Trends in antidiabetes medication use among hospitalised patients with type 2 diabetes: a retrospective single-centre cohort study.

OBJECTIVES: Novel antidiabetes medications with proven cardiovascular or renal benefit, such as sodium-glucose cotransporter-2 inhibitors (SGLT-2i) and glucagon-like peptide 1 receptor agonists (GLP-1 RA), have been introduced to the market. This study explored the 4-year trends of antidiabetes medication use among medical hospitalisations with type 2 diabetes (T2D). DESIGN: Retrospective cohort study. SETTING: Tertiary care hospital in Switzerland. PARTICIPANTS: 4695 adult hospitalisations with T2D and prevalent or incident use of one of the following antidiabetes medications (metformin, dipeptidyl peptidase-4 inhibitors (DPP-4i), sulfonylureas, GLP-1 RA, SGLT-2i, short-acting insulin or long-acting insulin), identified using electronic health record data. Quarterly trends in use of antidiabetes medications were plotted overall and stratified by cardiovascular disease (CVD) and chronic kidney disease (CKD). RESULTS: We observed a stable trend in the proportion of hospitalisations with T2D who received any antidiabetes medication (from 77.6% during 2019 to 78% in 2022; p for trend=0.97). In prevalent users, the largest increase in use was found for SGLT-2i (from 7.4% in 2019 to 21.8% in 2022; p for trend <0.01), the strongest decrease was observed for sulfonylureas (from 11.4% in 2019 to 7.2% in 2022; p for trend <0.01). Among incident users, SGLT-2i were the most frequently newly prescribed antidiabetes medication with an increase from 26% in 2019 to 56.1% in 2022 (p for trend <0.01). Between hospital admission and discharge, SGLT-2i also accounted for the largest increase in prescriptions (+5.1%; p<0.01). CONCLUSIONS: These real-world data from 2019 to 2022 demonstrate a significant shift in antidiabetes medications within the in-hospital setting, with decreased use of sulfonylureas and increased prescriptions of SGLT-2i, especially in hospitalisations with CVD or CKD. This trend aligns with international guidelines and indicates swift adaptation by healthcare providers, signalling a move towards more effective diabetes management.

BOLD: Blood-gas and Oximetry Linked Dataset.

Pulse oximeters measure peripheral arterial oxygen saturation (SpO2) noninvasively, while the gold standard (SaO2) involves arterial blood gas measurement. There are known racial and ethnic disparities in their performance. BOLD is a dataset that aims to underscore the importance of addressing biases in pulse oximetry accuracy, which disproportionately affect darker-skinned patients. The dataset was created by harmonizing three Electronic Health Record databases (MIMIC-III, MIMIC-IV, eICU-CRD) comprising Intensive Care Unit stays of US patients. Paired SpO2 and SaO2 measurements were time-aligned and combined with various other sociodemographic and parameters to provide a detailed representation of each patient. BOLD includes 49,099 paired measurements, within a 5-minute window and with oxygen saturation levels between 70-100%. Minority racial and ethnic groups account for ~25% of the data - a proportion seldom achieved in previous studies. The codebase is publicly available. Given the prevalent use of pulse oximeters in the hospital and at home, we hope that BOLD will be leveraged to develop debiasing algorithms that can result in more equitable healthcare solutions.

Variation in monitoring: Glucose measurement in the ICU as a case study to preempt spurious correlations.

OBJECTIVE: Health inequities can be influenced by demographic factors such as race and ethnicity, proficiency in English, and biological sex. Disparities may manifest as differential likelihood of testing which correlates directly with the likelihood of an intervention to address an abnormal finding. Our retrospective observational study evaluated the presence of variation in glucose measurements in the Intensive Care Unit (ICU). METHODS: Using the MIMIC-IV database (2008-2019), a single-center, academic referral hospital in Boston (USA), we identified adult patients meeting sepsis-3 criteria. Exclusion criteria were diabetic ketoacidosis, ICU length of stay under 1 day, and unknown race or ethnicity. We performed a logistic regression analysis to assess differential likelihoods of glucose measurements on day 1. A negative binomial regression was fitted to assess the frequency of subsequent glucose readings. Analyses were adjusted for relevant clinical confounders, and performed across three disparity proxy axes: race and ethnicity, sex, and English proficiency. RESULTS: We studied 24,927 patients, of which 19.5% represented racial and ethnic minority groups, 42.4% were female, and 9.8% had limited English proficiency. No significant differences were found for glucose measurement on day 1 in the ICU. This pattern was consistent irrespective of the axis of analysis, i.e. race and ethnicity, sex, or English proficiency. Conversely, subsequent measurement frequency revealed potential disparities. Specifically, males (incidence rate ratio (IRR) 1.06, 95% confidence interval (CI) 1.01 - 1.21), patients who identify themselves as Hispanic (IRR 1.11, 95% CI 1.01 - 1.21), or Black (IRR 1.06, 95% CI 1.01 - 1.12), and patients being English proficient (IRR 1.08, 95% CI 1.01 - 1.15) had higher chances of subsequent glucose readings. CONCLUSION: We found disparities in ICU glucose measurements among patients with sepsis, albeit the magnitude was small. Variation in disease monitoring is a source of data bias that may lead to spurious correlations when modeling health data.

Treatment of glucocorticoid- induced hyperglycemia in hospitalized patients - a systematic review and meta- analysis.

PURPOSE: Glucocorticoid (GC)-induced hyperglycemia is a frequent issue, however there are no specific guidelines for this diabetes subtype. Although treat-to-target insulin is recommended in general to correct hyperglycemia, it remains unclear which treatment strategy has a positive effect on outcomes. We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) to assess whether treating GC-induced hyperglycemia improves clinical outcomes. METHODS: MEDLINE and EMBASE were systematically searched for RCTs on adults reporting treatment and outcomes of GC-induced hyperglycemia since the beginning of the data bases until October 21, 2023. Glucose-lowering strategies as compared to usual care were investigated. RESULTS: We found 17 RCTs with 808 patients and included seven trials in the quantitative analysis. Patients with an intensive glucose-lowering strategy had lower standardized mean glucose levels of - 0.29 mmol/l (95%CI -0.64 to -0.05) compared to usual care group patients. There was no increase in hypoglycemic events in the intensively treated groups (RR 0.91, 95%CI 0.70-1.17). Overall, we did not have enough trials reporting clinical outcomes for a quantitative analysis with only one trial reporting mortality. CONCLUSION: In GC-induced hyperglycemia, tight glucose control has a moderate effect on mean glucose levels with no apparent harmful effect regarding hypoglycemia. There is insufficient data whether insulin treatment improves clinical outcomes, and data on non-insulin based treatment regimens are currently too sparse to draw any conclusions. SYSTEMATIC REVIEW REGISTRATION: Registered as CRD42020147409 at PROSPERO ( https://www.crd.york.ac.uk/prospero/ ) on April 28, 2020.

Barakat syndrome diagnosed decades after initial presentation.

Summary: Barakat syndrome, also called HDR syndrome, is a rare genetic disorder encompassing hypoparathyroidism (H), sensorineural deafness (D) and renal disease (R). A 64-year-old woman was referred to our endocrinology clinic for a switch in treatment (from dihydrotachysterol to calcitriol). She had progressive sensorineural deafness since the age of 18 and idiopathic hypoparathyroidism diagnosed at age of 36. Her medical history included osteoporosis with hip/spine fractures, nephrolithiasis and a family history of hearing loss, osteoporosis and kidney disease. The patient's clinical presentation indicated Barakat syndrome. Genetic analysis found a GATA3:c.916C>T nonsense variant. Further tests such as audiometry, labs and renal imaging supported the diagnosis. Due to rarity and manifold symptoms, diagnosis can be challenging. Optional GATA3 testing was suggested in 2018, except in cases of isolated sensorineural deafness or renal disease with pertinent family history. In isolated 'H' cases without 'D' and 'R', GATA3 studies are not required, as no haploinsufficiency cases were reported. Given the rise in genetic disorders, physicians should consistently consider rare genetic disorders in patients with suggestive symptoms, even decades after onset. Although diagnosis might not always impact management directly, it aids patients in accepting their condition and has broader family implications. Learning points: There is currently an important increase in genetic and clinical characterization of new orphan diseases and their causative agents. Unbiased re-evaluation for possible genetic disorders is necessary at every consultation. It is essential to recognize the differential diagnosis of idiopathic hypoparathyroidism. The patient's clinical presentation and family history can be important to establish the correct diagnosis. Physicians should not hesitate to search a patient's signs and symptoms online.

Variation in monitoring: Glucose measurement in the ICU as a case study to preempt spurious correlations.

Objective: Health inequities can be influenced by demographic factors such as race and ethnicity, proficiency in English, and biological sex. Disparities may manifest as differential likelihood of testing which correlates directly with the likelihood of an intervention to address an abnormal finding. Our retrospective observational study evaluated the presence of variation in glucose measurements in the Intensive Care Unit (ICU). Methods: Using the MIMIC-IV database (2008-2019), a single-center, academic referral hospital in Boston (USA), we identified adult patients meeting sepsis-3 criteria. Exclusion criteria were diabetic ketoacidosis, ICU length of stay under 1 day, and unknown race or ethnicity. We performed a logistic regression analysis to assess differential likelihoods of glucose measurements on day 1. A negative binomial regression was fitted to assess the frequency of subsequent glucose readings. Analyses were adjusted for relevant clinical confounders, and performed across three disparity proxy axes: race and ethnicity, sex, and English proficiency. Results: We studied 24,927 patients, of which 19.5% represented racial and ethnic minority groups, 42.4% were female, and 9.8% had limited English proficiency. No significant differences were found for glucose measurement on day 1 in the ICU. This pattern was consistent irrespective of the axis of analysis, i.e. race and ethnicity, sex, or English proficiency. Conversely, subsequent measurement frequency revealed potential disparities. Specifically, males (incidence rate ratio (IRR) 1.06, 95% confidence interval (CI) 1.01 - 1.21), patients who identify themselves as Hispanic (IRR 1.11, 95% CI 1.01 - 1.21), or Black (IRR 1.06, 95% CI 1.01 - 1.12), and patients being English proficient (IRR 1.08, 95% CI 1.01 - 1.15) had higher chances of subsequent glucose readings. Conclusion: We found disparities in ICU glucose measurements among patients with sepsis, albeit the magnitude was small. Variation in disease monitoring is a source of data bias that may lead to spurious correlations when modeling health data.

Evaluating equitable care in the ICU: Creating a causal inference framework to assess the impact of life-sustaining interventions across racial and ethnic groups.

Background: Variability in the provision of intensive care unit (ICU)-interventions may lead to disparities between socially defined racial-ethnic groups. Research Question: We used causal inference to examine the use of invasive mechanical ventilation (IMV), renal replacement therapy (RRT), and vasopressor agents (VP) to identify disparities in outcomes across race-ethnicity in patients with sepsis. Study Design and Methods: Single-center, academic referral hospital in Boston, Massachusetts, USA. Retrospective analysis of treatment effect with a targeted trial design categorized by treatment assignment within the first 24 hours in the MIMIC-IV dataset (2008- 2019) using targeted maximum likelihood estimation. Of 76,943 ICU stays in MIMIC-IV, 32,971 adult stays fulfilling sepsis-3 criteria were included. The primary outcome was in-hospital mortality. Secondary outcomes were hospital-free days, and occurrence of nosocomial infection stratified by predicted mortality probability ranges and self-reported race-ethnicity. Average treatment effects by treatment type and race-ethnicity, Racial-ethnic group (REG) or White group (WG), were estimated. Results: Of 19,419 admissions that met inclusion criteria, median age was 68 years, 57.4% were women, 82% were White, and mortality was 18.2%. There was no difference in mortality benefit associated with the administration of IMV, RRT, or VP between the REG and the WG. There was also no difference in hospital-free days or nosocomial infections. These findings are unchanged with different eligibility periods. Interpretation: There were no differences in the treatment outcomes from three life-sustaining interventions in the ICU according to race-ethnicity. While there was no discernable harm from the treatments across mortality risk, there was also no measurable benefit. These findings highlight the need for research to understand better the risk-benefit of life-sustaining interventions in the ICU.

BOLD: Blood-gas and Oximetry Linked Dataset - Open Source Research.

Pulse oximeters measure peripheral arterial oxygen saturation (SpO 2 ) noninvasively, while the gold standard (SaO 2 ) involves arterial blood gas measurement. There are known racial and ethnic disparities in their performance. BOLD is a new comprehensive dataset that aims to underscore the importance of addressing biases in pulse oximetry accuracy, which disproportionately affect darker-skinned patients. The dataset was created by harmonizing three Electronic Health Record databases (MIMIC-III, MIMIC-IV, eICU-CRD) comprising Intensive Care Unit stays of US patients. Paired SpO 2 and SaO 2 measurements were time-aligned and combined with various other sociodemographic and parameters to provide a detailed representation of each patient. BOLD includes 49,099 paired measurements, within a 5-minute window and with oxygen saturation levels between 70-100%. Minority racial and ethnic groups account for ∼25% of the data - a proportion seldom achieved in previous studies. The codebase is publicly available. Given the prevalent use of pulse oximeters in the hospital and at home, we hope that BOLD will be leveraged to develop debiasing algorithms that can result in more equitable healthcare solutions.

Racial Disparities in Invasive ICU Treatments Among Septic Patients: High Resolution Electronic Health Records Analysis from MIMIC-IV.

Background: Low-resolution administrative databases can give biased results, whereas high-resolution, time-stamped variables from clinical databases like MIMIC-IV might provide nuanced insights. We evaluated racial-ethnic disparities in life-sustaining ICU-treatments (Invasive Mechanical Ventilation (IMV), Renal Replacement Therapy (RRT), and Vasopressors (VP)) among patients with sepsis. Methods: In this observational retrospective cohort study, patients fulfilling sepsis-3 criteria were categorized by treatment assignment within the first 4 days. The outcomes were treatment allocations. The likelihood of receiving treatment was calculated by race-ethnicity (Racial-ethnic group (REG) or White group (WG)) using 5-fold sub-sampling nested logistic regression and XGBoost. Results: In 23,914 admissions, 82% were White, 42% were women. REG were less likely to receive IMV across all eligibility days (day 1 odds ratio (OR) 0.87, 95% confidence interval (CI) 0.83-0.94, day 4 OR 0.80, 95% CI 0.72 - 0.87). There were no differences in RRT (day 1 OR 1.00, 95% CI 0.96-1.09, day 4 OR 1.00, 95% CI 0.94-1.06). REG were also less likely to be treated with VP at days 1 to 3 (day 1 OR 0.87, 95% CI 0.76-0.94), but not at day 4 (OR 0.95, 95% CI 0.87-1.01). These findings remained robust when relaxing eligibility criteria for treatment allocation. Conclusion: Our findings reveal significant disparities in the use of invasive life-saving ICU treatments among septic patients from racial and ethnic minority backgrounds, particularly with respect to IMV and VP use. These disparities underscore not only the need to address inequality in critical care settings, but also highlight the importance of high-resolution data.

Prediction of In-Hospital Falls Using NRS, PACD Score and FallRS: A Retrospective Cohort Study.

BACKGROUND: Harmful in-hospital falls with subsequent injuries often cause longer stays and subsequently higher costs. Early identification of fall risk may help in establishing preventive strategies. OBJECTIVE: To assess the predictive ability of different clinical scores including the Post-acute care discharge (PACD) score and nutritional risk screening score (NRS), and to develop a new fall risk score (FallRS). METHODS: A retrospective cohort study of medical in-patients of a Swiss tertiary care hospital from January 2016 to March 2022. We tested the ability of the PACD score, NRS and FallRS to predict a fall by using the area under curve (AUC). Adult patients with a length of stay of ≥ 2 days were eligible. RESULTS: We included 19,270 admissions (43% females; median age, 71) of which 528 admissions (2.74%) had at least one fall during the hospital stay. The AUC varied between 0.61 (95% confidence interval (CI), 0.55-0.66) for the NRS and 0.69 (95% CI, 0.64-0.75) for the PACD score. The combined FallRS score had a slightly better AUC of 0.70 (95% CI, 0.65-0.75) but was more laborious to compute than the two other scores. At a cutoff of 13 points, the FallRS had a specificity of 77% and a sensitivity of 49% in predicting falls. CONCLUSIONS: We found that the scores focusing on different aspects of clinical care predicted the risk of falls with fair accuracy. A reliable score with which to predict falls could help in establishing preventive strategies for reducing in-hospital falls. Whether or not the scores presented have better predictive ability than more specific fall scores do will need to be validated in a prospective study.

Prevalence, Risk Factors and Outcomes Associated with Physical Restraint in Acute Medical Inpatients over 4 Years-A Retrospective Cohort Study.

BACKGROUND: Physical restraints are frequently used in acute care hospitals. Their application is associated with negative outcomes, while their intended preventive effect is debated. OBJECTIVES: To determine the prevalence of physical restraints and associated outcomes on medical wards in a tertiary care hospital. METHODS: Retrospective cohort study (January 2018 to December 2021). We included all adult medical in-patients and excluded patients with admission to the intensive care unit, short stays (length of stay (LOS) < 48 h), and patients declining informed consent. RESULTS: Of 11,979 admissions, the prevalence of patients with at least one restraint was 6.4% (n = 772). Sensor mats were used most frequently (73.0%, n = 666), followed by blanket restrictions (14.5%, n = 132), bedrails (8.8%, n = 80) and belts (3.7%, n = 34). On average, restraints were applied 19 h (standard deviation (SD) ± 161) before a fall. Average restraint duration was 42 h (SD ± 57). Patients with a restraint had longer LOS 8 days (IQR 5-14) vs. 5 days (IQR 3-9). Median nurses' time expenditure was 309 h (IQR 242-402) vs. 182 h (IQR 136-243) for non-restrained patients. Patients with restraints fell more often (22.5% vs. 2.7%) and were more likely to die (13.3% vs. 5.1%). These differences persisted after adjusting a regression model for important clinical confounders. We saw a decline in the duration of restraints over the years, but no variation between wards. CONCLUSION: Approximately 6% of medical patients, mostly older and severely ill, were affected by restraint use. For the first time, we report data over 4 years up to ward-level granularity.

Comparison of Cardiovascular Procedure Rates in Patients With Supplementary vs Basic Insurance in Switzerland.

Importance: Switzerland's mandatory health insurance provides universal coverage, but residents can opt for supplementary private insurance for nonessential, nonvital amenities. It is debated whether people with supplementary private insurance receive overtreatment due to financial incentives. Objective: To assess whether incidence rates of cardiovascular procedures in people with supplementary private insurance are higher than in those with basic insurance only. Design, Setting, and Participants: A population-based weighted cohort comparative effectiveness study, using administrative claims data from Switzerland assessing incidence rates (IRs), was conducted in adults undergoing a nonemergency cardiovascular inpatient procedure from January 1, 2012, to December 31, 2020. Analysis included primary or secondary discharge procedure codes for 1 of the following: percutaneous transluminal coronary angioplasty (PTCA), left atrial appendage (LAA) occlusion, patent foramen ovale (PFO) closure, transcatheter aortic valve replacement (TAVR), mitral valve clip implantation, cardiac pacemaker implantation, and atrial fibrillation/atrial flutter ablation. Exposures: Supplementary private health insurance. Main Outcomes and Measures: Incidence rates of cardiovascular procedures between insurance groups calculated by negative binomial regression adjusted by inverse probability weights. Results: Of 590 919 admissions (median age, 68 years; IQR, 57-77 years), 55.5% male, 15.7% non-Swiss nationality), 70.1% had basic insurance only. Independent of insurance status, IR for all cardiovascular procedures steadily increased over the study years. In general, people with supplementary private insurance received cardiovascular procedures more frequently (IR ratio [IRR], 1.11; 99% CI, 1.10-1.11) than people with basic insurance only. There was also an increase for every procedure: PTCA (IRR, 1.12; 99% CI, 1.12-1.13), LAA closure (IRR, 1.15; 99% CI, 1.13-1.16), mitral valve clip implantation (IRR, 1.08; 99% CI, 1.07-1.09), TAVR (IRR, 1.04; 99% CI, 1.03-1.06), PFO closure (IRR, 1.01; 99% CI, 1.00-1.02), pacemaker implantation (IRR, 1.08; 99% CI, 1.07-1.09), and atrial fibrillation/atrial flutter ablation (IRR, 1.12; 99% CI, 1.11-1.12). Sensitivity analyses, including side procedures, stratification by length of stay, and propensity score matching, suggested robustness of the results. Conclusions and Relevance: This study found an association between supplementary private insurance and a higher likelihood of receiving nonemergency cardiovascular procedures. Whether this higher rate of procedures in people with supplementary private insurance is based on clinical reasoning or due to financial incentives warrants further exploration.

Association of proteomic markers with nutritional risk and response to nutritional support: A secondary pilot study of the EFFORT trial using an untargeted proteomics approach.

BACKGROUND: By means of a structured nutritional support intervention, EFFORT showed a risk reduction for adverse events in medical in-patients. We were interested in the prognostic and therapeutic potential of an untargeted proteomics approach to understand response to nutritional support, risk of 30-day mortality, and distinct patterns in severity of malnutrition risk as assessed by the Nutritional Risk screening (NRS 2002), respectively. METHODS: From 2,088 patients, we randomly took 120 blood samples drawn before treatment initiation on day 1 after hospital admission. Cases were selected by treatment allocation (nutritional support vs. usual nutrition), NRS 2002, and mortality at 30 days, but not on disease type. We measured proteins by untargeted liquid chromatography mass spectrometry (LC-MS/MS). RESULTS: We found 242 distinct proteins in 120 patients of which 81 (67.5%) survived until day 30. Between group analysis revealed a slight difference between the treatment groups in patients with a NRS 3, but not in those with a higher NRS. C-statistic between non-survivors and survivors at day 30 ranged from 0.60 (95% confidence interval 0.34-0.78) for a combination of 3 proteins/predictors to 0.65 (95% CI 0.53-0.78) for a combination of 32 proteins/predictors. In nutritional support non-survivors, pathway analysis found significant enrichment in pathways for signal transduction, platelet function, immune system regulation, extracellular matrix organization, and integrin cell surface interactions compared to survivors. CONCLUSION: Within this pilot study using an untargeted proteomics approach, there was only little prognostic and therapeutic potential of proteomics for phenotyping the risk of malnutrition and response to nutritional therapy. The small sample size and high heterogeneity of our population regarding comorbidity burden calls for more targeted approaches in more homogenous populations to understand the true potential of proteomics for individualizing nutritional care. TRIAL REGISTRATION: This is a pre-planned secondary analysis of the EFFORT trial (ClinicalTrials.gov NCT02517476).

Glucose control after glucocorticoid administration in hospitalized patients - a retrospective analysis.

BACKGROUND: Glucocorticoid (GC)-induced hyperglycemia is a frequent adverse effect in hospitalized patients. Guidelines recommend insulin treatment to a target range of 6-10 mmol/L (108-180 mg/dl), but efficacies of particular regimes have not been well-studied. METHODS: In this retrospective cohort study, hospitalized patients receiving GCs at the medical ward were analyzed by treatment (basal-bolus vs. bolus-only vs. pre-mixed insulin) and compared to a non-insulin-therapy reference group. Coefficients of glucose variation (CV), percentage of glucose readings in range (4-10 mmol/L (72-180 mg/dl)) and hypoglycemia (< 4 mmol/L (< 72 mg/dl)) were evaluated. RESULTS: Of 2424 hospitalized patients receiving systemic GCs, 875 (36%) developed GC-induced hyperglycemia. 427 patients (17%) had a previous diagnosis of diabetes. Adjusted relative risk ratios (RRR) for the top tertile of CV (> 29%) were 1.47 (95% Cl 1.01-2.15) for bolus-only insulin, 4.77 (95% CI 2.67-8.51) for basal-bolus insulin, and 4.98 (95% CI 2.02-12.31) for premixed insulin, respectively. Adjusted RRR for percentages of glucose readings in range were 0.98 (95% Cl 0.97-0.99) for basal-bolus insulin, 0.99 (95% Cl 0.98-1.00) for premixed insulin, and 1.01 (95% Cl 1.00-1.01) for bolus-only insulin, respectively. Adjusted RRR for hypoglycemia was 13.17 (95% Cl 4.35-39.90) for basal-bolus insulin, 8.92 (95% Cl 2.60-30.63) for premixed insulin, and 2.99 (95% Cl 1.01-8.87) for bolus-only insulin, respectively. CONCLUSIONS: Current guidelines recommend a basal-bolus regimen for treatment of GC-induced hyperglycemia, but we found similar outcomes with pre-mixed and bolus-only insulin regimens. As GC-induced hyperglycemia is a frequent issue in hospitalized patients, it might be reasonable to prospectively study the ideal regimen.

Call, chosen, HA2T2, ANDC: validation of four severity scores in COVID-19 patients.

PURPOSE: To externally validate four previously developed severity scores (i.e., CALL, CHOSEN, HA2T2 and ANDC) in patients with COVID-19 hospitalised in a tertiary care centre in Switzerland. METHODS: This observational analysis included adult patients with a real-time reverse-transcription polymerase chain reaction or rapid-antigen test confirmed severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection hospitalised consecutively at the Cantonal Hospital Aarau from February to December 2020. The primary endpoint was all-cause in-hospital mortality. The secondary endpoint was disease progression, defined as needing invasive ventilation, ICU admission or death. RESULTS: From 399 patients (mean age 66.6 years ± 13.4 SD, 68% males), we had complete data for calculating the CALL, CHOSEN, HA2T2 and ANDC scores in 297, 380, 151 and 124 cases, respectively. Odds ratios for all four scores showed significant associations with mortality. The discriminative power of the HA2T2 score was higher compared to CALL, CHOSEN and ANDC scores [area under the curve (AUC) 0.78 vs. 0.65, 0.69 and 0.66, respectively]. Negative predictive values (NPV) for mortality were high, particularly for the CALL score (≥ 6 points: 100%, ≥ 9 points: 95%). For disease progression, discriminative power was lower, with the CHOSEN score showing the best performance (AUC 0.66). CONCLUSION: In this external validation study, the four analysed scores had a lower performance compared to the original cohorts regarding prediction of mortality and disease progression. However, all scores were significantly associated with mortality and the NPV of the CALL and CHOSEN scores in particular allowed reliable identification of patients at low risk, making them suitable for outpatient management.

[VIPoma of the Pancreas]. / VIPom des Pankreas.

VIPoma of the Pancreas Abstract. A 50-year old man was admitted for evaluation of progressive, chronic diarrhea with loss of weight and recurrent hypokalemia. Eventually, a neuroendocrine tumor of the pancreas secreting VIP (VIPoma) could be diagnosed. The patient was cured by a pancreaticoduodenectomy (Whipple procedure). With this case, we want to highlight the importance of a structured work-up in chronic diarrhea including thorough history and clinical assessment, laboratory tests and imaging studies.

Comparison of characteristics, predictors and outcomes between the first and second COVID-19 waves in a tertiary care centre in Switzerland: an observational analysis.

AIM OF THE STUDY: To compare admission characteristics, predictors and outcomes of patients with confirmed coronavirus disease 2019 (COVID-19) hospitalised in a tertiary care hospital in Switzerland during the first and second waves of the pandemic. METHODS: This retrospective observational analysis included adult patients with  severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection confirmed by a real-time reverse transcriptase polymerase chain reaction (RT-PCR) or rapid antigen test and hospitalised at the Cantonal Hospital Aarau from 26 February to 30 April 2020 (first wave) and from 1 October to 31 December 2020 (second wave). The primary endpoint was all-cause in-hospital mortality. The secondary endpoints were transfer to the intensive care unit (ICU) and length of hospital stay (LOS). RESULTS: Overall, 486 patients (mean age 65.9 years ± 14.7 SD, 65% male) were included. Ninety-two patients (19%) died during the hospital stay and 92 patients (19%) were transferred to the ICU. Admission characteristics, including comorbidities and frailty, were similar for patients of the first (n = 100) and second wave (n = 386). However, during the second wave the median time from symptom onset to presentation to the emergency department (ED) was shorter (7 days, interquartile range [IQR] 4–9 vs 8 days, IQR 4–11; p = 0.02). In the second wave, most patients received high-dose glucocorticoid treatment (0% vs 76%, p <0.01). In-hospital mortality was similar among COVID-19 patients in the first (19/100, 19%) and second wave (73/386, 19%); this finding persisted after full adjustment in multiple regression models (adjusted odds ratio [aOR] 1.18, 95% confidence interval [CI] 0.49–2.80; p = 0.71). Risk for ICU admission was also similar (24% vs 18%; aOR 0.98, 95% CI 0.46–2.06; p = 0.95). More patients were transferred to rehabilitation facilities in the second wave (18% vs 31%; aOR 2.06, 95% CI 1.04–4.07; p = 0.04) and LOS was 2.5 days shorter (9.0 vs 6.5 days; adjusted difference −2.53 days, 95%-CI −4.51 to −0.54; p = 0.01). Main predictors for in-hospital death were patient age (aOR 1.07, 95% CI 1.02–1.11; p <0.01), male sex (aOR 2.41, 95% CI 1.05–5.55; p = 0.04) and the age-adjusted Charlson comorbidity index (aOR 1.27, 95% CI 1.09–1.48 p <0.01). CONCLUSION: Despite differing treatment regimens, mortality and ICU admission remained largely unchanged for COVID-19 patients admitted during the second wave of the pandemic in our tertiary care hospital. However, discharge processes were optimised with patients leaving the hospital earlier and going to rehabilitation facilities more often.  .

Association of metabolomic markers and response to nutritional support: A secondary analysis of the EFFORT trial using an untargeted metabolomics approach.

BACKGROUND & AIMS: The EFFORT trial reported a substantial risk reduction for adverse events and mortality in medical in-patients receiving a nutritional support intervention. With the use of an untargeted metabolomics approach, we investigated the prognostic and therapeutic potential of metabolomic markers to understand, whether there are distinct metabolic patterns associated with malnutrition risk as assessed by the Nutritional Risk screening (NRS 2002) score, the risk of 30-day mortality and the response to nutritional support, respectively. METHODS: Out of the 2088 samples we randomly selected 120 blood samples drawn on day 1 after hospital admission and before treatment initiation. Samples were stratified by NRS 2002, treatment allocation (intervention vs. control), and mortality at 30 days, but not on the type of medical illness. We performed untargeted analysis by liquid chromatography mass spectrometry (LC-MS/MS). RESULTS: We measured 1389 metabolites in 120 patients of which 81 (67.5%) survived until day 30. After filtering, 371 metabolites remained, and 200 were matched to one or more Human Metabolome Data Base (HMDB) entries. Between group analysis showed a slight distinction between the treatment groups for patients with a NRS 3, but not for those with NRS 4 and ≥ 5. C-statistic between those who died and survived at day 30 ranged from 0.49 (95% confidence interval 0.35-0.68) for a combination of 5 metabolites/predictors to 0.66 (95% confidence interval 0.53-0.79) for a combination of 100 metabolites. Pathway analysis found significant enrichment in the pathways for nitrogen, vitamin B3 (nicotinate and nicotinamide), leukotriene, and arachidonic acid metabolisms in nutritional support responders compared to non-responders. CONCLUSION: In our heterogenous population of medical inpatients with different illnesses and comorbidities, metabolomic markers showed little prognostic and therapeutic potential for better phenotyping malnutrition and response to nutritional therapy. Future studies should focus on more selected patient populations to understand whether a metabolomic approach can advance the nutritional care of patients.

Synchronous pituitary and pineal gland lesions presenting with panhypopituitarism in a patient with widespread colorectal cancer: a case report.

A 60-year-old man presented to our hospital because of febrile neutropenia due to chemotherapy for his metastasized colon cancer. During hospital stay, polyuria and polydipsia were noted. He reported that his thirst had become increasingly intolerable over the last weeks. Diabetes mellitus was diagnosed. Polyuria and polydipsia persisted despite euglycemia under insulin treatment. Because of thirst and high urine volumes during the night, diabetes insipidus was suspected. Endocrinological work up revealed complete panhypopituitarism with impairment of all anterior and posterior axes. After substitution with hydrocortisone, levothyroxine and desmopressin symptoms resolved. MRI of the brain revealed one round, contrast enhancing lesion in the pituitary stalk and one in the pineal gland. Because of extensive extracerebral metastasis and poor performance status, the patient opted for radiation therapy only. He died 2.5 months later due to non-cerebral manifestations of his cancer before cerebral radiotherapy could be initiated.

Quality of life after hospitalization predicts one-year readmission risk in a large Swiss cohort of medical in-patients.

PURPOSE: Estimating the probability of readmission following hospitalization using prediction scores can be complex. Quality of life (QoL) may provide an easy and effective alternative. METHODS: Secondary analysis of the prospective "TRIAGE" cohort. All medical in-patients admitted to a Swiss tertiary care institution (2016-2019) ≥18 years with a length of stay of ≥2 days (23,309 patients) were included. EQ-5D VAS, EQ-5D index, and Barthel index were assessed at a single telephone interview 30-day after admission. Patients lost to follow-up were excluded. Readmission was defined as a non-elective hospital stay at our institution >24 h within 1 year after discharge and assessed using area under the curve (AUC) analysis with adjustment for confounders. RESULTS: 12,842 patients (43% females, median age 68, IQR 55-78) were included. Unadjusted discrimination was modest at 0.59 (95% CI 0.56-0.62) for EQ-5D VAS. Partially adjusted discrimination (for gender) was identical. Additional adjustment for insurance, Charlson comorbidity index, length of stay, and native language increased the AUC to 0.66 (95% CI 0.63-0.69). Results were robust irrespective of time to event (12, 6 or 3 months). A cut-off in the unadjusted model of EQ-5D VAS of 55 could separate cases with a specificity of 80% and a sensitivity of 30%. CONCLUSION: QoL at day 30 after admission can predict one-year readmission risk with similar precision as more intricate tools. It might help for identification of high-risk patients and the design of tailored prevention strategies.