
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http://dx.doi.org/10.5455/msm.2017.29.88-91DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5544439PMC
June 2017