Impact of maternal psoriasis on adverse maternal and neonatal outcomes: a systematic review and meta-analysis.

BACKGROUND: There is a dearth of robust evidence regarding the correlation between psoriasis with maternal and neonatal outcomes, making it challenging to establish definitive recommendations for the management of these patients. This systematic review and meta-analysis aimed to review the evidence with regard to the impact of maternal psoriasis on maternal and neonatal outcomes. METHODS: Following the PRISMA guideline, a systematic search of English articles using PubMed, Embase, Scopus, ScienceDirect, Web of Science, Google Scholar, and the Cochrane Library was conducted. The search was performed from inception to 22nd of May 2022. RESULT: A significant association was observed between psoriasis and maternal outcomes, including cesarean delivery [OR = 1.25 (95% CI: 1.13-1.30, p-value = 0.001)], (pre)eclampsia [OR = 1.29 (95% CI: 1.15-1.44, p-value = 0.0001)], gestational diabetes [Odds Ratio (OR) = 1.23 (95% Confidence Intervals (CI): 1.15-1.30, p-value = 0.001)], gestational hypertension [OR = 1.31 (95% CI: 1.18-1.45, p-value = 0.001)] and preterm birth [OR = 1.22 (95% CI: 1.10-1.35, p-value = 0.001)]. Also, there was a significant association between psoriasis and neonatal outcomes, including small for gestational age [OR = 1.07 (95% CI: 1.02-1.11, p-value = 0.053)], low birth weight [OR = 1.19 (95% CI: 1.02-1.38, p-value = 0.001)] and stillbirth [OR = 1.27 (95% CI: 1.04-1.55, p-value = 0.023)]. CONCLUSION: Maternal psoriasis could negatively impact maternal and neonatal outcomes. Our results strengthen the importance of close monitoring of the mothers' psoriasis status before and during pregnancy.

Incidence, accuracy, and barriers of diagnosing healthcare-associated infections: a case study in southeast Iran.

BACKGROUND: Healthcare-associated infections (HAIs) are a threat to patients. Accurate surveillance is required to identify and prevent HAIs. To estimate the incidence rate, report the accuracy and identify the barriers of reporting HAIs using a mixed-method study. METHODS: In this quantitative study, we externally evaluated the incidence rate and accuracy of the routine surveillance system in one of the main hospitals by an active follow-up of patients from September to December 2021. We used in-depth interviews with 18 experts to identify the barriers of the routine surveillance system. RESULTS: Among 404 hospitalized patients, 88 HAIs were detected. The estimated rate of HAIs was 17.1 (95% Confidence Intervals 95: 14.1, 21.1) per 1000 patient-days follow-up. However, in the same period, 116 HAIs were reported by the routine surveillance system, but the agreement between the two approaches was low (sensitivity = 61.4%, specificity = 82.6%, negative predictive value = 89.7%, and positive predictive validity = 46.5%). The minimum and maximum positive predictive values were observed in urinary tract infection (32.3%) and surgical site infection (60.9%). The main barrier of reporting HAIs was lack of cooperation in reporting HAIs by infection control link nurses and laboratory supervisors. CONCLUSIONS: The discrepancy between the longitudinal study findings and the routine surveillance might be related to the inaccessibility of the surveillance system to clinical information of patients. In this regard, decreasing the barriers, increasing the knowledge of infection control nurses and other nurses, as well as the development of hospital information systems are necessary.

The prevalence and predictors of herb-drug interactions among Iranian cancer patients during chemotherapy courses.

BACKGROUND: The concurrent usage of herbal medicines with conventional therapies is an important concern in cancer treatment which can lead to unexpected consequences like herb-drug interactions. This study aimed to determine the prevalence of potential herb-drug interactions and to predict factors associated with herb-drug interactions for cancer patients. METHODS: This cross-sectional study was conducted among a convenience sample of 315 cancer patients referring to the oncology clinics of Kerman city in 2018. Data were collected via comprehensive face-to-face interviews and medical chart reviews. A drug interaction checker was used to determine herb-drug interactions. The information of patients was compared based on herb-drug interactions using bivariable logistic regression models, and predictors were determined by the multivariable logistic regression model. All analyses were performed by Stata software version 16. RESULTS: Of 262 patients (83.2% of the patients) who used herbal medicines, 209 patients [79.8% (95% Confidence Intervals (CI): 75.2 - 85.1)] had potential herb-drug interactions. Chamomile was the most popular herbal medicine (n = 163, 78.0%), and minor and moderate herb-drug interactions were caused by green tea (n = 34, 16.3%) and peppermint (n = 78, 37.5%). The number of chemotherapeutic agents (OR: 1.92, 95% CI: 1.43-2.58; P-value < 0.0001) and the experienced of pain during chemotherapy courses (OR = 2.22, 95%CI:1.00-4.94; P-value = 0.04) were some of the predictors of herb-drug interactions among cancer patients. CONCLUSION: Herbal medicine use during chemotherapy was found prevalent among cancer patients; of them, the experience of potential herb-drug interactions was highly frequent. Oncologists and clinical pharmacologists are recommended to take into account challenges associated with herb-drug interactions in their routine practices, particularly during chemotherapy among these patients.

The Prevalence of Polypharmacy and Potential Drug-Drug Interactions among Iranian Cancer Patients: Which Patients were at Risk?

INTRODUCTION: Drug-Drug interactions (DDIs) are one of the considerable consequences of polypharmacy. Due to the influence of polypharmacy and drug interactions on cancer treatment and patients` health outcomes, this study aimed to determine the prevalence of polypharmacy and potential DDIs among adult cancer patients in Kerman province, southeast of Iran. METHODS: In this cross-sectional study, 315 cancer patients who referred to Kerman city oncology clinics were assessed in 2018. Data were collected through face-to-face interviews and medical charts were reviewed. Polypharmacy was defined as the use of at least five drugs simultaneously. Potential DDIs were checked using the "Drugs.com" online database. A bivariable and a multivariable logistic regression were used to determine the associated factors of outcome variables, polypharmacy status, and potential DDI in SPSS software version 23. RESULTS: Of 315 cancer patients, 191 patients (60.6%; 95% CI: 54.9, 66) used at least five drugs during chemotherapy courses. The prevalence of potential DDIs was 59.6% (n = 140, 95% confidence interval [CI]: 53.6-66.0. Experience co-morbid diseases (OR: 6.60; 95% CI: 3.82, 11.42; p value ≤ .0001), and positive metastatic status (OR: 2.80; 95% CI: 1.62, 4.82; p value ≤ .0001) could predict the polypharmacy during chemotherapy courses. Patients who suffered gastrointestinal cancers (OR: 5.55; 95% CI: 2.26, 13.62; p value ≤ .0001) and the number of prescribed or Over The Counter (OTC) drugs (OR: 1.29; 95% CI: 1.12, 1.48; p value < .0001) predicted the occurrence of potential DDIs among cancer patients. CONCLUSIONS: Regarding the high prevalence of polypharmacy and potential drug interactions among Iranian cancer patients during chemotherapy courses, it is advisable for physicians, nurses, and pharmacists to be vigilant to improve prescribing patterns. In addition, with intensive monitoring, alternative treatment strategies can be replaced.

Challenges and strategies of clinical rounds from the perspective of medical students: A qualitative research.

INTRODUCTION: Clinical rounds provide opportunities for medical students to acquire essential skills to practice medicine in the real world. Although this kind of training is one of the most important components of medical education, it is replete with barriers in its effective implementation. This study aimed to investigate medical students' experiences concerning the barriers and strategies of clinical rounds in Kerman University of Medical Sciences (KMU). MATERIALS AND METHODS: This qualitative research was conducted on 12 medical students in KMU in 2017. Purposive sampling was used and participants in three grades (stagers, interns, and residents) were selected, and individual semi-structured interviews were conducted until data saturation. The average of the interview time differed among the three batches (stagers, 51 min; interns, 38 min; and residents, 31 min). Content analysis using deductive approach was used for data analysis. MAXQDA version 10 was used for data analysis. RESULTS: Data analysis yielded the identification of six themes related to the system of clinical education, fields of clinical education, clinical environment, educational program, medical teachers, and medical students concerning the barriers and five themes related to the strategies for clinical rounds. CONCLUSIONS: Findings revealed a deeper understanding of medical students' experiences. Our investigation identified multiple challenges embedded in our context and strategies to overcome them. As teaching in clinical rounds is invaluable, there is a need to take into account the identified challenges and overcome them. Thus, more effective rounds with higher efficacy toward students' professional development can be implemented.

Identifying the challenges to good clinical rounds: A focus-group study of medical teachers.

INTRODUCTION: The use of clinical rounds, as an integral part of clinical teaching to help medical students acquire essential skills of practicing medicine, is critically important. An understanding of medical teachers' perceptions concerning the challenges of clinical rounds can help identify the key areas of focus to better foster professional development of medical students. This study explored the opinions of medical teachers of Kerman University of Medical Sciences about the challenges embedded in clinical rounds. There is a paucity of studies regarding the topic under investigation in our context. METHODS: This qualitative study was conducted using a conventional content analysis method. We held a focus group discussion with eight skilled bedside teachers, chosen using purposive sampling, from Kerman University of Medical Sciences in February 2018. The focus group lasted for approximately 2 hours. The session was audio-taped. We analyzed data by considering the verbatim transcribed document of the audio-recorded discussions using conventional content analysis method for theme development. Informed consent was obtained from the participants. RESULTS: Medical teachers described many primary challenges to clinical rounds. Some of them were multiple students on rounding practices, time constraints, priority of research and patient care to teaching, and lack of participation and enthusiasm. We categorized these varied challenges into 5 specific areas related to (1) system; (2) teachers; (3) learners; (4) patients; and (5) evaluation issues. Focus group participants expressed some suggestions to mitigate barriers such as having fewer students on the rounds, addressing time constraints through planning and flexibility, and the provision of medical education award. CONCLUSION: Clinical round practices are valuable but replete with a spectrum of problems. Many challenges affect the quality of teaching in clinical rounds that should be taken into account by bedside teachers in order to improve the quality of rounding practices. The identified challenges can be used in redressing bedside teaching to have more efficient rounding practices.

Strategies for teaching in clinical rounds: A systematic review of the literature.

BACKGROUND: Strategies for teaching in clinical rounds are dispersed. There is a need to comprehensively collate bedside strategies to enhance teaching and learning and make clinical rounds more effective. MATERIALS AND METHODS: A systematic review of English articles using Web of Science, PubMed, Embase, Scopus, and Cochrane library was conducted. Relevant keywords for teaching rounds/medical teachers/medical students/strategies and their synonyms were used accordingly. Additional studies were identified by searching reference lists of retrieved articles. All searches were conducted within a 10-day period from May 25, 2017, to June 3, 2017. In this systematic review, studies with any design on the subject of strategies for clinical rounds from clinical teachers' and medical students' perspectives were identified. Our search strategy yielded 524 articles. After removing duplicates, 337 articles remained. Based on the title and abstract review, 37 articles were obtained for further review and finally 18 entered the study. Data were extracted from the included studies. Two authors independently screened and scored the studies. We used inductive content analysis, and categories of strategies were derived from the data. RESULTS: Content analysis yielded identification of strategies for clinical rounds in nine categories named: system issues, advance planning, a preround huddle, patient issues, teachable moments, teacher issues, student issues, atmosphere issues, and a postround huddle. These were classified as "before rounds," "during rounds," and "after rounds" activities. Quality assessment scores for the research studies ranged from 5 to 14 (possible range, 1-16). Fourteen (77.8%) studies received quality scores at or above 10, and 4 (22.2%) studies received quality scores below 10. CONCLUSION: Due to the importance of clinical rounds in students' learning, medical teachers should divide their teaching session into activities before, during, and after rounds. These strategies on rounding practices can improve teaching and learning.

The perspective of medical students regarding the roles and characteristics of a clinical role model.

BACKGROUND: As medical students spend most of their time with their clinical teachers and imitate their roles and characteristics during the school year, it is important to identify the roles and characteristics that they find essential in their role models. These traits play a part in their future professions as doctors. OBJECTIVE: The aim of this study was to determine the perspective of students, interns, and residents regarding the roles and characteristics of a clinical role model. METHODS: In an analytical cross-sectional study, a structured and self-developed questionnaire was completed by 185 medical students at educational hospitals of Kerman University of Medical Sciences during April and May 2015. Participants were selected using convenience sampling method. For data analysis, we used descriptive and inferential statistics. SPSS software version 16 was used as needed. RESULTS: In total, 90 medical students (48.7%), 65 interns (35.1%), and 30 residents (16.2%) participated in this study. Male respondents (n=75) comprised 40.5% and female respondents (n=110) 59.5% of the study sample. The three most important roles of a clinical teacher were organizer role (99.7), teacher role (101.7), and supporter role (109.5) for students, interns, and residents respectively. On the other hand, supporter role (85.4), communicator role (86.4) and organizer role (83.4) were ranked as the least important for students, interns, and residents respectively. There was no significant association among the three batches and the roles of a clinical teacher (p>0.05). Conversely, Females rated the roles of a clinical teacher significantly higher than males (p<0.05). CONCLUSIONS: As teachers are frequently perceived by students as role models in medical schools, great attention should be given to their roles. Teachers must be aware that their roles have an impact on students' professional development and performance.

Factors associated with students' perceptions of role modelling.

OBJECTIVES: To determine which professional and humanistic attributes demonstrated by teachers in the health disciplines caused them to be perceived by students as positive or negative role models. METHODS: Quantitative empirical data were gathered using a self-administered questionnaire by graduating students in medical, dentistry, and pharmacy schools at Kerman University of Medical Sciences. A total of 3 graduating cohorts, comprising about 220 students, were selected for this study. Surveys were distributed during January-March 2013. RESULTS: In total, 183 students participated in the study. Altogether, students considered 504 and 473 academic staff as positive and negative role models (PRMs and NRMs), respectively. Women were considered more negatively than men (mean scores: -12.13 vs. -11.6, p=0.04). While clinicians were considered more positively than basic scientists (mean scores: 12.65 vs. 10.67, p=0.001), dentists received higher positive scores than physicians or pharmacists (average scores: 13.27 vs. 12.99 and 9.82). There was a significant relationship between the personality of the students and the overall characteristics of their perceived role models (ß for PRMs=0.35, p<0.0001; and ß for NRMs= 0.20, p= 0.039). CONCLUSIONS: Humanistic and professional attributes were proposed as major components of personal traits in perceived role models. Demonstration of humanistic attributes by teachers was strongly correlated with the students' perception of the role models. It is suggested that the role of humanistic and professional attributes should be highlighted across medical disciplines in an effort to develop or improve role modelling by academic staff.

Machine learning models in breast cancer survival prediction.

BACKGROUND: Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. OBJECTIVE: The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. METHODS: We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. RESULTS: Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). CONCLUSIONS: This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of accuracy. Therefore, this model is recommended as a useful tool for breast cancer survival prediction as well as medical decision making.