Digital decision aid for prenatal counseling in imminent extreme premature labor: development and pilot testing

Background In case of extreme premature delivery at 24 weeks of gestation, both early intensive care and palliative comfort care for the neonate are considered treatment options. Prenatal counseling, preferably using shared decision making, is needed to agree on the treatment option in case labor progresses. This article described the development of a digital decision aid (DA) to support pregnant women, partners and clinicians in prenatal counseling for imminent extreme premature labor. Methods This DA is developed following the International Patient Decision Aid Standards. The Dutch treatment guideline and the Dutch recommendations for prenatal counseling in extreme prematurity were used as basis. Development of the first prototype was done by expert clinicians and patients, further improvements were done after alpha testing with involved clinicians, patients and other experts (n = 12), and beta testing with non-involved clinicians and patients (n = 15). Results The final version includes information, probabilities and figures depending on users’ preferences. Furthermore, it elicits patient values and provides guidance to aid parents and professionals in making a decision for either early intensive care or palliative comfort care in threatening extreme premature delivery. Conclusion A decision aid was developed to support prenatal counseling regarding the decision on early intensive care versus palliative comfort care in case of extreme premature delivery at 24 weeks gestation. It was well accepted by parents and healthcare professionals. Our multimedia, digital DA is openly available online to support prenatal counseling and personalized, shared decision-making in imminent extreme premature labor.

Policy Spotlight Effect in Critical Time-Sensitive Diseases

Background: Categorization of hospital emergency capability (CHEC) is a policy implemented worldwide to regionalize critical emergent care. The CHEC policy mainly uses time-based indicators as emergency care quality measurements.Objectives: We aimed to explore the CHEC policy spotlight effect on critical time-sensitive diseases with and without the influence of time-based surveillance indicators and guidelines. Research Design: We conducted a nationwide retrospective cohort study between 2005–2011. Regarding critical time-sensitive diseases, our study targeted acute ischemic stroke (AIS), ST-segment elevation myocardial infarction (STEMI), septic shock, and major trauma. We selected diagnosis and treatment guideline adherence as process quality measures and defined medical utilization, upward transfer rate, and short-term mortality rate as outcome indicators. Subjects: The Taiwan National Health Insurance 2005 Longitudinal Health Insurance Database contains one million random cases, including medical records and hospital information. Results: During this 7-year study AIS, STEMI, septic shock, and major trauma, respectively. AIS and STEMI cohorts had significantly higher rates of guideline adherence and better process quality than those of septic shock and major trauma cohorts. Furthermore, AIS and STEMI cohorts had a significant increase in diagnosis costs. Conclusion: The CHEC policy spotlight effect exists in critical time-sensitive diseases with time-based quality indicators. Importantly, disease entities without these indicators may experience decreases in diagnosis and treatment guideline adherence, indirectly jeopardizing their outcomes.

Prevalence and Antimicrobial Resistance of Enterococcus Species: A Retrospective Cohort Study in Italy

Antimicrobial resistance represents one of the main threats to healthy ecosystems. In recent years, among the multidrug-resistant microorganisms responsible for nosocomial infections, the Enterococcus species have received much attention. Indeed, Enterococcus have peculiar skills in their ability to acquire resistance genes and to cause severe diseases, such as endocarditis. This study showed the prevalence and antimicrobial resistance rate of Enterococcus spp. isolated from clinical samples, from January 2015 to December 2019 at the University Hospital “San Giovanni di Dio e Ruggi d’Aragona” in Salerno, Italy. A total of 3236 isolates of Enterococcus faecalis (82.2%) and Enterococcus faecium (17.8%) were collected from urine cultures, blood cultures, catheters, respiratory tract, and other samples. Bacterial identification and antibiotic susceptibility were performed with VITEK 2. E. faecium showed a high resistance rate against ampicillin (84.5%), ampicillin/sulbactam (82.7%), and imipenem (86.7%), while E. faecalis showed the highest resistance rate against gentamicin and streptomycin high level, but both were highly sensitive to such antibiotics as tigecycline and vancomycin. Studies of surveillance are an important tool to detect changes in the resistance profiles of the main pathogens. These antimicrobial susceptibility patterns are necessary to improve the empirical treatment guideline of infections.

Guidelines for the conservative treatment of spinal deformities – Questionnaire for a Delphi consensus

Background: Spinal deformity is the oldest disease known to humankind. Many types of treatment methods, including both conservative and surgical, are in use.Objective: We aimed to validate a published guideline protocol based on the conservative treatment of spinal deformities.Method: A modified Delphi technique was used with a questionnaire sent out to professionals worldwide regarding the conservative treatment of spinal deformities.Results: Our study was completed after two rounds. A strong level of agreement of 80% and more (consensus cut-off point) was achieved in most questions in the first round. Some statements were below this margin, and they were sent to the participants via email in the second round for re-evaluation. Consensus was achieved in almost all of the statements in the second round. Only two items did not reach the cut-off point but were close to this value.Conclusion: This proposed Guideline Protocol was approved by the participants using the Delphi method and can be used as a valid tool for the conservative treatment of spinal deformities.Clinical implications: A conservative treatment guideline in spinal deformity management, will provide consistency in treatment and will facilitate comparability with surgery. It will be useful in determining the cost-effectiveness of treatment and in choosing the right patient for the right method of treatment. This guideline might help in this context, and may also create a systematic method for clinicians to use as a reference in both research and clinical practice.

Prevalence of antimicrobial resistance and its clinical implications in Ethiopia: a systematic review

Background Antimicrobial resistance is one of the major public health challenges in Ethiopia. However, there is no comprehensive summary of existing AMR data in the country. Aim To determine the prevalence of antimicrobial resistance and its clinical implications in Ethiopia. Methods A systematic literature search was performed on the PubMed/Medline database. Original studies on antimicrobial resistance conducted in Ethiopia between 1st January 2009 and 31st July 2019 were included. The outcome measure was the number of isolates resistant to antimicrobial agents in terms of specific pathogens, and disease condition. Data was calculated as total number of resistant isolates relative to the total number of isolates per specific pathogen and medication. Results A total of 48,021 study participants enrolled from 131 original studies were included resulting in 15,845 isolates tested for antimicrobial resistance. The most common clinical sample sources were urine (28%), ear, nose, and throat discharge collectively (27%), and blood (21%). All the studies were cross-sectional and 83% were conducted in hospital settings. Among Gram-positive bacteria, the reported level of resistance to vancomycin ranged from 8% (Enterococcus species) to 20% (S. aureus). E. coli, K. pneumoniae and P. aeruginosa were the most common Gram-negative pathogens resistant to key antimicrobial agents described in the national standard treatment guideline and were associated with diverse clinical conditions: urinary tract infections, diarrhea, surgical site infections, pneumonia, ocular infections, and middle ear infections. Conclusion Overall, there is a high prevalence of antimicrobial resistance in Ethiopia. Empirical treatment of bacterial infections needs to be guided by up-to-date national guidelines considering local antimicrobial susceptibility patterns. Equipping diagnostic laboratories with culture and drug susceptibility testing facilities, and establishing a strong antimicrobial stewardship program should be high priorities.

Novel observational study protocol to develop a prediction model that identifies patients with Graves’ ophthalmopathy insensitive to intravenous glucocorticoids pulse therapy

IntroductionIntravenous glucocorticoids pulse therapy is the first-line treatment for moderate-to-severe and active Graves’ ophthalmopathy, with a large proportion of patients having poor efficacy and exposed to the risk of glucocorticoids adverse effects. We introduce a novel protocol to develop a prediction model designed to identify patients with Graves’ ophthalmopathy who are not likely to benefit from intravenous glucocorticoids pulse therapy before administration, so that these patients can advance the time to receive appropriate treatment. Existing prediction models for prognosis of Graves’ ophthalmopathy have usually focused on traditional clinical indicators without adequate consideration of orbital soft tissue changes. Our protocol for model development will address this limitation by using artificial intelligence models to quantify facial morphological changes.Methods and analysisThis study is a single-centre, prospective and observational study. A sample size of 278 patients with moderate-to-severe and active Graves’ ophthalmopathy will be prospectively recruited at ophthalmology clinic of Shanghai Ninth People’s Hospital to collect clinical and artificial intelligence model’s baseline data as potential variables to develop the prediction model. They will receive 12-week intravenous glucocorticoids pulse therapy according to the 2021 European Group on Graves’ Orbitopathy treatment guideline. After standard medication course and following 12-week observation, patients will be evaluated for the effectiveness of treatment in our ophthalmology clinic and divided into glucocorticoids-sensitive and glucocorticoids-insensitive groups. The model will be developed by means of multivariate logistic regression to select the best variables for the prediction of glucocorticoids treatment efficacy before administration. The result of the study will provide evidence for the use of a prediction model to personalise treatment options for patients with moderate-to-severe and active Graves’ ophthalmopathy.Ethics and disseminationThe study received approval from the Ethics Committee of Shanghai Ninth People’s Hospital (ethical approval number: SH9H-2020-T211-1. Findings will be disseminated via peer-reviewed publications and conference presentations.Trial registration numberChiCTR2000036584 (Pre-results).

Assessment of Antibiotic Prescription Pattern Using who Prescribing Indicators and Aware Categorization of Antibiotics

Background: Medicines play a crucial role in the healthcare delivery of a hospital. The appropriate use of medicines gives us assessment of the quality of health services being provided in a particular region. Aim: To evaluate the prescribing practices and antibiotic utilization patterns so that the extent of irrational use can be assessed by comparing them with published ideal values set by WHO. Study design: Retrospective, cross-sectional study. Place and duration of study: Teaching Hospital of Faisalabad: Independent University Hospital (IUH), from Jan 2018 to June/July 2018. Methodology: 200 cases were selected through systematic random sampling from medicine/surgery wards and pharmacy registers. The standard World Health Organization prescribing indicators and AWaRe categorization of antibiotics were used to assess the prescribing practices of physicians/surgeons. Published ideal standards for each of the indicators were compared with study findings to identify extent of irrational drug use. Results: Most of the facility indicators were met with. The Drug and Therapeutic Committee (DTC) was functional. The Standard treatment guideline booklets (STGs) and Essential Drugs List (EDL) of the hospital were available. 88% of the key drugs listed in EDL were available in stock. The expenditure on antibiotics compared to total medicines was 17%. Regarding prescribing indicators: the average number of drugs prescribed per encounter was 6 (optimal value 1.6–1.8). Average no of antibiotic per prescription amounted to almost 1 (0.925). % prescriptions with an antibiotic amounted to 72% (optimal value 20-26.8%).72% antibiotics were prescribed from the EDL formulary of the hospital (optimal value 100%). Conclusion: Regarding compliance with prescribing indicators and AWaRe categorization of antibiotics by WHO, significant deviation was observed. Education and training of physicians according to WHO parameters is required to ensure rational prescribing. Keywords: Prescription pattern, WHO Prescribing Indicators, AWaRe Categorization

The Practices of Anaesthesiologists in the Management of Patients with Sickle Cell Disease: Empirical Evidence from Cameroon

Patients with sickle cell disease are more likely to undergo surgery during their lifetime, especially given the numerous complications they may develop. There is a paucity of data concerning the management of patients with sickle cell disease by anaesthesiologists, especially in Africa. This study aimed to describe the practices of anaesthesiologists in Cameroon concerning the perioperative management of patients with sickle cell disease. A cross-sectional study was carried out over four months and involved 35 out 47 anaesthesiologists working in hospitals across the country, who were invited to fill a data collection form after giving their informed consent. The data were analysed using descriptive statistics and a binary logistic regression model. Among the 35 anaesthesiologists included in the study, most (29 (82.9%)) had managed patients with sickle cell disease for both emergency and elective surgical procedures. Most of them had never asked for a haematology consultation before surgery. Most participants (26 (74.3%)) admitted to having carried out simple blood transfusions, while 4 (11.4%) carried out exchange transfusions. The haemoglobin thresholds for transfusion varied from one practitioner to another, between < 6 g/dl and < 9 g/dl. Only 6 (17.1%) anaesthesiologists had a treatment guideline for the management of patients with sickle cell disease in the hospitals where they practiced. Only 9 (25.7%) prescribed a search for irregular agglutinins. The percentage of haemoglobin S before surgery was always available for 5 (14.3%) of the participants. The coefficient (0.06) of the occurrence of a haematology consultation before surgery had a significant influence on the probability of management of post-operative complications (coefficient 0.06, 10% level of probability). This study highlights the fact that practices in the perioperative management of patients with sickle cell disease in Cameroon vary greatly from one anaesthesiologist to another. We disclosed major differences in the current recommendations, which support the fact that even in Sub-Saharan countries, guidelines applicable to the local settings should be published.

Feature Selection Approach to Improve Malaria Diagnosis Model for High and Low Endemic Areas of Tanzania

Malaria remains an important cause of death, especially in sub-Saharan Africa with about 228 million malaria cases worldwide and an estimated 405,000 deaths in 2019. Currently, malaria is diagnosed in the health facility using a microscope (BS) or rapid malaria diagnostic test (MRDT) and with area where these tools are inadequate the presumptive treatment is performed. Apart from that self-diagnosis and treatment is also practiced in some of the households. With the high-rate self-medication on malaria drugs, this study aimed at computing the most significant features using feature selection methods for best prediction of malaria in Tanzania that can be used in developing a machine learning model for malaria diagnosis. A malaria symptoms and clinical diagnosis dataset were extracted from patients&rsquo; files from four (4) identified health facilities in the regions of Kilimanjaro and Morogoro. These regions were selected to represent the high endemic areas (Morogoro) and low endemic areas (Kilimanjaro) in the country. The dataset contained 2556 instances and 36 variables. The random forest classifier a tree based was used to select the most important features for malaria prediction. Regional based features were obtained to facilitate accurate prediction. The feature ranking as indicated that fever is universally the most influential feature for predicting malaria followed by general body malaise, vomiting and headache. However, these features are ranked differently across the regional datasets. Subsequently, six predictive models, using important features selected by feature selection method, were used to evaluate the features performance. The features identified complies with malaria diagnosis and treatment guideline provided with WHO and Tanzania Mainland. The compliance is observed so as to produce a prediction model that will fit in the current health care provision system in Tanzania.