Correction: The BioRef Infrastructure, a Framework for Real-Time, Federated, Privacy-Preserving, and Personalized Reference Intervals: Design, Development, and Application.

[This corrects the article DOI: 10.2196/47254.].

The BioRef Infrastructure, a Framework for Real-Time, Federated, Privacy-Preserving, and Personalized Reference Intervals: Design, Development, and Application.

BACKGROUND: Reference intervals (RIs) for patient test results are in standard use across many medical disciplines, allowing physicians to identify measurements indicating potentially pathological states with relative ease. The process of inferring cohort-specific RIs is, however, often ignored because of the high costs and cumbersome efforts associated with it. Sophisticated analysis tools are required to automatically infer relevant and locally specific RIs directly from routine laboratory data. These tools would effectively connect clinical laboratory databases to physicians and provide personalized target ranges for the respective cohort population. OBJECTIVE: This study aims to describe the BioRef infrastructure, a multicentric governance and IT framework for the estimation and assessment of patient group-specific RIs from routine clinical laboratory data using an innovative decentralized data-sharing approach and a sophisticated, clinically oriented graphical user interface for data analysis. METHODS: A common governance agreement and interoperability standards have been established, allowing the harmonization of multidimensional laboratory measurements from multiple clinical databases into a unified "big data" resource. International coding systems, such as the International Classification of Diseases, Tenth Revision (ICD-10); unique identifiers for medical devices from the Global Unique Device Identification Database; type identifiers from the Global Medical Device Nomenclature; and a universal transfer logic, such as the Resource Description Framework (RDF), are used to align the routine laboratory data of each data provider for use within the BioRef framework. With a decentralized data-sharing approach, the BioRef data can be evaluated by end users from each cohort site following a strict "no copy, no move" principle, that is, only data aggregates for the intercohort analysis of target ranges are exchanged. RESULTS: The TI4Health distributed and secure analytics system was used to implement the proposed federated and privacy-preserving approach and comply with the limitations applied to sensitive patient data. Under the BioRef interoperability consensus, clinical partners enable the computation of RIs via the TI4Health graphical user interface for query without exposing the underlying raw data. The interface was developed for use by physicians and clinical laboratory specialists and allows intuitive and interactive data stratification by patient factors (age, sex, and personal medical history) as well as laboratory analysis determinants (device, analyzer, and test kit identifier). This consolidated effort enables the creation of extremely detailed and patient group-specific queries, allowing the generation of individualized, covariate-adjusted RIs on the fly. CONCLUSIONS: With the BioRef-TI4Health infrastructure, a framework for clinical physicians and researchers to define precise RIs immediately in a convenient, privacy-preserving, and reproducible manner has been implemented, promoting a vital part of practicing precision medicine while streamlining compliance and avoiding transfers of raw patient data. This new approach can provide a crucial update on RIs and improve patient care for personalized medicine.

Computational Evidence for Laboratory Diagnostic Pathways: Extracting Predictive Analytes for Myocardial Ischemia from Routine Hospital Data.

Background: Laboratory parameters are critical parts of many diagnostic pathways, mortality scores, patient follow-ups, and overall patient care, and should therefore have underlying standardized, evidence-based recommendations. Currently, laboratory parameters and their significance are treated differently depending on expert opinions, clinical environment, and varying hospital guidelines. In our study, we aimed to demonstrate the capability of a set of algorithms to identify predictive analytes for a specific diagnosis. As an illustration of our proposed methodology, we examined the analytes associated with myocardial ischemia; it was a well-researched diagnosis and provides a substrate for comparison. We intend to present a toolset that will boost the evolution of evidence-based laboratory diagnostics and, therefore, improve patient care. Methods: The data we used consisted of preexisting, anonymized recordings from the emergency ward involving all patient cases with a measured value for troponin T. We used multiple imputation technique, orthogonal data augmentation, and Bayesian Model Averaging to create predictive models for myocardial ischemia. Each model incorporated different analytes as cofactors. In examining these models further, we could then conclude the predictive importance of each analyte in question. Results: The used algorithms extracted troponin T as a highly predictive analyte for myocardial ischemia. As this is a known relationship, we saw the predictive importance of troponin T as a proof of concept, suggesting a functioning method. Additionally, we could demonstrate the algorithm's capabilities to extract known risk factors of myocardial ischemia from the data. Conclusion: In this pilot study, we chose an assembly of algorithms to analyze the value of analytes in predicting myocardial ischemia. By providing reliable correlations between the analytes and the diagnosis of myocardial ischemia, we demonstrated the possibilities to create unbiased computational-based guidelines for laboratory diagnostics by using computational power in today's era of digitalization.

Collaborative Challenges of Multi-Cohort Projects in Pharmacogenetics-Why Time Is Essential for Meaningful Collaborations.

Multi-cohort projects in medicine provide an opportunity to investigate scientific questions beyond the boundaries of a single institution and endeavor to increase the sample size for obtaining more reliable results. However, the complications of these kinds of collaborations arise during management, with many administrative hurdles. Hands-on approaches and lessons learned from previous collaborations provide solutions for optimized collaboration models. Here, we use our experience in running PGX-link, a Swiss multi-cohort project, to show the strategy we used to tackle different challenges from project setup to obtaining the relevant permits, including ethics approval. We set PGX-link in an international context because our struggles were similar to those encountered during the SYNCHROS (SYNergies for Cohorts in Health: integrating the ROle of all Stakeholders) project. We provide ad hoc solutions for cohorts, general project management strategies, and suggestions for unified protocols between cohorts that would ease current management hurdles. Project managers are not necessarily familiar with medical projects, and even if they are, they are not aware of the intricacies behind decision-making and consequently, of the time needed to set up multi-cohort collaborations. This paper is meant to be a brief overview of what we experienced with our multi-cohort project and provides the necessary practices for future managers.

Big Data in Laboratory Medicine-FAIR Quality for AI?

Laboratory medicine is a digital science. Every large hospital produces a wealth of data each day-from simple numerical results from, e.g., sodium measurements to highly complex output of "-omics" analyses, as well as quality control results and metadata. Processing, connecting, storing, and ordering extensive parts of these individual data requires Big Data techniques. Whereas novel technologies such as artificial intelligence and machine learning have exciting application for the augmentation of laboratory medicine, the Big Data concept remains fundamental for any sophisticated data analysis in large databases. To make laboratory medicine data optimally usable for clinical and research purposes, they need to be FAIR: findable, accessible, interoperable, and reusable. This can be achieved, for example, by automated recording, connection of devices, efficient ETL (Extract, Transform, Load) processes, careful data governance, and modern data security solutions. Enriched with clinical data, laboratory medicine data allow a gain in pathophysiological insights, can improve patient care, or can be used to develop reference intervals for diagnostic purposes. Nevertheless, Big Data in laboratory medicine do not come without challenges: the growing number of analyses and data derived from them is a demanding task to be taken care of. Laboratory medicine experts are and will be needed to drive this development, take an active role in the ongoing digitalization, and provide guidance for their clinical colleagues engaging with the laboratory data in research.

Machine Learning Prediction of Hypoglycemia and Hyperglycemia From Electronic Health Records: Algorithm Development and Validation.

BACKGROUND: Acute blood glucose (BG) decompensations (hypoglycemia and hyperglycemia) represent a frequent and significant risk for inpatients and adversely affect patient outcomes and safety. The increasing need for BG management in inpatients poses a high demand on clinical staff and health care systems in addition. OBJECTIVE: This study aimed to generate a broadly applicable multiclass classification model for predicting BG decompensation events from patients' electronic health records to indicate where adjustments in patient monitoring and therapeutic interventions are required. This should allow for taking proactive measures before BG levels are derailed. METHODS: A retrospective cohort study was conducted on patients who were hospitalized at a tertiary hospital in Bern, Switzerland. Using patient details and routine data from electronic health records, a multiclass prediction model for BG decompensation events (<3.9 mmol/L [hypoglycemia] or >10, >13.9, or >16.7 mmol/L [representing different degrees of hyperglycemia]) was generated based on a second-level ensemble of gradient-boosted binary trees. RESULTS: A total of 63,579 hospital admissions of 38,250 patients were included in this study. The multiclass prediction model reached specificities of 93.7%, 98.9%, and 93.9% and sensitivities of 67.1%, 59%, and 63.6% for the main categories of interest, which were nondecompensated cases, hypoglycemia, or hyperglycemia, respectively. The median prediction horizon was 7 hours and 4 hours for hypoglycemia and hyperglycemia, respectively. CONCLUSIONS: Electronic health records have the potential to reliably predict all types of BG decompensation. Readily available patient details and routine laboratory data can support the decisions for proactive interventions and thus help to reduce the detrimental health effects of hypoglycemia and hyperglycemia.

Real-world Health Data and Precision for the Diagnosis of Acute Kidney Injury, Acute-on-Chronic Kidney Disease, and Chronic Kidney Disease: Observational Study.

BACKGROUND: The criteria for the diagnosis of kidney disease outlined in the Kidney Disease: Improving Global Outcomes guidelines are based on a patient's current, historical, and baseline data. The diagnosis of acute kidney injury, chronic kidney disease, and acute-on-chronic kidney disease requires previous measurements of creatinine, back-calculation, and the interpretation of several laboratory values over a certain period. Diagnoses may be hindered by unclear definitions of the individual creatinine baseline and rough ranges of normal values that are set without adjusting for age, ethnicity, comorbidities, and treatment. The classification of correct diagnoses and sufficient staging improves coding, data quality, reimbursement, the choice of therapeutic approach, and a patient's outcome. OBJECTIVE: In this study, we aim to apply a data-driven approach to assign diagnoses of acute, chronic, and acute-on-chronic kidney diseases with the help of a complex rule engine. METHODS: Real-time and retrospective data from the hospital's clinical data warehouse of inpatient and outpatient cases treated between 2014 and 2019 were used. Delta serum creatinine, baseline values, and admission and discharge data were analyzed. A Kidney Disease: Improving Global Outcomes-based SQL algorithm applied specific diagnosis-based International Classification of Diseases (ICD) codes to inpatient stays. Text mining on discharge documentation was also conducted to measure the effects on diagnosis. RESULTS: We show that this approach yielded an increased number of diagnoses (4491 cases in 2014 vs 11,124 cases of ICD-coded kidney disease and injury in 2019) and higher precision in documentation and coding. The percentage of unspecific ICD N19-coded diagnoses of N19 codes generated dropped from 19.71% (1544/7833) in 2016 to 4.38% (416/9501) in 2019. The percentage of specific ICD N18-coded diagnoses of N19 codes generated increased from 50.1% (3924/7833) in 2016 to 62.04% (5894/9501) in 2019. CONCLUSIONS: Our data-driven method supports the process and reliability of diagnosis and staging and improves the quality of documentation and data. Measuring patient outcomes will be the next step in this project.

Volumetric Food Quantification Using Computer Vision on a Depth-Sensing Smartphone: Preclinical Study.

BACKGROUND: Quantification of dietary intake is key to the prevention and management of numerous metabolic disorders. Conventional approaches are challenging, laborious, and lack accuracy. The recent advent of depth-sensing smartphones in conjunction with computer vision could facilitate reliable quantification of food intake. OBJECTIVE: The objective of this study was to evaluate the accuracy of a novel smartphone app combining depth-sensing hardware with computer vision to quantify meal macronutrient content using volumetry. METHODS: The app ran on a smartphone with a built-in depth sensor applying structured light (iPhone X). The app estimated weight, macronutrient (carbohydrate, protein, fat), and energy content of 48 randomly chosen meals (breakfasts, cooked meals, snacks) encompassing 128 food items. The reference weight was generated by weighing individual food items using a precision scale. The study endpoints were (1) error of estimated meal weight, (2) error of estimated meal macronutrient content and energy content, (3) segmentation performance, and (4) processing time. RESULTS: In both absolute and relative terms, the mean (SD) absolute errors of the app's estimates were 35.1 g (42.8 g; relative absolute error: 14.0% [12.2%]) for weight; 5.5 g (5.1 g; relative absolute error: 14.8% [10.9%]) for carbohydrate content; 1.3 g (1.7 g; relative absolute error: 12.3% [12.8%]) for fat content; 2.4 g (5.6 g; relative absolute error: 13.0% [13.8%]) for protein content; and 41.2 kcal (42.5 kcal; relative absolute error: 12.7% [10.8%]) for energy content. Although estimation accuracy was not affected by the viewing angle, the type of meal mattered, with slightly worse performance for cooked meals than for breakfasts and snacks. Segmentation adjustment was required for 7 of the 128 items. Mean (SD) processing time across all meals was 22.9 seconds (8.6 seconds). CONCLUSIONS: This study evaluated the accuracy of a novel smartphone app with an integrated depth-sensing camera and found highly accurate volume estimation across a broad range of food items. In addition, the system demonstrated high segmentation performance and low processing time, highlighting its usability.

Parathyroid Hormone and Plasma Phosphate Are Predictors of Soluble α-Klotho Levels in Adults of European Descent.

CONTEXT: α-klotho is an integral membrane protein that serves as a coreceptor for fibroblast growth factor 23 (FGF23) in conjunction with cognate fibroblast growth factor receptors. Proteolytic cleavage sheds the ectodomain of α-klotho (soluble α-klotho) as an endocrine substance into blood, urine, and cerebrospinal fluid. OBJECTIVE: To study the relationship of soluble α-klotho to mineral metabolism in the general population with mainly preserved kidney function. DESIGN: Cross-sectional analysis of the associations between soluble α-klotho with laboratory markers of markers of mineral metabolism in a population-based cohort. SETTING: Three centers in Switzerland including 1128 participants. MEASURES: Soluble full-length α-klotho levels by a specific immunoassay and markers of mineral metabolism. RESULTS: The median serum level of soluble α-klotho was 15.0 pmol/L. Multivariable analyses using α-klotho as the outcome variable revealed a sex-by-PTH interaction: In men, PTH was positively associated with α-klotho levels, whereas this association was negative in women. Plasma phosphate associated with soluble α-klotho levels in an age-dependent manner, changing from a positive association in young adults gradually to a negative association in the elderly. The decline of 1,25 (OH)2 vitamin D3 levels in parallel to the gradual impairment of kidney function was greatly attenuated in the setting of high circulating soluble α-klotho levels. CONCLUSIONS: Soluble α-klotho level is associated with plasma phosphate in an age-dependent manner and with PTH in a sex-dependent manner. Furthermore, our data reveal soluble α-klotho as a modulator of 1,25 (OH)2 vitamin D3 levels in individuals with preserved renal function.

Fibroblast growth factor 23 and markers of mineral metabolism in individuals with preserved renal function.

Fibroblast growth factor 23 (FGF23) is a bone-derived hormone that regulates phosphate homeostasis. Circulating FGF23 is elevated in chronic kidney disease (CKD) and independently associated with poor renal and cardiovascular outcomes and mortality. Because the study of FGF23 in individuals with normal renal function has received little attention, we examined in a large, population-based study of 1128 participants the associations of FGF23 with markers of mineral metabolism and renal function. The median estimated glomerular filtration rate (eGFR) of the cohort was 105 ml/min per 1.73 m(2), and the median plasma FGF23 was 78.5 RU/ml. FGF23 increased and plasma 1,25-dihydroxyvitamin D3 decreased significantly below an eGFR threshold of 102 and 99 ml/min per 1.73 m(2), respectively. In contrast, plasma parathyroid hormone increased continuously with decreasing eGFR and was first significantly elevated at an eGFR of 126 ml/min per 1.73 m(2). On multivariable analysis adjusting for sex, age, body mass index, and GFR, FGF23 was negatively associated with 1,25-dihydroxyvitamin D3, and urinary absolute and fractional calcium excretion but not with serum calcium or parathyroid hormone. We found a positive association of FGF23 with plasma phosphate, but no association with urinary absolute or fractional phosphate excretion and, unexpectedly, a positive association with tubular maximum phosphate reabsorption/GFR. Thus, in the absence of CKD, parathyroid hormone increases earlier than FGF23 when the eGFR decreases. The increase in FGF23 occurs at a higher eGFR threshold than previously reported and is closely associated with a decrease in 1,25-dihydroxyvitamin D3. We speculate that the main demonstrable effect of FGF23 in the setting of preserved renal function is suppression of 1,25-dihydroxyvitamin D3 rather than stimulation of renal phosphate excretion.

Age is not associated with intracranial haemorrhage in patients with mild traumatic brain injury and oral anticoagulation.

BACKGROUND: Patients admitted to emergency departments with traumatic brain injury (TBI) are commonly being treated with oral anticoagulants. In contrast to patients without anticoagulant medication, no guidelines, scores or recommendations exist for the management of mild traumatic brain injury in these patients. We therefore tested whether age as one of the high risk factors of the Canadian head CT rule is applicable to a patient population on oral anticoagulants. METHODS: This cross-sectional analysis included all patients with mild TBI and concomitant oral anticoagulant therapy admitted to the Emergency Department, Inselspital Bern, Switzerland, from November 2009 to October 2014 (n = 200). Using a logistic regression model, two groups of patients with mild TBI on oral anticoagulant therapy were compared - those with and those without intracranial haemorrhage. RESULTS: There was no significant difference in age between the patient groups with (n = 86) and without (n = 114) intracranial haemorrhage (p = 0.078). In univariate logistic regression, GCS (OR = 0.419 (0.258; 0.680)) and thromboembolic event as reason for anticoagulant therapy (OR = 0.486 (0.257; 0.918)) were significantly associated with intracranial haemorrhage in patients with mild TBI and anticoagulation (all p < 0.05). However, there was no association with age (p = 0.078, OR = 1.024 (0.997; 1.051)), the type of accident or additional medication with acetylsalicylic acid or clopidogrel ((both p > 0.05; 0.552 (0.139; 2.202) and 0.256 (0.029; 2.237), respectively). CONCLUSION: Our study found no association between age and intracranial bleeding. Therefore, until further risk factors are identified, diagnostic imaging with CCT remains necessary for mild TBI patients on oral anticoagulation of all ages, especially those with therapeutic anticoagulation because of thromboembolic events.

S-100 B Concentrations Are a Predictor of Decreased Survival in Patients with Major Trauma, Independently of Head Injury.

BACKGROUND: Major trauma remains one of the principle causes of disability and death throughout the world. There is currently no satisfactory risk assessment to predict mortality in patients with major trauma. The aim of our study is to examine whether S-100 B protein concentrations correlate with injury severity and survival in patients with major trauma, with special emphasis on patients without head injury. METHODS: Our retrospective data analysis comprised adult patients admitted to our emergency department between 1.12. 2008 and 31.12 2010 with a suspected major trauma. S-100 B concentrations were routinely assessed in major trauma patients. RESULTS: A total of 27.7% (378) of all patients had major trauma. The median ISS was 24.6 (SD 8.4); 16.6% (63/378) of the patients died. S-100 B concentrations correlated overall with the ISS (p<0.0001). Patients who died had significantly higher S-100 B concentrations than survivors (8.2 µg/l versus 2.2 µg/l, p<0.0001). Polytraumatised patients with and without head trauma did not differ significantly with respect to S-100 B concentration (3.2 µg/l (SD 5.3) versus 2.9 µg/l (SD 3.8), respectively, p = 0.63) or with respect to Injury Severity Score (24.8 (SD 8.6) versus 24.2 (SD 8.1), respectively, p = 0.56). S-100 B concentrations correlated negatively with survival (p<0.0001) in all patients and in both subgroups (p = 0.001 and p = 0.006, respectively). CONCLUSIONS: S-100 concentrations on admission correlate positively with greater injury severity and decreased survival in major trauma patients, independently of the presence of a head injury. S-100 B protein levels at admission in patients with major trauma may therefore be used to assess outcome in all polytraumatised patients. These measurements should be subject to further evaluation.

Use of Diuretics is not associated with mortality in patients admitted to the emergency department: results from a cross-sectional study.

BACKGROUND: Patients with diuretic therapy are at risk for drug-induced adverse reactions. It is unknown if presence of diuretic therapy at hospital emergency room admission is associated with mortality. METHODS: In this cross sectional analysis, all emergency room patients 2010 and 2011 at the Inselspital Bern, Switzerland were included. A multivariable logistic regression model was performed to assess the association between pre-existing diuretic medication and 28 day mortality. RESULTS: Twenty-two thousand two hundred thirty-nine subjects were included in the analysis. A total of 8.5%, 2.5%, and 0.4% of patients used one, two, or three or more diuretics. In univariate analysis spironolactone, torasemide and chlortalidone use were associated with 28 day mortality (all p < 0.05). In a multivariate cox regression model no association with mortality was detectable (p > 0.05). No difference existed between patients with or without diuretic therapy (P > 0.05). Age and creatinine were independent risk factors for mortaliy (both p < 0.05). CONCLUSION: Use of diuretics is not associated with mortality in an unselected cohort of patients presenting in an emergency room.

Computed exercise plasma lactate concentrations: A conversion formula.

OBJECTIVES: Blood lactate measurements are common as a marker of skeletal muscle metabolism in sport medicine. Due to the close equilibrium between the extracellular and intramyocellular space, plasma lactate is a more accurate estimate of muscle lactate. However, whole blood-based lactate measurements are more convenient in field use. The purpose of this investigation was therefore (1) to establish a plasma-converting lactate formula for field use, and (2) to validate the computed plasma lactate levels by comparison to a laboratory standard method. DESIGN AND METHODS: A total of 91 venous samples were taken from 6 individuals with type 1 diabetes during resting and exercise conditions and assessed for whole blood and plasma lactate using the YSI 2300 analyzer. A linear model was applied to establish a formula for converting whole blood lactate to plasma lactate. The validity of computed plasma lactate values was assessed by comparison to a laboratory standard method. RESULTS: Whole blood YSI lactate could be converted to plasma YSI values (slope 1.66, intercept 0.12) for samples with normal hematocrit. Computed plasma levels compared to values determined by the laboratory standard method using Passing-Bablok regression yielded a slope of 1.03 (95%CI:0.99:1.08) with an intercept of -0.11 (95%CI:-0.18:-0.06). CONCLUSIONS: Whole blood YSI lactate values can be reliably converted into plasma values which are in line with laboratory determined plasma measurements.

Hyperphosphatemia Is an Independent Risk Factor for Mortality in Critically Ill Patients: Results from a Cross-Sectional Study.

BACKGROUND: Phosphate imbalances or disorders have a high risk of morbidity and mortality in patients with chronic kidney disease. It is unknown if this finding extends to mortality in patients presenting at an emergency room with or without normal kidney function. METHODS AND PATIENTS: This cross sectional analysis included all emergency room patients between 2010 and 2011 at the Inselspital Bern, Switzerland. A multivariable cox regression model was applied to assess the association between phosphate levels and in-hospital mortality up to 28 days. RESULTS: 22,239 subjects were screened for the study. Plasma phosphate concentrations were measured in 2,390 patients on hospital admission and were included in the analysis. 3.5% of the 480 patients with hypophosphatemia and 10.7% of the 215 patients with hyperphosphatemia died. In univariate analysis, phosphate levels were associated with mortality, age, diuretic therapy and kidney function (all p<0.001). In a multivariate Cox regression model, hyperphosphatemia (OR 3.29, p<0.001) was a strong independent risk factor for mortality. Hypophosphatemia was not associated with mortality (p>0.05). CONCLUSION: Hyperphosphatemia is associated with 28-day in-hospital mortality in an unselected cohort of patients presenting in an emergency room.

Calcium Disorders in the Emergency Department: Independent Risk Factors for Mortality.

BACKGROUND: Calcium disorders are common in both intensive care units and in patients with chronic kidney disease and are associated with increased morbidity and mortality. It is unknown whether calcium abnormalities in unselected emergency department admissions have an impact on in-hospital mortality. METHODS: This cross-sectional analysis included all admissions to the Emergency Department at the Inselspital Bern, Switzerland from 2010 to 2011. For hyper- and hypocalcaemic patients with a Mann-Whitney U-test, the differences between subgroups divided by age, length of hospital stay, creatinine, sodium, chloride, phosphate, potassium and magnesium were compared. Associations between calcium disorders and 28-day in-hospital mortality were assessed using the Cox proportional hazard regression model. RESULTS: 8,270 patients with calcium measurements were included in our study. Overall 264 (3.2%) patients died. 150 patients (6.13%) with hypocalcaemia and 7 patients with hypercalcaemia (6.19%) died, in contrast to 104 normocalcaemic patients (1.82%). In univariate analysis, calcium serum levels were associated with sex, mortality and pre-existing diuretic therapy (all p<0.05). In multivariate Cox regression analysis, hypocalcaemia and hypercalcaemia were independent risk factors for mortality (HR 2.00 and HR 1.88, respectively; both p<0.01). CONCLUSION: Both hypocalcaemia and hypercalcaemia are associated with increased 28-day in-hospital mortality in unselected emergency department admissions.

Primary Hyperventilation in the Emergency Department: A First Overview.

BACKGROUND: Primary hyperventilation is defined as a state of alveolar ventilation in excess of metabolic requirements, leading to decreased arterial partial pressure of carbon dioxide. The primary aim of this study was to characterise patients diagnosed with primary hyperventilation in the ED. METHODS: Our retrospective cohort study comprised adult (≥16 years) patients admitted to our ED between 1 January 2006 and 31 December 2012 with the primary diagnosis of primary (=psychogenic) hyperventilation. RESULTS: A total of 616 patients were eligible for study. Participants were predominantely female (341 [55.4%] female versus 275 [44.6%] male respectively, p <0.01). The mean age was 36.5 years (SD 15.52, range 16-85). Patients in their twenties were the most common age group (181, 29.4%), followed by patients in their thirties (121, 19.6%). Most patients presented at out-of-office hours (331 [53.7%]. The most common symptom was fear (586, 95.1%), followed by paraesthesia (379, 61.5%) and dizziness (306, 49.7%). Almost a third (187, 30.4%) of our patients had previously experienced an episode of hyperventilation and half (311, 50.5%) of patients had a psychiatric co-morbidity. CONCLUSION: Hyperventilation is a diagnostic chimera with a wide spectrum of symptoms. Patients predominantly are of young age, female sex and often have psychiatric comorbidities. The severity of symptoms accompanied with primary hyperventilation most often needs further work-up to rule out other diagnosis in a mostly young population. In the future, further prospective multicentre studies are needed to evaluate and establish clear diagnostic criteria for primary hyperventilation and possible screening instruments.

Hypermagnesemia is a strong independent risk factor for mortality in critically ill patients: results from a cross-sectional study.

BACKGROUND: Patients with electrolyte imbalances or disorders have a high risk of mortality. It is unknown if this finding from sodium or potassium disorders extends to alterations of magnesium levels. METHODS AND PATIENTS: In this cross-sectional analysis, all emergency room patients between 2010 and 2011 at the Inselspital Bern, Switzerland, were included. A multivariable logistic regression model was performed to assess the association between magnesium levels and in-hospital mortality up to 28days. RESULTS: A total of 22,239 subjects were screened for the study. A total of 5339 patients had plasma magnesium concentrations measured at hospital admission and were included into the analysis. A total of 6.3% of the 352 patients with hypomagnesemia and 36.9% of the 151 patients with hypermagnesemia died. In a multivariate Cox regression model hypermagnesemia (HR 11.6, p<0.001) was a strong independent risk factor for mortality. In these patients diuretic therapy revealed to be protective (HR 0.5, p=0.007). Hypomagnesemia was not associated with mortality (p>0.05). Age was an independent risk factor for mortality (both p<0.001). CONCLUSION: The study does demonstrate a possible association between hypermagnesemia measured upon admission in the emergency department, and early in-hospital mortality.

Hypoglycemia is associated with increased mortality in patients with acute decompensated liver cirrhosis.

PRINCIPALS: The liver plays an important role in glucose metabolism, in terms of glucolysis and gluconeogenesis. Several studies have shown that hyperglycemia in patients with liver cirrhosis is associated with progression of the liver disease and increased mortality. However, no study has ever targeted the influence of hypoglycemia. The aim of this study was to assess the association of glucose disturbances with outcome in patients presenting to the emergency department with acute decompensated liver cirrhosis. METHODS: Our retrospective data analysis comprised adult (≥ 16 years) patients admitted to our emergency department between January 1, 2002, and December 31, 2012, with the primary diagnosis of decompensated liver cirrhosis. RESULTS: A total of 312 patients were eligible for study inclusion. Two hundred thirty-one (74.0%) patients were male; 81 (26.0%) were female. The median age was 57 years (range, 51-65 years). Overall, 89 (28.5%) of our patients had acute glucose disturbances; 49 (15.7%) of our patients were hypoglycemic and 40 (12.8%) were hyperglycemic. Patients with hypoglycemia were significantly more often admitted to the intensive care unit than hyperglycemic patients (20.4% vs 10.8%, P < .015) or than normoglycemic patients (20.4% vs 10.3%, P < .011), and they significantly more often died in the hospital (28.6% hypoglycemic vs 7.5% hyperglycemic, P < .024; 28.6% hypoglycemic vs 10.3% normoglycemic P < .049). Survival analysis showed a significantly lower estimated survival for hypoglycemic patients (36 days) than for normoglycemic patients (54 days) or hyperglycemic patients (45 days; hypoglycemic vs hyperglycemic, P < .019; hypoglycemic vs normoglycemic, P < .007; hyperglycemic vs normoglycemic, P < .477). CONCLUSION: Hypoglycemia is associated with increased mortality in patients with acute decompensated liver cirrhosis. It is not yet clear whether hypoglycemia is jointly responsible for the increased short-term mortality of patients with acute decompensated liver cirrhosis or is only a consequence of the severity of the disease or the complications.