Search results for: patient mortality

Authors: Qing Wu, Xuchun Ye, Kirsten Corazzini

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Objective: It is increasingly recognized that patients’ rational and meaningful engagement in healthcare could make important contributions to their health care and safety management. However, recent evidence indicated that patients' actual roles in healthcare didn’t match their desired roles, and many patients reported a less active role than desired, which suggested that patient engagement in healthcare may be influenced by various factors. This study aimed to analyze influencing factors on patient engagement and explore the influence mechanism, which will be expected to contribute to the strategy development of patient engagement in healthcare. Methods: On the basis of analyzing the literature and theory study, the research framework was developed. According to the research framework, a cross-sectional survey was employed using the behavior and willingness of patient engagement in healthcare questionnaire, Chinese version All Aspects of Health Literacy Scale, Facilitation of Patient Involvement Scale and Wake Forest Physician Trust Scale, and other influencing factor related scales. A convenience sample of 580 patients was recruited from 8 general hospitals in Shanghai, Jiangsu Province, and Zhejiang Province. Results: The results of the cross-sectional survey indicated that the mean score for the patient engagement behavior was (4.146 ± 0.496), and the mean score for the willingness was (4.387 ± 0.459). The level of patient engagement behavior was inferior to their willingness to be involved in healthcare (t = 14.928, P ＜ 0.01). The influencing mechanism model of patient engagement in healthcare was constructed by the path analysis. The path analysis revealed that patient attitude toward engagement, patients’ perception of facilitation of patient engagement and health literacy played direct prediction on the patients’ willingness of engagement, and standard estimated values of path coefficient were 0.341, 0.199, 0.291, respectively. Patients’ trust in physician and the willingness of engagement played direct prediction on the patient engagement, and standard estimated values of path coefficient were 0.211, 0.641, respectively. Patient attitude toward engagement, patients’ perception of facilitation and health literacy played indirect prediction on patient engagement, and standard estimated values of path coefficient were 0.219, 0.128, 0.187, respectively. Conclusions: Patients engagement behavior did not match their willingness to be involved in healthcare. The influencing mechanism model of patient engagement in healthcare was constructed. Patient attitude toward engagement, patients’ perception of facilitation of engagement and health literacy posed indirect positive influence on patient engagement through the patients’ willingness of engagement. Patients’ trust in physician and the willingness of engagement had direct positive influence on the patient engagement. Patient attitude toward engagement, patients’ perception of physician facilitation of engagement and health literacy were the factors influencing the patients’ willingness of engagement. The results of this study provided valuable evidence on guiding the development of strategies for promoting patient rational and meaningful engagement in healthcare.

Keywords: healthcare, patient engagement, influencing factor, the mechanism

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Authors: Rebecca Oakes

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In the New Zealand public health system, work has been taking place to use electronic systems to convey data from the ‘floor to the board’ that makes patient needs, and therefore nursing work, visible. For nurses, these developments in health information technology puts us in a very new and exciting position of being able to articulate the work of nursing through a language understood at all levels of an organisation, the language of acuity. Nurses increasingly have a considerable stake-hold in patient acuity data. Patient acuity systems, when used well, can assist greatly in demonstrating how much work is required, the type of work, and when it will be required. The New Zealand Safe Staffing Unit is supporting New Zealand nurses to create a culture of shared governance, where nursing data is informing policies, staffing methodologies and forecasting within their organisations. Assisting organisations to understand their acuity data, strengthening user confidence in using electronic patient acuity systems, and ensuring nursing and midwifery workload is accurately reflected is critical to the success of the safe staffing programme. Nurses and midwives have the capacity via an acuity tool to become key informers of organisational planning. Quality patient care, best use of health resources and a quality work environment are essential components of a safe, resilient and well resourced organisation. Nurses are the key informers of this information. In New Zealand a national level approach is paving the way for significant changes to the understanding and use of patient acuity and nursing workload information.

Keywords: nursing workload, patient acuity, safe staffing, New Zealand

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Authors: Öykü Barutçu, Mehmet Özgür Kuzdan

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Aim: Laparoscopy is very risky in patients undergoing, multiple open abdominal surgeries. The aim of this study, to define a safe method for the first trocar placement in children with a history of multiple open abdominal surgeries. Methods: Children who underwent laparoscopic surgery between March 2019 and April 2020 with a history of three or more open abdominal surgeries were included in the retrospective study. Patient information was obtained from the hospital automation system. Ultrasonography was used to determine the location of adhesions preoperatively. The first trocar was placed according to ultrasonography findings, using the Hasson technique to create an air pocket with finger dissection. The patient's preoperative, perioperative, and postoperative findings are reported. Results: A total of 10 patients were included in the study. The median number of operations before laparoscopy was three. The most common site for the first trocar entry was Palmer's point (40%). No mortality or morbidity was observed amongst any patients. The average number of adhesions detected by USG and observed on laparoscopy were significantly positively correlated. Conclusion: In children with a history of multiple abdominal surgeries, abdominal wall ultrasonography for visualization of adhesions and finger dissection for the formation of an air pocket appears to be a safe method for the first trocar insertion.

Keywords: abdominal wall, child, laparoscopy, ultrasonography

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Authors: S. M. P Manjula, Ishara Amarathunga, Aryan Nath Koura, Jaideepraj Rao

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Background: Laparoscopic D2 Gastrectomy for non metastatic advanced Gastric cancer (AGC) has become a controversial topic as there are confronting ideas from experts in the field. Lack of consensus are mainly due to non feasibility of the dissection and safety and efficacy. Method: Data from all D2 Gastrectomies performed (both Subtotal and Total Gastrectomies) in our unit from 2009 December to 2013 December were retrospectively analysed. Computor database was prospectively maintained. Pathological stage two A (iiA) and above considered advanced Gastric cancers, who underwent curative intent D2 Gastrectomy were included for analysis(n=46). Four patients excluded from the study as peritoneal fluid cytology came positive for cancer cells and one patient exempted as microscopic resection margin positive(R1) after curative resection. Thirty day morbidity and mortality, operative time, lymph nodes harvest and survival (disease free and overall) analyzed. Results: Complete curative resection achieved in 40 patients. Mean age of the study population was 62.2 (32-88) and male to female ratio was 23: 17. Thirty day mortality (1/40) and morbidity (6/40). Average operative time 203.7 minutes (185- 400) and average lymphnodes harvest was 40.5 (18-91). Disease free survival of the AGC in this study population was 16.75 months (1-49). Average hospital stay was 6.8 days (3-31). Conclusion: Laparoscopic dissection is effective feasible and safe in AGC.

Keywords: laparoscopy, advanced gastric cancer, safety, efficacy

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Authors: Mehravar Javid, Rohma Hassan

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Understanding a patient’s hallucinations requires a degree of cultural humility when these experiences are consistent with beliefs that are normative to the patient’s respective culture and religion, and in this exploratory case study, the treatment history of a 32-year-old female Iranian patient who sought psychoanalytic treatment in Iran is explored, who stated that she had been witnessing jinn since she was fifteen-years-old. She experienced considerable disempowerment and lack of support in her upbringing and curiously believes that the jinn provide her with comfort and power, yet simultaneously create a sense of fear and horror. When her analyst wonders about a possible link between the jinn and the patient’s self-object needs and what was denied for her in her youth, the patient becomes resistant to treatment, especially when the possibility of the jinn existing as hallucinations is raised. Throughout the course of therapy, the patient discusses her tumultuous marriage, her strained relationship with her family, and inner conflicts. She also begins to find solace in her relationship with her therapist, satisfying her self-object needs and enabling her to widen her self-awareness and wish for deeper connections with others. In understanding her needs and fears, the role of the jinn in her psychological landscape aims to be understood, with a larger discussion of how to work with patients experiencing supernatural phenomena and how the phenomena serve as an object, whether real or imaginary. The overall aim is to shed light on the intricate interplay between cultural and religious beliefs and psychological manifestations.

Keywords: cultural considerations, jinn, projective identification, self-object needs, transference

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Authors: Zainab Elazab, Azhar Aziz

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Background: Spontaneous Splenic artery pseudoaneurysm rupture is a rare condition which is potentially life threatening, if not detected and managed early. We report a case of abdominal pain with intraperitoneal free fluid, which turned out to be spontaneous rupture of a splenic artery pseudoaneurysm, and was treated with arterial embolization. Case presentation: A 28-year old, previously healthy male presented to the ED with a history of sudden onset upper abdominal pain and fainting attack. The patient denied any history of trauma or prior similar attacks. On examination, the patient had tachycardia and a low-normal BP (HR 110, BP 106/66) but his other vital signs were normal (Temp. 37.2, RR 18 and SpO2 100%). His abdomen was initially soft with mild tenderness in the upper region. Blood tests showed leukocytosis of 12.3 X109/L, Hb of 12.6 g/dl and lactic acid of 5.9 mmol/L. Ultrasound showed trace of free fluid in the perihepatic and perisplenic areas, and a splenic hypoechoic lesion. The patient remained stable; however, his abdomen became increasingly tender with guarding. We made a provisional diagnosis of a perforated viscus and the patient was started on IV fluids and IV antibiotics. An erect abdominal x-ray did not show any free air under the diaphragm so a CT abdomen was requested. Meanwhile, bedside ultrasound was repeated which showed increased amount of free fluid, suggesting intra-abdominal bleeding as the most probable etiology for the condition. His CT abdomen revealed a splenic injury with multiple lacerations, a focal intrasplenic enhancing area on venous phase scan (suggesting a pseudoaneurysm with associated splenic intraparenchymal, sub capsular and perisplenic hematomas). Free fluid in the subhepatic and intraperitoneal regions along the small bowel was also detected. Angiogram was done which confirmed a diagnosis of pseudoaneurysm of intrasplenic arterial branch, and angio-embolization was done to control the bleeding. The patient was later discharged in good condition with a surgery follow-up. Conclusion: Splenic artery pseudoaneurysm rupture is a rare cause of abdominal pain which should be considered in any case of abdominal pain with intraperitoneal bleeding. Early management is crucial as it carries a high mortality. Bedside ultrasound is a useful tool to help for early diagnosis of such cases.

Keywords: abdominal pain, pseudo aneurysm, rupture, splenic artery

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Authors: Truong H. Le, Ngoc M. To, Quang N. Tran, Luu T. Cao, Chi V. Le

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Introduction: In Vietnam, the current monitoring and treatment for ordinary diabetic patient mostly based on glucose monitoring with HbA1c test for every three months (recommended goal is HbA1c < 6.5%~7%). For diabetes in pregnant women or Gestational diabetes mellitus (GDM), glycemic control until the time of delivery is extremly important because it could reduce significantly medical implications for both the mother and the child. Besides, GDM requires continuos glucose monitoring at least every two weeks and therefore an alternative marker of glycemia for short-term control is considering a potential tool for the healthcare providers. There are published studies have indicated that the glycosylated serum protein is a better indicator than glycosylated hemoglobin in GDM monitoring. Based on the actual practice in Vietnam, this study was designed to evaluate the role of serum fructosamine as a monitoring tool in GDM treament and its correlations with fasting blood glucose (G0), 2-hour postprandial glucose (G2) and glycosylated hemoglobin (HbA1c). Methods: A cohort study on pregnant women diagnosed with GDM by the 75-gram oralglucose tolerance test was conducted at Endocrinology Department, Cho Ray hospital, Vietnam from June 2014 to March 2015. Cho Ray hospital is the final destination for GDM patient in the southern of Vietnam, the study population has many sources from other pronvinces and therefore researchers belive that this demographic characteristic can help to provide the study result as a reflection for the whole area. In this study, diabetic patients received a continuos glucose monitoring method which consists of bi-weekly on-site visit every 2 weeks with glycosylated serum protein test, fasting blood glucose test and 2-hour postprandial glucose test; HbA1c test for every 3 months; and nutritious consultance for daily diet program. The subjects still received routine treatment at the hospital, with tight follow-up from their healthcare providers. Researchers recorded bi-weekly health conditions, serum fructosamine level and delivery outcome from the pregnant women, using Stata 13 programme for the analysis. Results: A total of 500 pregnant women was enrolled and follow-up in this study. Serum fructosamine level was found to have a light correlation with G0 ( r=0.3458, p < 0.001) and HbA1c ( r=0.3544, p < 0.001), and moderately correlated with G2 ( r=0.4379, p < 0.001). During study timeline, the delivery outcome of 287 women were recorded with the average age of 38.5 ± 1.5 weeks, 9% of them have macrosomia, 2.8% have premature birth before week 35th and 9.8% have premature birth before week 37th; 64.8% of cesarean section and none of them have perinatal or neonatal mortality. The study provides a reference interval of serum fructosamine for GDM patient was 112.9 ± 20.7 μmol/dL. Conclusion: The present results suggests that serum fructosamine is as effective as HbA1c as a reflection of blood glucose control in GDM patient, with a positive result in delivery outcome (0% perinatal or neonatal mortality). The reference value of serum fructosamine measurement provided a potential monitoring utility in GDM treatment for hospitals in Vietnam. Healthcare providers in Cho Ray hospital is considering to conduct more studies to test this reference as a target value in their GDM treatment and monitoring.

Keywords: gestational diabetes mellitus, monitoring tool, serum fructosamine, Vietnam

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Authors: Jonathon Bailey, Neil Bressloff, Nick Curzen

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Transcatheter Aortic Valve Implantation (TAVI) devices are stent-like frames with prosthetic leaflets on the inside, which are percutaneously implanted. The device in a crimped state is fed through the arteries to the aortic root, where the device frame is opened through either self-expansion or balloon expansion, which reveals the prosthetic valve within. The frequency at which TAVI is being used to treat aortic stenosis is rapidly increasing. In time, TAVI is likely to become the favoured treatment over Surgical Valve Replacement (SVR). Mortality after TAVI has been associated with severe Paravalvular Aortic Regurgitation (PAR). PAR occurs when the frame of the TAVI device does not make an effective seal against the internal surface of the aortic root, allowing blood to flow backwards about the valve. PAR is common in patients and has been reported to some degree in as much as 76% of cases. Severe PAR (grade 3 or 4) has been reported in approximately 17% of TAVI patients resulting in post-procedural mortality increases from 6.7% to 16.5%. TAVI devices, like SVR devices, are circular in cross-section as the aortic root is often considered to be approximately circular in shape. In reality, however, the aortic root is often non-circular. The ascending aorta, aortic sino tubular junction, aortic annulus and left ventricular outflow tract have an average ellipticity ratio of 1.07, 1.09, 1.29, and 1.49 respectively. An elliptical aortic root does not severely affect SVR, as the leaflets are completely removed during the surgical procedure. However, an elliptical aortic root can inhibit the ability of the circular Balloon-Expandable (BE) TAVI devices to conform to the interior of the aortic root wall, which increases the risk of PAR. Self-Expanding (SE) TAVI devices are considered better at conforming to elliptical aortic roots, however the valve leaflets were not designed for elliptical function, furthermore the incidence of PAR is greater in SE devices than BE devices (19.8% vs. 12.2% respectively). If a patient’s aortic root is too severely elliptical, they will not be suitable for TAVI, narrowing the treatment options to SVR. It therefore follows that in order to increase the population who can undergo TAVI, and reduce the risk associated with TAVI, non-circular devices should be developed. Computational simulations were employed to further advance our understanding of non-circular TAVI devices. Radial stiffness of the TAVI devices in multiple directions, frame bending stiffness and resistance to balloon induced expansion are all computationally simulated. Finally, a simulation has been developed that demonstrates the expansion of TAVI devices into a non-circular patient specific aortic root model in order to assess the alterations in deployment dynamics, PAR and the stresses induced in the aortic root.

Keywords: tavi, tavr, fea, par, fem

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Authors: Njabulo Ncube, Elena Kulinskaya, Nicholas Steel, Dmitry Pshezhetskiy

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Life expectancy in the United Kingdom (UK) has been near constant since 2010, particularly for the individuals of 65 years and older. This trend has been also noted in several other countries. This slowdown in the increase of life expectancy was concurrent with the increase in the number of deaths caused by non-communicable diseases. Of particular concern is the world-wide exponential increase in the number of diabetes related deaths. Previous studies have reported increased mortality hazards among diabetics compared to non-diabetics, and on the differing effects of antidiabetic drugs on mortality hazards. This study aimed to estimate the all-cause mortality hazards and related life expectancies among type 2 diabetes (T2DM) patients in the UK using the time-variant Gompertz-Cox model with frailty. The study also aimed to understand the major causes of the change in life expectancy growth in the last decade. A total of 221 182 (30.8% T2DM, 57.6% Males) individuals aged 50 years and above, born between 1930 and 1960, inclusive, and diagnosed between 2000 and 2016, were selected from The Health Improvement Network (THIN) database of the UK primary care data and followed up to 31 December 2016. About 13.4% of participants died during the follow-up period. The overall all-cause mortality hazard ratio of T2DM compared to non-diabetic controls was 1.467 (1.381-1.558) and 1.38 (1.307-1.457) when diagnosed between 50 to 59 years and 60 to 74 years, respectively. The estimated life expectancies among T2DM individuals without further comorbidities diagnosed at the age of 60 years were 2.43 (1930-1939 birth cohort), 2.53 (1940-1949 birth cohort) and 3.28 (1950-1960 birth cohort) years less than those of non-diabetic controls. However, the 1950-1960 birth cohort had a steeper hazard function compared to the 1940-1949 birth cohort for both T2DM and non-diabetic individuals. In conclusion, mortality hazards for people with T2DM continue to be higher than for non-diabetics. The steeper mortality hazard slope for the 1950-1960 birth cohort might indicate the sub-population contributing to a slowdown in the growth of the life expectancy.

Keywords: T2DM, Gompetz-Cox model with frailty, all-cause mortality, life expectancy

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Authors: A. Jatau, Q. Majeed, H. M. Bandiya

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The efficacy of five local spices, namely; Hot pepper (Capsicum annum L.), Black pepper (Piper guinese Schum and Thonn), Sweet basil (Occimum canum Sim), African nut-meg (Monodora myristica Dunal), and Ginger (Zingiber officianale Ross) with conventional insecticide against the D. maculatus was studied under ambient laboratory conditions. The plants were pulverized into powders and applied at the rate of 1.0, 2.0 and 3.0g per 25g of disinfected dried fish. The same amount of fish (25g) was treated with 5ml of 1.0, 2.0 and 3.0 percent solution of conventional insecticide (dichlorvos) and air dried for 2hrs. Ten newly hatched 1st instar larvae (24hrs old) were introduced into each powdered smoked fish in separate beakers. Untreated control was also set up. Observation on the mortality and development were recorded daily until the larvae pupated. Each of the treated smoked fish showed significant (p<0.05) effect on the larval mortality and development when compared with the control. The Piper guinense was as efficacious as dichlorvos in killing all the larvae (100%) at all concentrations before pupation. Ocimum Canunm gave the second best results (50.00, 63.33 and 100%), while the other three spices resulted in less than 50% mortalities at all rate of application. The spice powders were also observed to have extended the larval developmental period. Thus, the spices tested can be recommended for the control of D. maculatus.

Keywords: development, dermestes maculatus, insecticide, local spices, mortality

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Authors: Igor A. Bessmertny, Bidru C. Enkomaryam

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Active involving patients and communities in health decisions can improve both people’s health and the healthcare system. Adopting artificial intelligence can lead to more accurate and complete patient record management. This review aims to identify the current state of researches conducted using artificial intelligence techniques to improve patient engagement and wellbeing, medical domains used in patient engagement context, and lastly, to assess opportunities and challenges for patient engagement in the wellness process. A search of peer-reviewed publications, reviews, conceptual analyses, white papers, author’s manuscripts and theses was undertaken. English language literature published in 2013– 2022 period and publications, report and guidelines of World Health Organization (WHO) were also assessed. About 281 papers were retrieved. Duplicate papers in the databases were removed. After application of the inclusion and exclusion criteria, 41 papers were included to the analysis. Patient counseling in preventing adverse drug events, in doctor-patient risk communication, surgical, drug development, mental healthcare, hypertension & diabetes, metabolic syndrome and non-communicable chronic diseases are implementation areas in healthcare where patient engagement can be implemented using artificial intelligence, particularly machine learning and deep learning techniques and tools. The five groups of factors that potentially affecting patient engagement in safety are related to: patient, health conditions, health care professionals, tasks and health care setting. Active involvement of patients and families can help accelerate the implementation of healthcare safety initiatives. In sub-Saharan Africa, using digital technologies like artificial intelligence in patient engagement context is low due to poor level of technological development and deployment. The opportunities and challenges available to implement patient engagement strategies vary greatly from country to country and from region to region. Thus, further investigation will be focused on methods and tools using the potential of artificial intelligence to support more simplified care that might be improve communication with patients and train health care professionals.

Keywords: artificial intelligence, patient engagement, machine learning, patient involvement

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Authors: Najade Sheriff, Malaz Elsaddig, Kevin Jones

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Background: Death in the first month of life accounts for an increasing proportion of under-five mortality. Advancement to reduce this number is being made across the globe; however, progress is slowest in sub-Saharan Africa. Objectives: The study aims to identify differences between neonatal deaths of inpatient babies born in a hospital facility in rural Uganda to those of neonates admitted from the community and to explore whether they can be used to risk stratify neonatal admissions. Results: A retrospective chart review was conducted on records for neonates admitted to the Special Care Baby Unit (SCBU) Kitovu Hospital from 1st July 2016 to 21st July 2017. A total of 442 babies were admitted and the overall neonatal mortality was 24.8% (40% inpatient, 37% community, 23% hospital referrals). 40% of deaths occurred within 24 hours of admission and the majority were male (63%). 43% of babies were hypothermic upon admission, a significantly greater proportion of which were inpatient babies born in labour ward (P=0.0025). Intrapartum related death accounted for ½ of all inpatient babies whereas complications of prematurity were the predominant cause of death in the community group (37%). Severe infection does not seem like a significant factor of mortality for inpatients (2%) as it does for community admissions (29%). Furthermore, with 52.5% of community admissions weighing < 1500g, very low birth weight (VLBW) may be a significant risk factor for community neonatal death. Conclusion: The neonatal mortality rate in this study is high, and the leading causes of death are all largely preventable. A high rate of inpatient birth asphyxiation indicates the need for good quality facility-based perinatal care as well as a greater focus on the management of hypothermia, such as Kangaroo care. Moreover, a reduction in preterm deliveries is necessary to reduce associated comorbidities, and monitoring for signs of infection is especially important for community admissions.

Keywords: community, mortality, newborn, Uganda

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Authors: P. Aarumugam, N. Krishnamoorthy, K. Gunasekaran

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The mosquitoes with loss of minimum three legs especially the hind legs have the negative impact on the survival hood of mosquitoes. Three days old unfed adult female laboratory strain was selected in each generation against sublethal dosages (0.004%, 0.005%, 0.007% and 0.01%) of deltamethrin upto 40 generations. Impregnated papers with acetone were used for control. Every fourth generation, survived mosquitoes were observed for functional mortality. Hind legs lost were significantly (P< 0.05) higher in treated than the controls up to generation 24, thereafter no significant lost. In contrary, no significant forelegs lost among exposed mosquitoes. Middle legs lost were also not significant in the exposed mosquitoes except first generation (F1). The field strain (Chennai) did not show any significant loss of legs (fore or mid or hind) compared to the control. The selection pressure on mosquito population influences strong natural selection to develop various adaptive mechanisms.

Keywords: Anopheles stephensi, deltamethrin, functional mortality, synthetic pyrethroids

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Authors: Anita Puspawati

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A failure in obtaining informed consent from patient occurs because there is not effective communication skill in doctors. Therefore, the language is very important in communication between doctor and patient. This study uses descriptive analysis method, that is a method used mainly in researching the status of a group of people, an object, a condition, a system of thought or a class of events in the present. The result of this study indicates that the communicative language between doctors and patients will increase the trust of patients to their doctors and accordingşy, patients will provide the informed consent voluntarily.

Keywords: communicative, language, doctor, patient

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Authors: Haoming Ma, Guo Yu, Peiru Zhou

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Background: Previous studies show that dysglycemia, mostly hyperglycemia, hypoglycemia and glycemic variability(GV), are associated with excess mortality in critically ill patients, especially those without diabetes. Glycemic variability is an increasingly important measure of glucose control in the intensive care unit (ICU) due to this association. However, there is limited data pertaining to the relationship between different clinical factors and glycemic variability and clinical outcomes categorized by their DM status. This retrospective study of 958 intensive care unit(ICU) patients was conducted to investigate the relationship between GV and outcome in critically ill patients and further to determine the significant factors that contribute to the glycemic variability. Aim: We hypothesize that the factors contributing to mortality and the glycemic variability are different from critically ill patients with or without diabetes. And the primary aim of this study was to determine which dysglycemia (hyperglycemia\hypoglycemia\glycemic variability) is independently associated with an increase in mortality among critically ill patients in different groups (DM/Non-DM). Secondary objectives were to further investigate any factors affecting the glycemic variability in two groups. Method: A total of 958 diabetic and non-diabetic patients with severe diseases in the ICU were selected for this retrospective analysis. The glycemic variability was defined as the coefficient of variation (CV) of blood glucose. The main outcome was death during hospitalization. The secondary outcome was GV. The logistic regression model was used to identify factors associated with mortality. The relationships between GV and other variables were investigated using linear regression analysis. Results: Information on age, APACHE II score, GV, gender, in-ICU treatment and nutrition was available for 958 subjects. Predictors remaining in the final logistic regression model for mortality were significantly different in DM/Non-DM groups. Glycemic variability was associated with an increase in mortality in both DM(odds ratio 1.05; 95%CI:1.03-1.08,p＜0.001) or Non-DM group(odds ratio 1.07; 95%CI:1.03-1.11,p=0.002). For critically ill patients without diabetes, factors associated with glycemic variability included APACHE II score(regression coefficient, 95%CI:0.29,0.22-0.36,p＜0.001), Mean BG(0.73,0.46-1.01,p＜0.001), total parenteral nutrition(2.87,1.57-4.17,p＜0.001), serum albumin(-0.18,-0.271 to -0.082,p＜0.001), insulin treatment(2.18,0.81-3.55,p=0.002) and duration of ventilation(0.006,0.002-1.010,p=0.003).However, for diabetes patients, APACHE II score(0.203,0.096-0.310,p＜0.001), mean BG(0.503,0.138-0.869,p=0.007) and duration of diabetes(0.167,0.033-0.301,p=0.015) remained as independent risk factors of GV. Conclusion: We found that the relation between dysglycemia and mortality is different in the diabetes and non-diabetes groups. And we confirm that GV was associated with excess mortality in DM or Non-DM patients. Furthermore, APACHE II score, Mean BG, total parenteral nutrition, serum albumin, insulin treatment and duration of ventilation were significantly associated with an increase in GV in Non-DM patients. While APACHE II score, mean BG and duration of diabetes (years) remained as independent risk factors of increased GV in DM patients. These findings provide important context for further prospective trials investigating the effect of different clinical factors in critically ill patients with or without diabetes.

Keywords: diabetes, glycemic variability, predictors, severe disease

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Authors: Sarah Aldhalaan, Tanzila Saba

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Healthcare sectors are increasing rapidly to fulfill patient’s needs across the world. A patient identification is considered as the main aspect for a patient to be served in healthcare institutes. Nowadays, people are presenting their insurance card along with their identification card in order to get the needed treatment in hospitals however, this process lack security preferences. The aim of this research paper is to reveal a solution to introduce and use biometrics in healthcare hospitals. The findings show that the people know biometrics since they are interacting with them through different channels and that the need for biometrics techniques to identify patients is essential. Also, the survey relevant questions are used to analyze and add insights on what is are the suitable biometrics to be used in such cases. Moreover, results are presented to exhibit the effectiveness of the used methodology and in analyzing usage of biometrics in hospitals in an enhancing way. Finally, an interesting conclusion of overall work is presented at the end of paper.

Keywords: biometrics, healthcare, fingerprint, Saudi Arabia

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Authors: Gunjan Srivastava, Shamila Kalia

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Dalbergia sissoo Roxb., (Family- Leguminosae; Subfamily- Papilionoideae), is an economically and ecologically important tree species having medicinal value. Of the rich complex of insect fauna, ten have been recognized as potential pests of nurseries and plantations. Present study was conducted to explore an effective ecofriendly control of Dichomeris eridantis Meyrick, an important defoliator pest of D. sissoo. Health and environmental concerns demanded devising a bio-intensive pest management strategy and employing ecofriendly measures. In the present laboratory bioassay two entomopathogenic fungi Acremonium perscinum and Beauveria bassiana were tested and compared for evaluating the efficacy of their seven different concentrations (besides control) against the 3rd, 4th and 5th instar larvae of D. eridantis, on the basis of mean percent mortality data recorded and tabulated for seven days after treatment application. Analysis showed that both treatments vary significantly among themselves. Also, variations amongst instars and duration with respect to their mortality were highly significant (p < .001). All their interactions were found to vary significantly. B. bassiana at 0.25x107 spores / ml spore concentration caused maximum mean percent mortality (62.38%) followed by mean percent mortality at its 0.25x106 spores / ml concentration (56.67%). Mean percent mortality at maximum spore concentration (0.054x107 spores / ml) and next highest spore concentration (0.054 x106 spores / ml) due to A. perscinum treatment were far less effective (mean percent mortality of 45.40% and 31.29%, respectively). At 168 hours mean percent mortality of larval instars due to both fungal treatment applications reached its maximum (52.99%) whereas, at 24 hours mean percent mortality remained least (5.70%). In both cases, treatments were most effective against 3rd instar larvae and least effective against 5th instar larvae. A comparative acccount of efficacy of B. bassiana and A. perscinum on the 3rd, 4th and 5th instar larvae of D. eridantis on 5th, 6th and 7th post treatment observation days after their application, on the basis of their median lethal concentrations (LC50) proved B. bassiana to be more potential microbial pathogen of the two fungal microbes, for all the three instars (3rd, 4th and 5th) of D. eridantis, on all the three days (5th, 6th and 7th post observation days after application of both treatments). Percent mortality of D. eridantis increased in a dose dependent manner. Koch’s Postulates tested positive, thus confirming the pathogenicity of B. bassiana against the larval instars of D. eridantis. LC90 values of 0.280x1011 spores/ml, 0.301x108 spores/ml and 0.262x108 spores/ml concentrations of B. bassiana were standardized which can effectively cause mortality of all the larval instars of D. eridantis in the field after 5th, 6th and 7th day of their application, respectively. Therefore, these concentrations can be safely used in nurseries as well as plantations of D. sissoo for effective control of D. eridantis larvae.

Keywords: Acremonium perscinum, Beauveria bassiana, Dalbergia sissoo, Dichomeris eridantis

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Authors: Hichem Sassi

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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

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Authors: Rafael Ricieri, Rogerio Barros

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Objective: This study is to report a case of massive necrotizing enterocolitis in a six-month-old patient, requiring ileostomy and protective jejunostomy as a damage control measure in the first exploratory laparotomy surgery in massive enterocolitis without a previous diagnosis. Methods: This study is a case report of success in making and closing a protective jejunostomy. However, the low number of publications on this staged and risky measure of surgical resolution encouraged the team to study the indication and especially the correct time for closing the patient's protective jejunostomy. The main study instrument will be the six-month-old patient's medical record. Results: Based on the observation of the case described, it was observed that the time for the closure of the described procedure (protective jejunostomy) varies according to the level of compromise of the health status of your patient and of an individual of each person. Early closure, or failure to close, can lead to a favorable problem for the patient since several problems can result from this closure, such as new intestinal perforations, hydroelectrolyte disturbances. Despite the risk of new perforations, we suggest closing the protective jejunostomy around the 14th day of the procedure, thus keeping the patient on broad-spectrum antibiotic therapy and absolute fasting, thus reducing the chances of new intestinal perforations. Associated with the closure of the jejunostomy, a gastric tube for decompression is necessary, and care in an intensive care unit and electrolyte replacement is necessary to maintain the stability of the case.

Keywords: jejunostomy, ileostomy, enterocolitis, pediatric surgery, gastric surgery

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Authors: Hakan Duger, Alparslan Ersoy, Canan Ersoy

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Diabetes mellitus is the most common etiology of end-stage renal disease (ESRD). Also, diabetic nephropathy is the etiology of ESRD in approximately 23% of kidney transplant recipients. A successful kidney transplant improves the quality of life and reduces the mortality risk for most patients. However, patients require close follow-up after transplantation due to medical complications. Diabetes mellitus can affect patient morbidity and mortality due to possible effects of immunosuppressive therapy on glucose metabolism. We compared the frequency of medical complications and the outcomes in diabetic and non-diabetic kidney transplant recipients. Materials and Methods: This retrospective study conducted in 498 patients who underwent kidney transplant surgery at our center in 10-year periods. The patients were divided into two groups: diabetics (46 ± 10 year, 26 males, 16 females) and non-diabetics (39 ± 12 year, 259 males, 197 females). The medical complications, graft functions, causes of graft loss and death were obtained from medical records. Results: There was no significant difference between recipient age, duration of dialysis, body mass index, gender, donor type, donor age, dialysis type, histories of HBV, HCV and coronary artery disease between two groups. The history of hypertension in diabetics was higher (69% vs. 36%, p < 0.001). The ratios of hypertension (50.1% vs. 57.1%), pneumonia (21.9% vs. 20%), urinary infection (16.9% vs. 20%), transaminase elevation (11.5% vs. 20%), hyperpotasemia (14.7% vs. 17.1%), hyponatremia (9.7% vs. 20%), hypotension (7.1% vs. 7.9%), hypocalcemia (1.4% vs. 0%), thrombocytopenia (8.6% vs. 8.6%), hypoglycemia (0.7% vs. 0%) and neutropenia (1.8% vs. 0%) were comparable in non-diabetic and diabetic groups, respectively. The frequency of hyperglycaemia in diabetics was higher (8.6% vs. 54.3%, p < 0.001). After transplantation, primary non-function (3.4% vs. 2.6%), delayed graft function (25.1% vs. 34.2%) and acute rejection (7.3% vs. 10.5%) ratios of in non-diabetic and diabetic groups were similar, respectively. Hospitalization durations in non-diabetics and diabetics were 22.5 ± 17.5 and 18.7 ± 13 day (p=0.094). Mean serum creatinine levels in non-diabetics and diabetics were 1.54 ± 0.74 and 1.52 ± 0.62 mg/dL at 6th month. Forty patients had graft loss. The ratios of graft loss and death in non-diabetic and diabetic groups were 8.2% vs. 7.1% and 7.1% vs. 2.6% (p > 0.05). There was no significant relationship between graft and patient survivals with the development of medical complication. Conclusion: As a result, medical complications are common in the early period. Hyperglycaemia was frequently seen following transplantation due to the effects of immunosuppressant regimens. However, the frequency of other medical complications in diabetic patients did not differ from non-diabetic one. The most important cause of death is still infections. The development of medical complications during the first 6 months did not significantly affect transplant outcomes.

Keywords: kidney transplantation, diabetes mellitus, complication, graft function

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Authors: S. Madhusudhan, G. V. Vaniprabha

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Worldwide statistics have shown that smoking contributes significantly to mortality, with nicotine, being more addictive. Smoking causes more than 7,00,000 deaths/year in India. Compared to the general population, the prevalence of smoking is found to be much higher among people with psychotic disorders and, more so in schizophrenia. Schizophrenic patients who smoke tend to have higher frequency of heavy smoking, with rates ranging from 60% to as high as 80%. Hence, smokers with psychiatric disorders suffer higher rates of morbidity and mortality secondary to smoking related illnesses.

Keywords: brief intervention, nicotine dependence, schizophrenia

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Authors: Jitka Rychtarikova

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Regional differences in mortality in the Czech Republic (CR) may be moderate from a broader European perspective, but important discrepancies in life expectancy can be found between smaller territorial units. In this study territorial units are based on Administrative Districts of Municipalities with Extended Powers (MEP). This definition came into force January 1, 2003. There are 205 units and the city of Prague. MEP represents the smallest unit for which mortality patterns based on life tables can be investigated and the Czech Statistical Office has been calculating such life tables (every five-years) since 2004. MEP life tables from 2009-2013 for males and females allowed the investigation of three main life cycles with the use of temporary life expectancies between the exact ages of 0 and 35; 35 and 65; and the life expectancy at exact age 65. The results showed regional survival inequalities primarily in adult and older ages. Consequently, only mortality indicators for adult and elderly population were related to census 2011 unlinked data for the same age groups. The most relevant socio-economic factors taken from the census are: having a partner, educational level and unemployment rate. The unemployment rate was measured for adults aged 35-64 completed years. Exploratory spatial data analysis methods were used to detect regional patterns in spatially contiguous units of MEP. The presence of spatial non-stationarity (spatial autocorrelation) of mortality levels for male and female adults (35-64), and elderly males and females (65+) was tested using global Moran’s I. Spatial autocorrelation of mortality patterns was mapped using local Moran’s I with the intention to depict clusters of low or high mortality and spatial outliers for two age groups (35-64 and 65+). The highest Moran’s I was observed for male temporary life expectancy between exact ages 35 and 65 (0.52) and the lowest was among women with life expectancy of 65 (0.26). Generally, men showed stronger spatial autocorrelation compared to women. The relationship between mortality indicators such as life expectancies and socio-economic factors like the percentage of males/females having a partner; percentage of males/females with at least higher secondary education; and percentage of unemployed males/females from economically active population aged 35-64 years, was evaluated using multiple regression (OLS). The results were then compared to outputs from geographically weighted regression (GWR). In the Czech Republic, there are two broader territories North-West Bohemia (NWB) and North Moravia (NM), in which excess mortality is well established. Results of the t-test of spatial regression showed that for males aged 30-64 the association between mortality and unemployment (when adjusted for education and partnership) was stronger in NM compared to NWB, while educational level impacted the length of survival more in NWB. Geographic variation and relationships in mortality of the CR MEP will also be tested using the spatial Durbin approach. The calculations were conducted by means of ArcGIS 10.6 and SAS 9.4.

Keywords: Czech Republic, mortality, municipality, socio-economic factors, spatial analysis

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Authors: Tanushree Jaitly, Shailendra Gupta, Leila Taher, Gerold Schuler, Julio Vera

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Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further.

Keywords: cancer immunotherapy, epitope prediction, NGS data, personalized medicine

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Authors: Esra Bora, Alper Omeroglu, Zeynep Pelin Polat, Oguzhan Kara, Fatih Akdogan, Sema Ucak Basat

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Hyponatremia is one of the most encountered electrolyte imbalance among all medical fields. It has a wide range of symptoms as well as complications from fatigue to loss of consciousness. Although a lot of factors can cause low sodium levels in serum, combining specific medications can lead to severe hyponatremia in a rapid onset which can cause high mortality and morbidity. The objective of this case report was to underline that prescribing specific medications disregarding their side effects can cause this common electrolyte imbalance but in a more severe manner. In this case report, we present a 46-year-old male patient with a serum sodium level of 104 mEq/L who consumed hydrochlorothiazide for hypertension and was under treatment with selective serotonin reuptake inhibitors (SSRIs) for major depression. The patient had tonic-clonic seizures at the second hour of the treatment and intubation was needed due to loss of consciousness and hypoxia. After proper replacement of sodium with hypertonic solutions in intensive care unit for nine days, extubation indicated. Even in healthy young males, hyponatremia due to two separately prescribed medications can lead life-threatening hyponatremia. Physicians should be aware of the side effects of diuretics, especially hydrochlorothiazides and SSRIs and their combinations.

Keywords: diuretics, hydrochlorothiazide, hyponatremia, SSRI

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Authors: G. Yoga Sairam Teja, K. Harsha Vardhan, A. Vinay Kumar, K. Nithish Kumar, Ch. Shanthi Priyag

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The emergence of the Internet of Things (IoT) has facilitated better device control and monitoring in the modern world. The constant monitoring of a patient would be drastically altered by the usage of IoT in healthcare. As we've seen in the case of the COVID-19 pandemic, it's important to keep oneself untouched while continuously checking on the patient's heart rate and temperature. Additionally, patients with paralysis should be closely watched, especially if they are elderly and in need of special care. Our "IoT BASED PATIENT HEALTH MONITORING SYSTEM" project uses IoT to track patient health conditions in an effort to address these issues. In this project, the main board is an 8051 microcontroller that connects a number of sensors, including a heart rate sensor, a temperature sensor (LM-35), and a saline water measuring circuit. These sensors are connected via an ESP832 (WiFi) module, which enables the sending of recorded data directly to the cloud so that the patient's health status can be regularly monitored. An LCD is used to monitor the data in offline mode, and a buzzer will sound if any variation from the regular readings occurs. The data in the cloud may be viewed as a graph, making it simple for a user to spot any unusual conditions.

Keywords: IoT, ESP8266, 8051 microcontrollers, sensors

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Authors: Gagandeep Singh Grover, Vini Mahajan, Bhagmal, Priti Thaware, Jaspreet Takkar

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Dengue is a mosquito-borne viral disease endemic in many countries in the tropics and sub-tropics. The state of Punjab in India shows cyclical and seasonal variation in dengue cases. The Case Fatality Rate of Dengue has ranged from 0.6 to 1.0 in the past years. The department has initiated a review of the cases that have died due to dengue in order to know the exact cause of the death in a case of dengue. The study has been undertaken to know the other associated co-morbidities and factors causing death in a case of dengue. The study used the predesigned proforma on which the records (medical and Lab) were recorded and reviewed by the expert committee of the doctors. This study has revealed that cases of dengue having co-morbidities have a longer stay in the hospital. Fluid overload and co-morbidities have been found as major factors leading to death, however, in a confirmed case of dengue hepatorenal shutdown was found to be a major cause of mortality. The data obtained will help in sensitizing the treating physicians in order to decrease the mortality due to dengue in future.

Keywords: dengue, death, morbidities, DHF, DSS

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Authors: Nelson Rotimi Osungbemiro, Sanni Rafiu Olugbenga, Abayomi Olufemi Olajuyigbe

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Ninety Fingerlings of Clarias gariepinus were exposed to the pathogenic Flavobacterium columnare a Gram Negative bacteria responsible for high mortality in fish pond raised young fish (fries and fingerlings) of Clarias sp. in Southwestern Nigeria. After feeding with 40% crude protein pelletized fish feed for 5 days, the fishes were divided into two groups, one group was treated with extracts from Calendula officinalis flowers, while the second group was not treated (control). The results indicated that, at day 5, colony formation had been manifesting and at day 7, skin lesion occurred and at the 8th day, first mortality of fish occurred, and this continued steadily on the 9th-12th day when all the fishes were dead. Whereas, in the group that was treated with Calendula sp., no single mortality was recorded. This research shows that plant extract from Calendula flowers is an effective antimicrobial agent against the virulent pathogenic Flavobacterium columnare disease.

Keywords: antimicrobial, Flavobacterium columnare, Clarias gariepinus, fish

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Authors: Grace Omowunmi Soyebi

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Data Mining is the extraction of information from a large database which helps in predicting a trend or behavior, thereby helping management make knowledge-driven decisions. One principal problem of most hospitals in rural areas is making use of the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method, which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to easily retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: data mining, medical record system, systems programming, computing

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Authors: Hacer Kobya Bulut, Kıymet Yeşilçiçek Çalık, Birsel Canan Demirbağ, Hacer Erdöl, Songül Aktaş

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Introduction: As an expression of an emotion which always exists in life, crying is regarded as one of the problematic behaviors of patients by nurses. Towards such patients, nurses may exhibit emotional and behavioral reactions such as feeling helpless, anger, indifferent, defense, and opposition. However crying either meets a need, reduces the tension to cope with problems or helps patient to gain strength. Therefore, nurses must accept that crying is a normal mechanism that reduces emotional tension and should approach a crying patient accordingly. Objective: This study was carried out to evaluate the communicational behaviors of the nurses towards ‘crying patient’. Methods: This descriptive study was conducted with the nurses working at a university hospital in a city in the Eastern Black Sea in June-September 2015. The entire universe was tried to be reached without sampling. 90% of the population was reached and the study was completed with 309 nurses who volunteered to participate in the study. Data were collected through a questionnaire which was prepared reviewing the literature by researchers. Data were evaluated in SPSS analysis program using percentages, numbers and chi-square test with the 95% confidence interval and p <0.05significance level. Findings: The findings showed that the average age of nurses was 31.52 ± 7.96, work experience was 10:09 ± 7.69 and only 22.7% had training about ‘approach to crying patient’ during their education. 97.1% of the nurses often faced with crying patients in their professional lives, 62.8% stated that they faced crying women patients. When they see crying patients, 84.8% of the nurses ‘do not want the patient to cry’, 80.9% wonder ‘why they are crying’, % 79.6 ‘feel uneasiness’,% 79.3 ‘feel sorry’ and 41.4% ‘ feel helpless’. The question ‘Why do you think the patient is crying?’ was answered by 93.5% nurses as ‘they are suffering’, by 86.1% ‘they are helpless’, 80.9% ‘they are sad’, 79.6% ‘they need help’, 54.4% ‘because they feel inadequate,’ and 44.7% ‘they fail to control their crying behavior. ‘How do you approach to your patient when she/he is crying?’ question was answered by 82.5% of nurses as ‘I would console’, 77.3% as ‘I would ask the reason’, 63.1% as ‘I would try to stop her from crying’ all of which are actually inappropriate nursing approaches. However, 92.2% of the nurses stated that ‘I do not judge the crying patient’, ‘87.1% said ‘I allocate time to crying patients’ and 85.8% said ‘ I ask patient whether they want to cry alone’. The study showed that educational background and work experience of the nurses affected the appropriate approach to crying patients (P <0.05). Conclusion: As a result of the study, it was found out that nurses do not want patients to cry, so they exhibit inappropriate approach such as consoling the patients and they have difficulty in approaching crying patients.

Keywords: approach to patient, communication, crying patient, nurse, Turkey

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

Procedia PDF Downloads 105