LDHB contributes to the regulation of lactate levels and basal insulin secretion in human pancreatic ß cells.

Using 13C6 glucose labeling coupled to gas chromatography-mass spectrometry and 2D 1H-13C heteronuclear single quantum coherence NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning ß cell function. In both mouse and human islets, the contribution of glucose to the tricarboxylic acid (TCA) cycle is similar. Pyruvate fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While the conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is 6-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and ß cell-specific LDHB expression. LDHB inhibition amplifies LDHA-dependent lactate generation in mouse and human ß cells and increases basal insulin release. Lastly, cis-instrument Mendelian randomization shows that low LDHB expression levels correlate with elevated fasting insulin in humans. Thus, LDHB limits lactate generation in ß cells to maintain appropriate insulin release.

Predicting Successful Weaning from Mechanical Ventilation by Reduction in Positive End-expiratory Pressure Level Using Machine Learning.

Weaning patients from mechanical ventilation (MV) is a critical and resource intensive process in the Intensive Care Unit (ICU) that impacts patient outcomes and healthcare expenses. Weaning methods vary widely among providers. Prolonged MV is associated with adverse events and higher healthcare expenses. Predicting weaning readiness is a non-trivial process in which the positive end-expiratory pressure (PEEP), a crucial component of MV, has potential to be indicative but has not yet been used as the target. We aimed to predict successful weaning from mechanical ventilation by targeting changes in the PEEP-level using a supervised machine learning model. This retrospective study included 12,153 mechanically ventilated patients from Medical Information Mart for Intensive Care (MIMIC-IV) and eICU collaborative research database (eICU-CRD). Two machine learning models (Extreme Gradient Boosting and Logistic Regression) were developed using a continuous PEEP reduction as target. The data is splitted into 80% as training set and 20% as test set. The model's predictive performance was reported using 95% confidence interval (CI), based on evaluation metrics such as area under the receiver operating characteristic (AUROC), area under the precision-recall curve (AUPRC), F1-Score, Recall, positive predictive value (PPV), and negative predictive value (NPV). The model's descriptive performance was reported as the variable ranking using SHAP (SHapley Additive exPlanations) algorithm. The best model achieved an AUROC of 0.84 (95% CI 0.83-0.85) and an AUPRC of 0.69 (95% CI 0.67-0.70) in predicting successful weaning based on the PEEP reduction. The model demonstrated a Recall of 0.85 (95% CI 0.84-0.86), F1-score of 0.86 (95% CI 0.85-0.87), PPV of 0.87 (95% CI 0.86-0.88), and NPV of 0.64 (95% CI 0.63-0.66). Most of the variables that SHAP algorithm ranked to be important correspond with clinical intuition, such as duration of MV, oxygen saturation (SaO2), PEEP, and Glasgow Coma Score (GCS) components. This study demonstrates the potential application of machine learning in predicting successful weaning from MV based on continuous PEEP reduction. The model's high PPV and moderate NPV suggest that it could be a useful tool to assist clinicians in making decisions regarding ventilator management.

Predicting Hypoxia Using Machine Learning: Systematic Review.

Background: Hypoxia is an important risk factor and indicator for the declining health of inpatients. Predicting future hypoxic events using machine learning is a prospective area of study to facilitate time-critical interventions to counter patient health deterioration. Objective: This systematic review aims to summarize and compare previous efforts to predict hypoxic events in the hospital setting using machine learning with respect to their methodology, predictive performance, and assessed population. Methods: A systematic literature search was performed using Web of Science, Ovid with Embase and MEDLINE, and Google Scholar. Studies that investigated hypoxia or hypoxemia of hospitalized patients using machine learning models were considered. Risk of bias was assessed using the Prediction Model Risk of Bias Assessment Tool. Results: After screening, a total of 12 papers were eligible for analysis, from which 32 models were extracted. The included studies showed a variety of population, methodology, and outcome definition. Comparability was further limited due to unclear or high risk of bias for most studies (10/12, 83%). The overall predictive performance ranged from moderate to high. Based on classification metrics, deep learning models performed similar to or outperformed conventional machine learning models within the same studies. Models using only prior peripheral oxygen saturation as a clinical variable showed better performance than models based on multiple variables, with most of these studies (2/3, 67%) using a long short-term memory algorithm. Conclusions: Machine learning models provide the potential to accurately predict the occurrence of hypoxic events based on retrospective data. The heterogeneity of the studies and limited generalizability of their results highlight the need for further validation studies to assess their predictive performance.

Safety outcomes of bariatric surgery in patients with advanced organ disease: the ONWARD study: a prospective cohort study.

INTRODUCTION: Increasing numbers of patients with advanced organ disease are being considered for bariatric and metabolic surgery (BMS). There is no prospective study on the safety of BMS in these patients. This study aimed to capture outcomes for patients with advanced cardiac, renal, or liver disease undergoing BMS. MATERIALS AND METHODS: This was a multinational, prospective cohort study on the safety of elective BMS in adults (≥18 years) with advanced disease of the heart, liver, or kidney. RESULTS: Data on 177 patients with advanced diseases of heart, liver, or kidney were submitted by 75 centres in 33 countries. Mean age and BMI was 48.56±11.23 years and 45.55±7.35 kg/m 2 , respectively. Laparoscopic sleeve gastrectomy was performed in 124 patients (70%). The 30-day morbidity and mortality were 15.9% ( n =28) and 1.1% ( n =2), respectively. Thirty-day morbidity was 16.4%, 11.7%, 20.5%, and 50.0% in patients with advanced heart ( n =11/61), liver ( n =8/68), kidney ( n =9/44), and multi-organ disease ( n =2/4), respectively. Cardiac patients with left ventricular ejection fraction less than or equal to 35% and New York Heart Association classification 3 or 4, liver patients with model for end-stage liver disease score greater than or equal to 12, and patients with advanced renal disease not on dialysis were at increased risk of complications. Comparison with a propensity score-matched cohort found advanced disease of the heart, liver, or kidney to be significantly associated with higher 30-day morbidity. CONCLUSION: Patients with advanced organ disease are at increased risk of 30-day morbidity following BMS. This prospective study quantifies that risk and identifies patients at the highest risk.

Mitochondrial Metabolism in the Spotlight: Maintaining Balanced RNAP III Activity Ensures Cellular Homeostasis.

RNA polymerase III (RNAP III) holoenzyme activity and the processing of its products have been linked to several metabolic dysfunctions in lower and higher eukaryotes. Alterations in the activity of RNAP III-driven synthesis of non-coding RNA cause extensive changes in glucose metabolism. Increased RNAP III activity in the S. cerevisiae maf1Δ strain is lethal when grown on a non-fermentable carbon source. This lethal phenotype is suppressed by reducing tRNA synthesis. Neither the cause of the lack of growth nor the underlying molecular mechanism have been deciphered, and this area has been awaiting scientific explanation for a decade. Our previous proteomics data suggested mitochondrial dysfunction in the strain. Using model mutant strains maf1Δ (with increased tRNA abundance) and rpc128-1007 (with reduced tRNA abundance), we collected data showing major changes in the TCA cycle metabolism of the mutants that explain the phenotypic observations. Based on 13C flux data and analysis of TCA enzyme activities, the present study identifies the flux constraints in the mitochondrial metabolic network. The lack of growth is associated with a decrease in TCA cycle activity and downregulation of the flux towards glutamate, aspartate and phosphoenolpyruvate (PEP), the metabolic intermediate feeding the gluconeogenic pathway. rpc128-1007, the strain that is unable to increase tRNA synthesis due to a mutation in the C128 subunit, has increased TCA cycle activity under non-fermentable conditions. To summarize, cells with non-optimal activity of RNAP III undergo substantial adaptation to a new metabolic state, which makes them vulnerable under specific growth conditions. Our results strongly suggest that balanced, non-coding RNA synthesis that is coupled to glucose signaling is a fundamental requirement to sustain a cell's intracellular homeostasis and flexibility under changing growth conditions. The presented results provide insight into the possible role of RNAP III in the mitochondrial metabolism of other cell types.

Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation.

Prolonged mechanical ventilation (PMV) after lung transplantation poses several risks, including higher tracheostomy rates and increased in-hospital mortality. Mechanical power (MP) of artificial ventilation unifies the ventilatory variables that determine gas exchange and may be related to allograft function following transplant, affecting ventilator weaning. We retrospectively analyzed consecutive double lung transplant recipients at a national transplant center, ventilated through endotracheal tubes upon ICU admission, excluding those receiving extracorporeal support. MP and derived indexes assessed up to 36 h after transplant were correlated with invasive ventilation duration using Spearman's coefficient, and we conducted receiver operating characteristic (ROC) curve analysis to evaluate the accuracy in predicting PMV (>72 h), expressed as area under the ROC curve (AUROC). PMV occurred in 82 (35%) out of 237 cases. MP was significantly correlated with invasive ventilation duration (Spearman's ρ = 0.252 [95% CI 0.129-0.369], p < 0.01), with power density (MP normalized to lung-thorax compliance) demonstrating the strongest correlation (ρ = 0.452 [0.345-0.548], p < 0.01) and enhancing PMV prediction (AUROC 0.78 [95% CI 0.72-0.83], p < 0.01) compared to MP (AUROC 0.66 [0.60-0.72], p < 0.01). Mechanical power density may help identify patients at risk for PMV after double lung transplantation.

Towards interoperability in infection control: a standard data model for microbiology.

The COVID-19 pandemic has made it clear: sharing and exchanging data among research institutions is crucial in order to efficiently respond to global health threats. This can be facilitated by defining health data models based on interoperability standards. In Germany, a national effort is in progress to create common data models using international healthcare IT standards. In this context, collaborative work on a data set module for microbiology is of particular importance as the WHO has declared antimicrobial resistance one of the top global public health threats that humanity is facing. In this article, we describe how we developed a common model for microbiology data in an interdisciplinary collaborative effort and how we make use of the standard HL7 FHIR and terminologies such as SNOMED CT or LOINC to ensure syntactic and semantic interoperability. The use of international healthcare standards qualifies our data model to be adopted beyond the environment where it was first developed and used at an international level.

Integrated NMR and MS Analysis of the Plasma Metabolome Reveals Major Changes in One-Carbon, Lipid, and Amino Acid Metabolism in Severe and Fatal Cases of COVID-19.

Brazil has the second-highest COVID-19 death rate worldwide, and Rio de Janeiro is among the states with the highest rate in the country. Although vaccine coverage has been achieved, it is anticipated that COVID-19 will transition into an endemic disease. It is concerning that the molecular mechanisms underlying clinical evolution from mild to severe disease, as well as the mechanisms leading to long COVID-19, are not yet fully understood. NMR and MS-based metabolomics were used to identify metabolites associated with COVID-19 pathophysiology and disease outcome. Severe COVID-19 cases (n = 35) were enrolled in two reference centers in Rio de Janeiro within 72 h of ICU admission, alongside 12 non-infected control subjects. COVID-19 patients were grouped into survivors (n = 18) and non-survivors (n = 17). Choline-related metabolites, serine, glycine, and betaine, were reduced in severe COVID-19, indicating dysregulation in methyl donors. Non-survivors had higher levels of creatine/creatinine, 4-hydroxyproline, gluconic acid, and N-acetylserine, indicating liver and kidney dysfunction. Several changes were greater in women; thus, patients' sex should be considered in pandemic surveillance to achieve better disease stratification and improve outcomes. These metabolic alterations may be useful to monitor organ (dys) function and to understand the pathophysiology of acute and possibly post-acute COVID-19 syndromes.

Intermittent Surface Oxygenation Results in Similar Mitochondrial Protection and Maintenance of Aerobic Metabolism as Compared to Continuous Oxygenation during Hypothermic Machine Kidney Machine Perfusion.

Short bubble and subsequent surface oxygenation is an innovative oxygenation technique and alternative for membrane oxygenation during hypothermic machine perfusion (HMP). The metabolic effect of the interruption of surface oxygenation for 4 h (mimicking organ transport) during HMP was compared to continuous surface and membrane oxygenation in a pig kidney ex situ preservation model. After 30 min of warm ischemia by vascular clamping, a kidney of a ±40 kg pig was procured and subsequently preserved according to one of the following groups: (1) 22-h HMP + intermittent surface oxygenation (n = 12); (2) 22-h HMP + continuous membrane oxygenation (n = 6); and (3) 22-h HMP + continuous surface oxygenation (n = 7). Brief perfusate O2 uploading before kidney perfusion was either obtained by direct bubble (groups 1, 3) or by membrane (group 2) oxygenation. Bubble oxygenation during minimum 15 min was as efficient as membrane oxygenation in achieving supraphysiological perfusate pO2 levels before kidney perfusion. Metabolic tissue analysis (i.e., lactate, succinate, ATP, NADH, and FMN) during and at the end of the preservation period demonstrated similar mitochondrial protection between all study groups. Short bubble and subsequent intermittent surface oxygenation of the perfusate of an HMP-kidney might be an effective and cheap preservation strategy to protect mitochondria, eliminating the need/costs of a membrane oxygenator and oxygen source during transport.

Data suggested hospitalization as critical indicator of the severity of the COVID-19 pandemic, even at its early stages.

COVID-19 has been spreading widely since January 2020, prompting the implementation of non-pharmaceutical interventions and vaccinations to prevent overwhelming the healthcare system. Our study models four waves of the epidemic in Munich over two years using a deterministic, biology-based mathematical model of SEIR type that incorporates both non-pharmaceutical interventions and vaccinations. We analyzed incidence and hospitalization data from Munich hospitals and used a two-step approach to fit the model parameters: first, we modeled incidence without hospitalization, and then we extended the model to include hospitalization compartments using the previous estimates as a starting point. For the first two waves, changes in key parameters, such as contact reduction and increasing vaccinations, were enough to represent the data. For wave three, the introduction of vaccination compartments was essential. In wave four, reducing contacts and increasing vaccinations were critical parameters for controlling infections. The importance of hospitalization data was highlighted, as it should have been included as a crucial parameter from the outset, along with incidence, to avoid miscommunication with the public. The emergence of milder variants like Omicron and a significant proportion of vaccinated people has made this fact even more evident.

Global trends in BMS research using publication as a surrogate marker: A 30 year review.

Obesity is a global pandemic with increasing prevalence and long-term negative health outcomes. Bariatric metabolic surgery (BMS) is the most effective treatment option for achieving long-term weight loss. A systematic search was performed from 1990 to 2020 of BMS procedures using standardised groups. Data were collected on operation type reported, country and continent of publication. North America and Europe were the leading contributors to global publications in BMS, producing 41.3 % (n = 4931) and 37.1 % (n = 4436) of publications respectively, with increasing publications from Asia. Roux-en-Y Gastric Bypass (RYGB) and Sleeve Gastrectomy (SG) were the most studied procedure types with number of publications continuing to increase over time. A plateau and downward trend was seen for Laparoscopic Adjustable Gastric Band (LAGB) publication from 2015 to 2019. An increase in emerging/experimental techniques over the past decade is observed.

Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contacts.

Mathematical models have been widely used during the ongoing SARS-CoV-2 pandemic for data interpretation, forecasting, and policy making. However, most models are based on officially reported case numbers, which depend on test availability and test strategies. The time dependence of these factors renders interpretation difficult and might even result in estimation biases. Here, we present a computational modelling framework that allows for the integration of reported case numbers with seroprevalence estimates obtained from representative population cohorts. To account for the time dependence of infection and testing rates, we embed flexible splines in an epidemiological model. The parameters of these splines are estimated, along with the other parameters, from the available data using a Bayesian approach. The application of this approach to the official case numbers reported for Munich (Germany) and the seroprevalence reported by the prospective COVID-19 Cohort Munich (KoCo19) provides first estimates for the time dependence of the under-reporting factor. Furthermore, we estimate how the effectiveness of non-pharmaceutical interventions and of the testing strategy evolves over time. Overall, our results show that the integration of temporally highly resolved and representative data is beneficial for accurate epidemiological analyses.

Aerosol-into-liquid capture and detection of atmospheric soluble metals across the gas-liquid interface using Janus-membrane electrodes.

The soluble fraction of atmospheric transition metals is particularly associated with health effects such as reactive oxygen species compared to total metals. However, direct measurements of the soluble fraction are restricted to sampling and detection units in sequence burdened with a compromise between time resolution and system bulkiness. Here, we propose the concept of aerosol-into-liquid capture and detection, which allowed one-step particle capture and detection via the Janus-membrane electrode at the gas-liquid interface, enabling active enrichment and enhanced mass transport of metal ions. The integrated aerodynamic/electrochemical system was capable of capturing airborne particles with a cutoff size down to 50 nm and detecting Pb(II) with a limit of detection of 95.7 ng. The proposed concept can pave the way for cost-effective and miniaturized systems, for the capture and detection of airborne soluble metals in air quality monitoring, especially for abrupt air pollution events with high airborne metal concentrations (e.g., wildfires and fireworks).

A long-term study on structural changes in calcium aluminate silicate hydrates.

Production of blended cements in which Portland cement is combined with supplementary cementitious materials (SCM) is an effective strategy for reducing the CO2 emissions during cement manufacturing and achieving sustainable concrete production. However, the high Al2O3 and SiO2 contents of SCM change the chemical composition of the main hydration product, calcium aluminate silicate hydrate (C-A-S-H). Herein, spectroscopic and structural data for C-A-S-H gels are reported in a large range of equilibration times from 3 months up to 2 years and Al/Si molar ratios from 0.001 to 0.2. The 27Al MAS NMR spectroscopy and thermogravimetric analysis indicate that in addition to the C-A-S-H phase, secondary phases such as strätlingite, katoite, Al(OH)3 and calcium aluminate hydrate are present at Al/Si ≥ 0.03 limiting the uptake of Al in C-A-S-H. More secondary phases are present at higher Al concentrations; their content decreases with equilibration time while more Al is taken up in the C-A-S-H phase. At low Al contents, Al concentrations decrease strongly with time indicating a slow equilibration, in contrast to high Al contents where a clear change in Al concentrations over time was not observed indicating that the equilibrium has been reached faster. The 27Al NMR studies show that tetrahedrally coordinated Al is incorporated in C-A-S-H and its amount increases with the amount of Al present in the solution. Supplementary Information: The online version contains supplementary material available at 10.1617/s11527-022-02080-x.

The Kinetics of Adsorption and Desorption of Selected Semivolatile Hydrocarbons and H2O Vapor on Two Mineral Dust Materials: A Molecular View.

A flowing gas experiment using a Knudsen flow reactor was performed on a series of seven semivolatile probe gases interacting with two often used mineral dust materials, namely, coarse Arizona test dust (ATD-C) and kaolinite. The semivolatile probe gases used were applinate (acetate ester), pipol (ethyl ester of 2-methylvaleric acid), benzylacetate (acetate ester of benzylalcohol), menthol (alcohol), toluene, limonene, and γ-terpinene (terpene hydrocarbon). Uptake experiments under molecular flow conditions resulted in absolute coverages and initial uptake coefficients γ0 based on the geometric sample surface. Integration of a simple Langmuir adsorption model afforded an analytical solution of the desorption kinetics of the semivolatile hydrocarbon upon spontaneous desorption from the solid mineral dust substrate at ambient temperature. Numerical fitting of the desorption rate resulted in adsorption (ka) and desorption (kd) rate constants, where 1/kd represented the surface residence time of the adsorbed semivolatile. The major conclusions are as follows: (a) Desorption at short ("prompt") and long time scales reveal stronger binding to ATD compared to kaolinite for all tested organic probe gases. (b) No difference in the desorption yields and kinetics was observed for H2O vapor on either substrate. (c) Prompt desorption at ambient temperature starts with the immediate detection of probe gases adsorbed on the vessel walls of the sample compartment, followed by the slower growth and decay of semivolatiles adsorbed on the substrate, leading to ka and kd. (d) Surface residence times at ambient temperatures for semivolatile organics vary from 50 to 40 000 s for toluene/ATD and menthol/ATD, respectively. For H2O vapor, 3000 s was measured on both kaolinite and ATD. (e) Large initial uptake coefficients γ0 in the range of 0.25-0.77 were measured for all semivolatiles except toluene, whose values were lower by roughly one order of magnitude. Rapid saturation was observed in all cases except for limonene, which appeared to undergo chemical reactions on both mineral substrates.

Effective removal of the rotifer Brachionus calyciflorus from a Chlorella vulgaris microalgal culture by homogeneous solar photo-Fenton at neutral pH.

In this study, a citrate-modified photo-Fenton process was successfully applied to decontaminate a Chlorella vulgaris microalgae culture spiked with the rotifer Brachionus calyciflorus (5 individuals mL-1). The applied treatment (1 mg L-1 Fe2+, 20 mg L-1 H2O2, 17.5 mg L-1 citric acid) had only moderate effects on viability and regrowth of the microalgae since, after a short post-treatment delay of a few days, they reached final cell densities similar to that obtained for microalgae cultures that were not spiked. The decontamination was effective as no regrowth of rotifers was observed in the microalgae cultures after treatment. The efficacy of the citrate-modified photo-Fenton treatment was also studied with a higher starting concentration of 20 rotifers mL-1 and was compared with a solar light/H2O2 treatment. Results show that both treatments had similar efficacies on the rotifer elimination, but that the citrate-modified photo-Fenton treatment had a lower negative impact on the regrowth of microalgae than the solar light/H2O2 treatment. However, when microalgae cultures were spiked with 20 rotifers mL-1, rotifers were only partially inactivated and post-treatment regrowth occurred, which highlights the importance to apply the photo-Fenton process at an early stage of a contamination to achieve full rotifer elimination. In any case, a contamination with 5 rotifers mL-1 is already a significant threat as numbers above 1000 rotifers mL-1 were reached after 14 days and caused the microalgae culture to fail. Overall, our treatment suggests that the citrate-modified solar photo-Fenton process is an environmentally friendly solution to support the maintenance of contaminant-free microalgal cultures.

Nuclear Magnetic Resonance Spectroscopy Metabolomics in Idiopathic Intracranial Hypertension to Identify Markers of Disease and Headache.

BACKGROUND AND OBJECTIVE: We evaluated the metabolomic profile in CSF, serum and urine of participants with idiopathic intracranial hypertension (IIH) compared to controls and measured changes in metabolism associated with clinical markers of disease activity and treatment. METHODS: A case-control study compared women aged 18-55 years with active IIH (Friedman diagnostic criteria), to a sex, age and body mass index matched control group. IIH participants were identified from neurology and ophthalmology clinics from National Health Service hospitals and underwent a prospective intervention to induce disease remission through weight loss with re-evaluation at 12 months. Clinical assessments included lumbar puncture, headache, papilledema and visual measurements. Spectra of CSF, serum and urine metabolites were acquired utilizing proton nuclear magnetic resonance spectroscopy. RESULTS: Urea was lower in IIH (CSF; controls median ±IQR 0.196 ±0.008, IIH 0.058 ±0.059, p<0.001, urine; controls 5971.370 ±3021.831, IIH 4691.363 ±1955.774, p=0.009), correlated with ICP (urine p=0.019) and headache severity (CSF p=0.031) and increased by 12 months (CSF 12 months; 0.175 ±0.043, p=0.004, urine; 5210.874 ±1825.302, p=0.043). The lactate:pyruvate ratio was increased compared to controls (CSF; controls 49.739 ±19.523, IIH 113.114 ±117.298, p=0.023, serum; controls 38.187 ±13.392, IIH 54.547 ±18.471, p=0.004) and decreased at 12 months (CSF; 113.114 ±117.298, p<0.001). Baseline acetate was higher in IIH (CSF; controls 0.128 ±0.041, IIH 0.192 ±0.151, p=0.008), correlated with headache severity (p = 0.030) and headache disability (p = 0.003) and was reduced at 12 months (0.160 ±0.060, p = 0.007). Ketones 3-hydroxybutyrate and acetoacetate were altered in CSF at baseline in IIH (3-hydroxybutyrate; controls 0.074 ±0.063, IIH 0.049 ±0.055, p = 0.019, acetoacetate; controls 0.013 ±0.007, IIH 0.017 ±0.010, p = 0.013) and normalized at 12 months (0.112 ±0.114, p = 0.019, 0.029 ±0.017, p = 0.015 respectively). DISCUSSION: We observed metabolic disturbances that are evident in CSF, serum and urine of IIH participants, suggesting global metabolic dysregulation. Altered ketone body metabolites normalized following therapeutic weight loss. CSF:serum urea ratio was altered which may influence ICP dynamics and headache. Elevated CSF acetate, known to stimulate trigeminal sensitization, was associated with headache morbidity. These alterations of metabolic pathways specific to IIH provide biological insight and warrants mechanistic evaluation.

Handling of the Covid-19 Pandemic and Its Effects on Bariatric Surgical Practice: Analysis of GENEVA Study Database.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic led to a worldwide suspension of bariatric and metabolic surgery (BMS) services. The current study analyses data on patterns of service delivery, recovery of practices, and protective measures taken during the COVID-19 pandemic by bariatric teams. MATERIALS AND METHODS: The current study is a subset analysis of the GENEVA study which was an international cohort study between 01/05/2020 and 31/10/2020. Data were specifically analysed regarding the timing of BMS suspension, patterns of service recovery, and precautionary measures deployed. RESULTS: A total of 527 surgeons from 439 hospitals in 64 countries submitted data regarding their practices and handling of the pandemic. Smaller hospitals (with less than 200 beds) were able to restart BMS programmes more rapidly (time to BMS restart 60.8 ± 38.9 days) than larger institutions (over 2000 beds) (81.3 ± 30.5 days) (p = 0.032). There was a significant difference in the time interval between cessation/reduction and restart of bariatric services between government-funded practices (97.1 ± 76.2 days), combination practices (84.4 ± 47.9 days), and private practices (58.5 ± 38.3 days) (p < 0.001). Precautionary measures adopted included patient segregation, utilisation of personal protective equipment, and preoperative testing. Following service recovery, 40% of the surgeons operated with a reduced capacity. Twenty-two percent gave priority to long waiters, 15.4% gave priority to uncontrolled diabetics, and 7.6% prioritised patients requiring organ transplantation. CONCLUSION: This study provides global, real-world data regarding the recovery of BMS services following the COVID-19 pandemic.