scholarly journals An Effort to Increase the Independence of Pregnant Women in Detecting High Risk and Complications of Pregnancy

2020 ◽  
Vol 8 ◽  
Author(s):  
Ika Mardiyanti ◽  
Yasi Anggasari
Keyword(s):  
High Risk ◽  
Pregnant Women ◽  
Family System ◽  
Health Care Systems ◽  
Health Conditions ◽  
Self Awareness ◽  
Service Activity ◽  
Care Systems ◽  
Birth Planning ◽  
Developmental Conditions

Health problems for pregnant women, both physically and psychologically, have an impact on the quality of life of the mother and the baby she is carrying. Women with high-risk pregnancies need to prepare themselves with more attention to their health conditions in facing pregnancy. Several factors that influence the independence of pregnant women in early detection of high risk pregnancies include age, developmental conditions, health conditions, cultural orientation, health care systems, family system factors or family support, lifestyle, environmental factors and available resources. The output target to be achieved in the implementation of this community service activity is to increase the understanding and skills of pregnant women about high-risk pregnancies and to be published in national journals. Efforts to increase the independence of pregnant women in detecting high risks and complications of pregnancy through the use of the  health of both mother and childbook, Skor Pudji Rochyati and birth planning and complication prevention program stickers are a form of self-awareness for pregnant women and supported by social support by their families, it is hoped that pregnant women will be fully aware of the signs and dangers that occur. on himself and checked himself into a health facility and wanted to be referred to a higher level of service precisely and quickly.

scholarly journals Testing the Mig-HealthCare Algorithm in Greece

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
E Riza ◽  
P Karnaki ◽  
D Zota ◽  
A Linos
Keyword(s):  
Health Care ◽  
Early Stage ◽  
Health Care Systems ◽  
Health Conditions ◽  
Health Issues ◽  
Host Countries ◽  
Local Hospital ◽  
Raising Awareness ◽  
Significant Burden ◽  
Care Systems

Abstract The Mig-HealthCare Algorithm is a tool, comprising a set of questions developed with the aim to (a) guide the user on how to access all the categories and tools that are available through the Roadmap & Toolbox (b) help the user identify the health issues of importance when providing care to a specific migrant/refugee. At the end of a series of questions, a brief report summarizing the main outcomes is generated. The algorithm was tested in Greece in two mainland reception centres and a local hospital in an area serving migrants/refugees. Results discuss the usefulness of the algorithm for improving the delivery of appropriate health services to migrants/refugees and its importance in raising awareness about the health conditions which are crucial for migrants/refugees and are expected to pose a significant burden on the health care systems of host countries unless dealt with adequately at an early stage.

scholarly journals COVID-19: Rethinking the Lockdown Groupthink

2021 ◽  
Vol 9 ◽  
Author(s):  
Ari R. Joffe
Keyword(s):  
Public Health ◽  
High Risk ◽  
Cost Benefit Analysis ◽  
Health Care Systems ◽  
Herd Immunity ◽  
Cost Benefit ◽  
Risk Groups ◽  
School Closures ◽  
Trade Offs ◽  
Care Systems

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused the Coronavirus Disease 2019 (COVID-19) worldwide pandemic in 2020. In response, most countries in the world implemented lockdowns, restricting their population's movements, work, education, gatherings, and general activities in attempt to “flatten the curve” of COVID-19 cases. The public health goal of lockdowns was to save the population from COVID-19 cases and deaths, and to prevent overwhelming health care systems with COVID-19 patients. In this narrative review I explain why I changed my mind about supporting lockdowns. The initial modeling predictions induced fear and crowd-effects (i.e., groupthink). Over time, important information emerged relevant to the modeling, including the lower infection fatality rate (median 0.23%), clarification of high-risk groups (specifically, those 70 years of age and older), lower herd immunity thresholds (likely 20–40% population immunity), and the difficult exit strategies. In addition, information emerged on significant collateral damage due to the response to the pandemic, adversely affecting many millions of people with poverty, food insecurity, loneliness, unemployment, school closures, and interrupted healthcare. Raw numbers of COVID-19 cases and deaths were difficult to interpret, and may be tempered by information placing the number of COVID-19 deaths in proper context and perspective relative to background rates. Considering this information, a cost-benefit analysis of the response to COVID-19 finds that lockdowns are far more harmful to public health (at least 5–10 times so in terms of wellbeing years) than COVID-19 can be. Controversies and objections about the main points made are considered and addressed. Progress in the response to COVID-19 depends on considering the trade-offs discussed here that determine the wellbeing of populations. I close with some suggestions for moving forward, including focused protection of those truly at high risk, opening of schools, and building back better with a economy.

FOLFOX4/XELOX in stage II–III colon cancer: Efficacy results of the Italian three or six colon adjuvant (TOSCA) trial.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 3501-3501 ◽  
Author(s):  
Alberto F. Sobrero ◽  
Sara Lonardi ◽  
Gerardo Rosati ◽  
Maria Di Bartolomeo ◽  
Monica Ronzoni ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Health Care Systems ◽  
Standard Of Care ◽  
Stage Ii ◽  
Phase Iii ◽  
Stage Iii ◽  
Absolute Difference ◽  
Open Label ◽  
Care Systems

3501 Background: Six months of oxaliplatin-based treatment has been the standard of care as adjuvant therapy for stage III colon cancer and an accepted option for high-risk stage II. Given the cumulative neurotoxicity associated to oxaliplatin, a shorter duration of therapy, if equally efficacious, would be advantageous for patients and health-care systems. Methods: TOSCA was an open-label, phase III, multicenter, non-inferiority trial randomizing patients with high-risk stage II or stage III radically resected colon cancer to receive 3 months or 6 months of FOLFOX4/XELOX. Primary end-point was relapse-free survival. Results: From June 2007 to March 2013, 3759 patients were accrued from 130 Italian sites, 64% receiving FOLFOX4 and 36% XELOX in either arm. Two thirds were stage III. At the cut-off time for analysis the median time of follow-up was 62 months and 772 relapses or deaths have been observed. The RFS rate at 8 years is 75%. This analysis was done when 82% of the planned number of events was reached, with a power of 72% instead of 80%. The decision to anticipate the analysis was based on the participation to the IDEA joint collaborative analysis of studies sharing this clinical question. The Hazard Ratio of the 3months vs 6 months for relapse/death was 1.14 (95%CI 0.99-1.31, p for non inferiority = 0.253) and the confidence interval crossed the non inferiority limit of 1.20. Conclusions: TOSCA was not able to demonstrate that 3 months of oxaliplatin-based adjuvant treatment is as efficacious as 6 months. Nevertheless , because the absolute difference in RFS between the two treatment durations is small ( less than 3 % at 5 years ), the decision to complete the whole 6-month program should be individualized based on toxicity and patients’ attitude. This study is registered with ClinicalTrials.gov Registration Number: NCT00646607. It was supported by a grant from AIFA (Agenzia Italiana del Farmaco) Grant Code FARM5RWTWZ. Clinical trial information: NCT00646607.

scholarly journals Responsibilities of Pregnant Women for on Going Pregnancy - Medical Aspects

2016 ◽  
Vol 9 (2) ◽  
pp. 121-130
Author(s):  
Ratko Matijević ◽  
Katja Erjavec
Keyword(s):  
Health Care ◽  
Pregnant Women ◽  
Pregnancy Outcome ◽  
Health Care Systems ◽  
Unborn Child ◽  
Communication Education ◽  
Mortality And Morbidity ◽  
Good Communication ◽  
Care Systems ◽  
Potential Damage

There are numerous factors known to affect the course of pregnancy and adversely impact perinatal mortality and morbidity. Some of them are avoidable and some are not. Avoidable factors can be either under responsibility of medical staff, health care systems and communities; or under responsibility of pregnant women. By modifying and changing their lifestyle, pregnant women can influence some avoidable factors and improve their pregnancy outcome. However, by ignoring them, they can cause potential damage to themselves and to their unborn child. There is no well defined responsibility for women concerning ways they influence their pregnancy outcome; they have a full right to make decisions about themselves and their unborn children, whether right or wrong. Good communication, education and understanding are essential when dealing with these issues.

scholarly journals Incorporating Patient Narratives to Enhance Audiological Care and Clinical Research Outcomes

2021 ◽  
Vol 30 (3S) ◽  
pp. 916-921 ◽  
Author(s):  
Khaya D. Clark ◽  
Angela C. Garinis ◽  
Dawn Konrad-Martin
Keyword(s):  
Quality Improvement ◽  
Health Care Systems ◽  
Clinical Care ◽  
Health Conditions ◽  
Patient Centered ◽  
Aural Rehabilitation ◽  
Experience Of Care ◽  
Patient Narratives ◽  
Care Processes ◽  
Care Systems

Purpose The engagement of patients as key stakeholders in their experience of care processes is a critical component of quality improvement efforts for both clinical care and translational research. Increasingly, health care systems are soliciting input from patients on care processes and experiences through surveys, patient interviews, and patient video narratives. The purpose of this viewpoint article is twofold: (a) to describe the increasing role of patient narratives about their experiences with adverse health conditions to inform patient-centered research and quality improvement efforts and (b) to present three patient narratives that highlight the real-world impacts of hearing loss and tinnitus, the life enhancing impacts of aural rehabilitation, and the importance of prospective ototoxicity monitoring in individuals with complex health conditions. Conclusion Patient narratives provide individual patient perspectives that can be used to build awareness of the range of experiences and impact of hearing disorders, and to explore patient preferences for when and how to implement hearing-related clinical services.

scholarly journals Covid-19 Detection Using AI

2021 ◽  
pp. 561-566
Author(s):  
Shashank Mishra ◽  
Himanshu Kumar Shukla ◽  
Rajiv Singh ◽  
Vivek Pandey ◽  
Shubham Sagar ◽  
...  
Keyword(s):  
Health Care ◽  
High Risk ◽  
Health Care Systems ◽  
Hospital Setting ◽  
Sudden Increase ◽  
Repeated Testing ◽  
Rt Pcr ◽  
X Ray ◽  
Care Systems ◽  
Chest X Ray

The sudden increase in COVID-19 patients is a major shock to our global health care systems. With limited availability of test kits, it is not possible for all patients with respiratory infections to be tested using RT-PCR. Testing also takes a long time, with limited sensitivity. The detection of COVID-19 infections on Chest X-Ray can help isolate patients at high risk while awaiting test results. X-Ray machines are already available in many health care systems, and with many modern X-Ray systems already installed on the computer, there is no travel time involved in the samples. In this work we propose the use of chest X-Ray to prioritize the selection of patients for further RT-PCR testing. This can be useful in a hospital setting where current systems have difficulty deciding whether to keep the patient in the ward with other patients or isolate them from COVID-19 areas. It may also be helpful in identifying patients with high risk of COVID with false positive RT-PCR that will require repeated testing. In addition, we recommend the use of modern AI techniques to detect COVID-19 patients who use X-Ray imaging in an automated manner, especially in areas where radiologists are not available, and help make the proposed diagnostic technology easier. Introducing the CovidAID: COVID-19 AI Detector, a model based on a deep neural network of screening patients for proper diagnosis. In a publicly available covid-chest x-ray-dataset [2], our model provides 90.5% accuracy with 100% sensitivity (remember) to COVID-19 infection. We are greatly improving the results of Covid-Net [10] on the same database.

Coronavirus Disease 2019 (COVID-19) and late Pregnancy Loss in Infected Pregnant Women: A Mini Review

2020 ◽  
Author(s):  
Mahmood Noorishadkam ◽  
MohamadHosein Lookzadeh ◽  
Mahta Mazaheri ◽  
Seyed Reza Mirjalili ◽  
Reza Bahrami ◽  
...  
Keyword(s):  
Health Care ◽  
Pregnant Women ◽  
Pregnancy Loss ◽  
Health Care Systems ◽  
Late Pregnancy ◽  
China National Knowledge Infrastructure ◽  
Knowledge Infrastructure ◽  
Care Systems ◽  
Medical Health Care ◽  
Bibliographic Search

Background: One of the main issues for health care systems during the coronavirus disease 2019 (COVID‑19) was whether infected pregnant women would have pregnancy complications compared with healthy pregnant women during the pandemic. There was no sufficient data about the risk and rate of late pregnancy loss in pregnant women infected with COVID-19. In this study we reviewed the late pregnancy loss in infected pregnant women with COVID-19. Methods: A comprehensive bibliographic search was conducted in PubMed, Google Scholar, SciELO, Springer Link, China National Knowledge Infrastructure (CNKI) platforms, and Wan Fang database to identify relevant studies published up to September 10, 2020. Results: A total of seven cohort studies exclusively on late pregnancy loss and infected women with COVID-19 were selected. Conclusions: No evidence supported higher risk of late pregnancy loss in pregnant women with COVID-19. We suggested that the pandemic rapidly unfolds, it is critical that medical health care staffs keep up to date and caution should be undertaken to further study and monitor possible infection in the late pregnant mothers.

A predictive model of pcsk-9 inhibitors eligibility in coronary and dyslipidemic patients

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
I Dima ◽  
D Soulis ◽  
D Terentes-Printzios ◽  
I Skoumas ◽  
K Aznaouridis ◽  
...  
Keyword(s):  
Health Care ◽  
Cardiovascular Risk ◽  
High Risk ◽  
Predictive Model ◽  
Health Care Systems ◽  
Clinical Status ◽  
Risk Groups ◽  
Funding Source ◽  
Private Company ◽  
Care Systems

Abstract Purpose Dyslipidemia is a major cardiovascular risk factor and treatment is mostly based on statins and ezetimibe. PCSK-9 inhibitors are monoclonal antibodies that reduce LDL-c levels and have shown significant reduction of cardiovascular risk in high risk patients. Data regarding potential eligibility for PCSK-9, is limited especially when referring to the recent guidelines. Methods Eligibility was calculated using a proprietary adjustable software, which stores data and patient information and thus by using different criteria it can determine potential candidates for PCSK-9 inhibitors. For this purpose, 2000 patients were enrolled prospectively. Our study population was comprised of inpatients diagnosed either with acute coronary syndromes (ACS) or with chronic coronary disease (cCAD) and outpatients from Lipids' Clinic (OLC) (n=407, n=1087, n=506, respectively). In order to test eligibility, three different LDL thresholds were used in our model for high and very high risk groups: a) 70mg/dl and 55mg/dl, respectively, as recommended by the recently updated 2019 ESC/EAS Guidelines for Dyslipidaemia b) 100mg/dl and 70mg/dl, respectively, as recommended by the 2016 ESC/EAS Guidelines for Dyslipidaemias and c) 130mg/dl and 100mg/dl respectively, as mandated by our National Health Care system but also applicable in other countries. Results The eligible percentages for the three thresholds were 18.85%, 9.75% and 2.15%, in the total population (TP) respectively and it varied according to clinical status. Subgroup analysis of eligible population revealed the trends in each group (Figure 1). The increase toward more recent guidelines was mostly attributed to the increasing number of coronary patients who become eligible as our criteria become stricter. Conclusions Our predictive model provides a realistic estimation of PCSK-9 inhibitors potential eligibility in coronary and dyslipidaemic patients and thus it can become a useful tool for the use of PCSK-9 in health care systems. Figure 1 Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Amgen Hellas LTD

scholarly journals Artificial Intelligence in the Fight Against COVID-19 in the Banking Sector

2020 ◽  
Vol 1 (1) ◽  
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Decision Making ◽  
High Risk ◽  
Health Care System ◽  
Banking Sector ◽  
Health Care Systems ◽  
Use Cases ◽  
Care Systems ◽  
Human Thinking

The COVID-19 pandemic has been causing a massive strain in different sectors around the globe, especially in the health care systems in many countries. Artificial Intelligence has found its way in the health care system in helping to find a cure or vaccine by screening out medicines that could be promising for cure. Not only that but by containing the virus and predicting highly effected areas and limiting the spread of the virus. Many use cases based on AI was successful to monitor the spread and lock areas that were predicted by AI algorithms to be at high risk. Broadly speaking, AI involves ‘the ability of machines to emulate human thinking, reasoning and decision - making.

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