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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Several clinical risk scores for unplanned 30-day readmission have been published, but there is a lack of external validation and head-to-head comparison. Objective: Retrospective replication of six clinical risk scores (LACE, HOSPITAL, SEMI, RRS, PARA, Tsui et al.)f Design: Models were fitted with the original intercept and beta coefficients as reported. Otherwise, a logistic model was refitted (SEMI and Tsui et al). We performed subgroup analyses on main admission specialty. This report adheres to the TRIPOD statement for reporting of prediction models. Participants: We used our prospective cohort of 15,639 medical patients from a Swiss tertiary care institution from 2016 through 2018. Main Measures: Thirty-day readmission rate and area under the curve (AUC < 0.50 worse than chance, > 0.70 acceptable, > 0.80 excellent) Conclusions: Among several readmission risk scores, HOSPITAL, PARA, and the score from Tsui et al. showed the best predictive abilities and have high potential to improve patient care. Interventional research is now needed to understand the effects of these scores when used in clinical routine. Key Results: Among the six risk scores externally validated, calibration of the models was overall poor with overprediction of events, except for the HOSPITAL and the PARA scores. Discriminative abilities (AUC) were as follows: LACE 0.53 (95% CI 0.50–0.56), HOSPITAL 0.73 (95% CI 0.72–0.74), SEMI 0.47 (95% CI 0.46–0.49), RRS 0.64 (95% CI 0.62–0.66), PARA 0.72 (95% CI 0.72–0.74), and the score from Tsui et al. 0.73 (95% CI 0.72–0.75). Performance in subgroups did not differ from the overall performance, except for oncology patients in the PARA score (0.57, 95% CI 0.54–0.60), and nephrology patients in the SEMI index (0.25, 95% CI 0.18–0.31), respectively. [ABSTRACT FROM AUTHOR]

Early diagnosis of thyroid disorders is key to further treatment. We assessed the ability of a high-throughput proton NMR metabolomic profile to distinguish disease type amongst of Graves' disease (n=87), Hashimoto's thyroiditis (n=17), toxic goiter (n=11), and autoimmune thyroiditis [i. e., subacute thyroiditis (n=4), postpartum thyroiditis (n=1)]. This observational study was conducted investigating patients presenting with a thyroid disorder at a Swiss hospital endocrine referral center and an associated endocrine outpatient clinic. The main outcome was diagnosis of thyroid disorder based on classical parameters. Blood draws took place as close as possible to treatment initiation. We performed one-way ANOVA and partial least squares discriminant analysis (PLS-DA) as multivariate classification and feature ranking method. One-way ANOVA analysis yielded following significantly different metabolites, triglycerides in small VLDL, triglycerides in very small VLDL, and triglycerides in large LDL (FDR=0.04). There was no distinct separation of any of the 4 diagnoses by PLS-DA. We did not find a metabolomic biomarker combination capable of predicting diagnosis. Preanalytical issues might have influenced our results. We strongly suggest replicating our work in another cohort. [ABSTRACT FROM AUTHOR]

Objectives Recently, the Hospital Frailty Risk Score based on a derivation and validation study in the UK has been proposed as a low-cost, systematic screening tool to identify older, frail patients who are at a greater risk of adverse outcomes and for whom a frailty-attuned approach might be useful. We aimed to validate this Score in an independent cohort in Switzerland. Design Secondary analysis of a prospective, observational study (TRIAGE study). Setting One 600-bed tertiary care hospital in Aarau, Switzerland. Participants Consecutive medical inpatients aged =75 years that presented to the emergency department or were electively admitted between October 2015 and April 2018. Primary and secondary outcome measures The primary endpoint was all-cause 30-day mortality. Secondary endpoints were length of hospital stay, hospital readmission, functional impairment and quality of life measures. We used multivariate regression analyses. Results Of 4957 included patients, 3150 (63.5%) were classified as low risk, 1663 (33.5%) intermediate risk, and 144 (2.9%) high risk for frailty. Compared with the low-risk group, patients in the moderate risk and high-risk groups had increased risk for 30-day mortality (OR (OR) 2.53, 95% CI 2.09 to 3.06, p<0.001 and OR 4.40, 95% CI 2.94 to 6.57, p<0.001) with overall moderate discrimination (area under the ROC curve 0.66). The results remained robust after adjustment for important confounders. Similarly, we found longer length of hospital stay, more severe functional impairment and a lower quality of life in higher risk group patients. Conclusion Our data confirm the prognostic value of the Hospital Frailty Risk Score to identify older, frail people at risk for mortality and adverse outcomes in an independent patient population. [ABSTRACT FROM AUTHOR]

Background: Uncertainty about factors influencing the susceptibility and triggers for Graves' disease persists, along with a wide variation in the response to anti-thyroid drugs, currently at approximately 50% of non-responders. The aim of this narrative review is to summarize immunological concepts, with a combined endocrine and immunological perspective, to highlight potential new areas of research.Main Text: Relevant studies were identified through a systematic literature search using the PubMed and EMBASE databases in March 2016. No cut-offs regarding dates were imposed. We used the terms "Graves' Disease" or "Basedow" or "thyrotoxicosis" together with the terms "etiology", "pathophysiology", "immunodeficiency", "causality", and "autoimmunity". The terms "orbitopathy", "ophthalmopathy", and "amiodarone" were excluded. Articles in English, French, German, Croatian, Spanish, and Italian were eligible for inclusion.Conclusions: While concepts such as the impact of iodine, smoking, human leucocyte antigen, infections, and ethnicity are established, new ideas have emerged. Pertaining evidence suggests the involvement of autoimmunity and immunodeficiency in the pathophysiology of Graves' disease. Recent studies point to specific immunological mechanisms triggering the onset of disease, which may also serve as targets for more specific therapies. [ABSTRACT FROM AUTHOR]

Context: First-line treatment in Graves' disease is often done with antithyroid agents (ATD), but relapse rates remain high making definite treatment necessary. Predictors for relapse risk help guiding initial treatment decisions. Objective: We aimed to externally validate the prognostic accuracy of the recently proposed Graves' Recurrent Events After Therapy (GREAT) score to predict relapse risk in Graves' disease. Design, setting and participants: We retrospectively analyzed data (2004-2014) of patients with a first episode of Graves' hyperthyroidism from four Swiss endocrine outpatient clinics. Main outcome measures: Relapse of hyperthyroidism analyzed by multivariate Cox regression. Results: Of the 741 included patients, 371 experienced a relapse (50.1%) after a mean follow-up of 25.6 months after ATD start. In univariate regression analysis, higher serum free T4, higher thyrotropin-binding inhibitor immunoglobulin (TBII), younger age and larger goiter were associated with higher relapse risk. We found a strong increase in relapse risk with more points in the GREAT score from 33.8% in patients with GREAT class I (0-1 points), 59.4% in class II (2-3 points) with a hazard ratio of 1.79 (95% CI: 1.42-2.27, P < 0.001) and 73.6% in class III (4-6 points) with a hazard ratio of 2.24 (95% CI: 1.64-3.06, P < 0.001). Conclusions: Based on this retrospective analysis within a large patient population from a multicenter study, the GREAT score shows good external validity and can be used for assessing the risk for relapse in Graves' disease, which influence the initial treatment decisions. [ABSTRACT FROM AUTHOR]

Background: Identification of pretreatment risk factors predicting relapse in patients with hyperthyroidism of Graves' disease after stopping anti-thyroid drugs (ATD) is decisive to guide therapeutic options. Purpose: We performed a systematic search and meta-analysis to study predictors for relapse after stopping ATD in patients with Graves' disease. Methods: Based on a pre-specified protocol, we searched PubMed, EMBASE and Cochrane in July 2015 for case-control, controlled and randomized-controlled trials reporting risk factors for relapse after stopping ATD. The primary endpoint was relapse of disease until follow-up. PRISMA and SIGN statements were used for reviewing the data and assessing the quality of included trials. Results: We included 54 trials with a total of 7595 participants. Most trials were small with moderate-to-high risk for bias. Ten trials were assessed only qualitatively (2227 patients), genomic data were reported in 13 trials (2178 patients) and 31 trials (4346 patients) were assessed quantitatively. In total, there were 3696 relapses in 7595 patients (48.7%). By using random-effects meta-analysis, orbitopathy, smoking, thyroid volume measured by sonography, goiter size, fT4, tT3, TRAb and TBII were significantly associated with relapse, whereas male vs female sex, age and initial tT4 level did not show significant associations. Conclusions: This analysis found several risk factors to predict relapse in Graves' disease, which can be combined in a risk score. Prospective studies should evaluate the prognostic accuracy of such a score to guide treatment decisions. [ABSTRACT FROM AUTHOR]

Introduction: The inflammatory biomarker pro-adrenomedullin (ProADM) provides additional prognostic information for the risk stratification of general medical emergency department (ED) patients. The aim of this analysis was to develop a triage algorithm for improved prognostication and later use in an interventional trial. Methods: We used data from the multi-national, prospective, observational TRIAGE trial including consecutive medical ED patients from Switzerland, France and the United States. We investigated triage effects when adding ProADM at two established cut-offs to a five-level ED triage score with respect to adverse clinical outcome. Results: Mortality in the 6586 ED patients showed a step-wise, 25-fold increase from 0.6% to 4.5% and 15.4%, respectively, at the two ProADM cut-offs (≤0.75nmol/L, >0.75–1.5nmol/L, >1.5nmol/L, p ANOVA <0.0001). Risk stratification by combining ProADM within cut-off groups and the triage score resulted in the identification of 1662 patients (25.2% of the population) at a very low risk of mortality (0.3%, n = 5) and 425 patients (6.5% of the population) at very high risk of mortality (19.3%, n = 82). Risk estimation by using ProADM and the triage score from a logistic regression model allowed for a more accurate risk estimation in the whole population with a classification of 3255 patients (49.4% of the population) in the low risk group (0.3% mortality, n = 9) and 1673 (25.4% of the population) in the high-risk group (15.1% mortality, n = 252). Conclusions: Within this large international multicenter study, a combined triage score based on ProADM and established triage scores allowed a more accurate mortality risk discrimination. The TRIAGE-ProADM score improved identification of both patients at the highest risk of mortality who may benefit from early therapeutic interventions (rule in), and low risk patients where deferred treatment without negatively affecting outcome may be possible (rule out). [ABSTRACT FROM AUTHOR]

Background: Whether the addition of immunosuppressive drugs to standard antithyroid drugs reduces the relapse risk in Graves' disease remains uncertain. Purpose: The aim of this study was to investigate the effects of immunosuppressive drugs on the relapse rate after a first episode of hyperthyroidism due to Graves' disease. Methods: Based on a pre-specified protocol, PubMed (1946-July 2015), EMBASE (1947-July 2015), and Cochrane (1992-July 2015) databases were searched. The search was for (randomized) controlled trials comparing immunosuppressive drugs with a control group. PRISMA and SIGN statements were used for assessing data quality. Two reviewers extracted data, with any disagreement being resolved by consensus. Data were pooled using a random-effects model. Results: The primary endpoint was relapse of disease until follow-up. Secondary endpoints included reduction of thyroid volume and decrease in thyrotropin-receptor antibody (TRAb) levels. Seven trials with 862 participants were included. Most trials were small with a moderate to high risk of bias. There were 113 relapses in 481 (23.5%) patients receiving immunosuppressive drugs compared with 225 relapses in 381 (59.1%) control patients (risk ratio for recurrence 0.55; [confidence interval (CI) 0.41-0.75]). Subgroup analyses showed similar effects for randomized trials and controlled trials (I² 0%), and for trials using corticosteroid and non-corticosteroid immunosuppressive drugs (I² 0%). Use of immunosuppressive drugs also resulted in significant reductions in thyroid volume (-10.72 mL [CI -15.59 to -5.85]) and TRAb levels (-17.01 IU/L [CI -33.31 to -0.72]). Immunosuppressive drug-related adverse effects were not systematically reported, and thus were not included in the quantitative analysis. Conclusions: Current evidence suggests a possible relevant reduction in relapse risk when immunosuppressive drugs are added to standard treatment of Graves' disease. The small number of trials with high heterogeneity in regard to treatment modalities and the lack of systematic reporting of adverse effects calls for larger, conclusive trials. [ABSTRACT FROM AUTHOR]

Background: Metabolic syndrome is a major risk factor for cardiovascular diseases, which are still the major cause of death in developed countries. Methods: We cross-sectionally studied the association between urinary phytoestrogen excretion and metabolic cardiovascular risk factors. Hence, we used data from the National Health and Nutrition Examination Survey from 1999 to 2004 with 1,748 participants, who had urine levels of isoflavones and lignans measured. Geometric means of waist circumference, blood pressure, fasting glucose, HDL cholesterol, and triglyceride levels were computed by quartiles of isoflavone or lignan urinary excretion. Outcome was assessed as the presence of metabolic syndrome according to NCEP-ATP III criteria. The association between phytoestrogen concentration and the metabolic syndrome was calculated using logistic regression analyses. Results: Plasma triglyceride and HDL cholesterol levels were lower in participants in the highest quartile of lignan excretion compared with the lowest (both P < 0.01). However, blood pressure, waist circumference, and plasma glucose levels did not differ significantly between extreme quartiles. The presence of metabolic syndrome was lower with increasing levels of urinary lignans (OR 0.48, 95 % CI 0.28; 0.80 top vs. bottom quartile), especially when separately computed for the excretion of enterolactone (OR 0.47, 95 % CI 0.28; 0.78). There was no significant association between isoflavone excretion and any component of the metabolic syndrome. Conclusions: Our study shows that an increasing excretion of lignans, especially enterolactone, might be associated with a decreased presence of the metabolic syndrome. [ABSTRACT FROM AUTHOR]

Background: Glucocorticoid (GC)-induced hyperglycemia is a frequent side effect in hospitalized patients. Guidelines recommend treat-to-target treatment between 6–10 mmol/L (108–180 mg/dL) with insulin, but data on outcome is scarce. We investigated the 30-day outcome in hospitalized patients receiving GCs. Methods: All patient records of hospitalized patients between January 2014 and April 2018 were screened for GC administration and consecutive hyperglycemia. The primary combined endpoint consisted of death, cardiovascular events, and infections until 30 days after admission. Hypoglycemia was a secondary outcome. Results: Of the 2424 hospitalized patients (9.6% of all hospitalized patients) who received systemic GCs and met inclusion criteria, the overall incidence for GC-induced hyperglycemia was 812 (33.5%), and 89 (3.7%) had at least one documented hypoglycemia during their hospital stay. Compared to patients with normoglycemia, GC-induced hyperglycemia had an adjusted-odds ratio of 1.68 (95% CI 1.25–2.26) for the combined primary endpoint. Hypoglycemia even had an odds ratio of 1.95 (95% CI 1.2–3.17). Conclusions: Mortality, cardiovascular events, and rate of infections were markedly higher in patients with GC-induced hyperglycemia as compared to patients with normoglycemia. Importantly, hypoglycemia was associated with a doubled risk for adverse outcome. Future studies should evaluate whether optimized glucose control by minimizing the risk for hypoglycemia has a beneficial effect on clinical outcomes in patients with GC-induced hyperglycemia. [ABSTRACT FROM AUTHOR]

When counseling patients regarding the best first-line treatment for Graves' disease, physicians should use a shared decision making approach outlining the risks and benefits of each treatment option and providing estimates regarding recurrence risks with antithyroid drug therapy based on recently published clinical scores (i.e., GREAT score) [[3]]. 3 Struja T, Kaeslin M, Boesiger F, Jutzi R, Imahorn N, Kutz A. External validation of the GREAT score to predict relapse risk in Graves' disease: results from a multicenter, retrospective study with 741 patients. Predicting the risk of recurrence before the start of antithyroid drug therapy in patients with Graves' hyperthyroidism. [Extracted from the article]