Propofol and Kearns-Sayre Syndrome: An idiographic approach

With the focus on an idiographic approach whereby the observations incorporated the various dimensions of individual functioning ‘top-down’ to ‘bottom-up’, this case report describes the successful management of a 14-year-old girl with Kearns-Sayre syndrome and Dyggve-Melchior-Clausen disease requiring a transvenous permanent pacemaker implantation for complete heart block. The patient presented to a tertiary care centre in Muscat, Oman, in 2023 seeking consultation. The current idiographic approach appears to have a heuristic value for 2 interrelated reasons. Firstly, it is unlikely that even tertiary care units can accrue such rare presentations and scrutinise them under nomothetic approach. Secondly, by employing the idiographic approach that is capable of examining each case in-depth, the aspiration for good health and well-being may come to the forefront. To the best of the authors’ knowledge this is the first published idiographic report in anaesthesia care. Keywords: Intravenous Anaesthetics; Artificial Pacemaker; Kearns-Sayre Syndrome; Propofol; Idiographic Approach; Case Report; Oman

Fabrication of polyethersulfone electrospun nanofibrous membranes incorporated with hydrous manganese dioxide for enhanced ultrafiltration of oily solution

In this work, a new type of ultrafiltration (UF) electrospun nanofibrous membranes (ENMs) incorporating hydrous manganese dioxide (HMO) nanoparticles was fabricated with the objective of improving properties of polyethersulfone (PES)-based membrane for synthetic oily solution treatment. Two treatments were carried out to improve the mechanical property and hydrophilicity of the PES-based membrane without compromising its porosity and water permeance. The first treatment involved the use of mixed solvents – dimethylformamide and n-methyl-pyrrolidinone (DMF/NMP) in which NMP is a high vapor pressure component that could enhance the mechanical properties of the nanofibrous by improving solvent-induced fusion of inter-fiber junction points. The second treatment involved the incorporation of specific amount of HMO nanoparticles in PES dope solution to enhance membrane hydrophilicity. Heat treatment was also adopted as an effective approach to strengthen and prevent delamination of the nanofibrous mat during UF process. The HMO-incorporated ENMs exhibited an excellent oil rejection (97.98% and 94.04%) and a promising water flux recovery (89.29% and 71.10%) when used to treat a synthetic oily solution containing 5000 or 10,000 ppm oil, respectively. The best promising HMO-incorporated ENM exhibited much higher magnitude of water productivity (>7000 L/m2h) without sacrificing oil removal rate. Most importantly, this nanofillers-incorporated membrane showed significantly lower degree of flux decline as a result of improved surface resistance against oil fouling and is of potential for long-term operation with extended lifespan. The promising mechanical and anti-fouling properties of the ENMs is potentially applicable in the efficient industrial oily effluents treatment when challenged with oil-in-water emulsions

The gulf implantable cardioverter-defibrillator registry: Rationale, methodology, and implementation

Background: The implantable cardioverter-defibrillator (ICD) is effective in the prevention of sudden cardiac death in high-risk patients. Little is known about ICD use in the Arabian Gulf. We designed a study to describe the characteristics and outcomes of patients receiving ICDs in the Arab Gulf region. Methods: Gulf ICD is a prospective, multi-center, multinational, and observational study. All adult patients 18 years or older, receiving a de novo ICD implant and willing to sign a consent form will be eligible. Data on baseline characteristics, ICD indication, procedure and programing, in-hospital, and 1-year outcomes will be collected. Target enrollment is 1500 patients, which will provide adequate precision across a wide range of expected event rates. Results: Fifteen centers in six countries are enrolling patients (Saudi Arabia, United Arab Emirates, Kuwait, Oman, Bahrain, and Qatar). Two-thirds of the centers have dedicated electrophysiology laboratories, and in almost all centers ICDs are implanted exclusively by electrophysiologists. Nearly three-quarters of the centers reported annual ICD implant volumes of ≤150 devices, and pulse generator replacements constitute <30% of implants in the majority of centers. Enrollment started in December 2013, and accrual rate increased as more centers entered the study reaching an average of 98 patients per month. Conclusions: Gulf ICD is the first prospective, observational, multi-center, and multinational study of the characteristics and, the outcomes of patients receiving ICDs in the Arab Gulf region. The study will provide valuable insights into the utilization of and outcomes related to ICD therapy in the Gulf region

Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study

Background Preterm birth is a major global health challenge, the leading cause of death in children under 5 years of age, and a key measure of a population’s general health and nutritional status. Current clinical methods of estimating fetal gestational age are often inaccurate. For example, between 20 and 30 weeks of gestation, the width of the 95% prediction interval around the actual gestational age is estimated to be 18–36 days, even when the best ultrasound estimates are used. The aims of this study are to improve estimates of fetal gestational age and provide personalised predictions of future growth. Methods Using ultrasound-derived, fetal biometric data, we developed a machine learning approach to accurately estimate gestational age. The accuracy of the method is determined by reference to exactly known facts pertaining to each fetus—specifically, intervals between ultrasound visits—rather than the date of the mother’s last menstrual period. The data stem from a sample of healthy, well-nourished participants in a large, multicentre, population-based study, the International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st). The generalisability of the algorithm is shown with data from a different and more heterogeneous population (INTERBIO21st Fetal Study). Findings In the context of two large datasets, we estimated gestational age between 20 and 30 weeks of gestation with 95% confidence to within 3 days, using measurements made in a 10-week window spanning the second and third trimesters. Fetal gestational age can thus be estimated in the 20–30 weeks gestational age window with a prediction interval 3–5 times better than with any previous algorithm. This will enable improved management of individual pregnancies. 6-week forecasts of the growth trajectory for a given fetus are accurate to within 7 days. This will help identify at-risk fetuses more accurately than currently possible. At population level, the higher accuracy is expected to improve fetal growth charts and population health assessments. Interpretation Machine learning can circumvent long-standing limitations in determining fetal gestational age and future growth trajectory, without recourse to often inaccurately known information, such as the date of the mother’s last menstrual period. Using this algorithm in clinical practice could facilitate the management of individual pregnancies and improve population-level health. Upon publication of this study, the algorithm for gestational age estimates will be provided for research purposes free of charge via a web portal

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population