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BackgroundHeart failure decompensation is a major driver of hospitalizations and represents a significant burden to the health care system. Identifying those at greatest risk of admission can allow for targeted interventions to reduce this risk. ObjectiveThis paper aims to compare the predictive value of objective and subjective heart failure respiratory symptoms on imminent heart failure decompensation and subsequent hospitalization within a 30-day period. MethodsA prospective observational pilot study was conducted. People living at home with heart failure were recruited from a single-center heart failure outpatient clinic. Objective (blood pressure, heart rate, weight, B-type natriuretic peptide) and subjective (4 heart failure respiratory symptoms scored for severity on a 5-point Likert scale) data were collected twice weekly for a 30-day period. ResultsA total of 29 participants (median age 79 years; 18/29, 62% men) completed the study. During the study period, 10 of the 29 participants (34%) were hospitalized as a result of heart failure. For objective data, only heart rate exhibited a between-group difference. However, it was nonsignificant for variability (P=.71). Subjective symptom scores provided better prediction. Specifically, the highest precision of heart failure hospitalization was observed when patients with heart failure experienced severe dyspnea, orthopnea, and bendopnea on any given day (area under the curve of 0.77; sensitivity of 83%; specificity of 73%). ConclusionsThe use of subjective respiratory symptom reporting on a 5-point Likert scale may facilitate a simple and low-cost method of predicting heart failure decompensation and imminent hospitalization. Serial collection of symptom data could be augmented using ecological momentary assessment of self-reported symptoms within a mobile health monitoring strategy for patients at high risk for heart failure decompensation.

Accurate quantification of bone, muscle, and their components is still an unmet need in the musculoskeletal field. Current methods to quantify tissue volumes in 3D images are expensive, labor-intensive, and time-consuming; thus, a reliable, valid, and quick application is highly needed. Tissue Compass is a standalone software for semiautomatic segmentation and automatic quantification of musculoskeletal organs. To validate the software, cross-sectional micro-CT scans images of rat femur (n = 19), and CT images of hip and abdomen (n = 100) from the Osteoporotic Fractures in Men (MrOS) Study were used to quantify bone, hematopoietic marrow (HBM), and marrow adipose tissue (MAT) using commercial manual software as a comparator. Also, abdominal CT scans (n = 100) were used to quantify psoas muscle volumes and intermuscular adipose tissue (IMAT) using the same software. We calculated Pearson's correlation coefficients, individual intra-class correlation coefficients (ICC), and Bland-Altman limits of agreement together with Bland-Altman plots to show the inter- and intra-observer agreement between Tissue Compass and commercially available software. In the animal study, the agreement between Tissue Compass and commercial software was r > 0.93 and ICC > 0.93 for rat femur measurements. Bland-Altman limits of agreement was - 720.89 (- 1.5e+04, 13,074.00) for MAT, 4421.11 (- 1.8e+04, 27,149.73) for HBM and - 6073.32 (- 2.9e+04, 16,388.37) for bone. The inter-observer agreement for QCT human study between two observers was r > 0.99 and ICC > 0.99. Bland-Altman limits of agreement was 0.01 (- 0.07, 0.10) for MAT in hip, 0.02 (- 0.08, 0.12) for HBM in hip, 0.05 (- 0.15, 0.25) for bone in hip, 0.02 (- 0.18, 0.22) for MAT in L1, 0.00 (- 0.16, 0.16) for HBM in L1, and 0.02 (- 0.23, 0.27) for bone in L1. The intra-observer agreement for QCT human study between the two applications was r > 0.997 and ICC > 0.99. Bland-Altman limits of agreement was 0.03 (- 0.13, 0.20) for MAT in hip, 0.05 (- 0.08, 0.18) for HBM in hip, 0.05 (- 0.24, 0.34) for bone in hip, - 0.02 (- 0.34, 0.31) for MAT in L1, - 0.14 (- 0.44, 0.17) for HBM in L1, - 0.29 (- 0.62, 0.05) for bone in L1, 0.03 (- 0.08, 0.15) for IMAT in psoas, and 0.02 (- 0.35, 0.38) for muscle in psoas. Compared to a conventional application, Tissue Compass demonstrated high accuracy and non-inferiority while also facilitating easier analyses. Tissue Compass could become the tool of choice to diagnose tissue loss/gain syndromes in the future by requiring a small number of CT sections to detect tissue volumes and fat infiltration.

Accurate quantification of bone, muscle, and their components is still an unmet need in the musculoskeletal field. Current methods to quantify tissue volumes in 3D images are expensive, labor-intensive, and time-consuming; thus, a reliable, valid, and quick application is highly needed. Tissue Compass is a standalone software for semiautomatic segmentation and automatic quantification of musculoskeletal organs. To validate the software, cross-sectional micro-CT scans images of rat femur (n = 19), and CT images of hip and abdomen (n = 100) from the Osteoporotic Fractures in Men (MrOS) Study were used to quantify bone, hematopoietic marrow (HBM), and marrow adipose tissue (MAT) using commercial manual software as a comparator. Also, abdominal CT scans (n = 100) were used to quantify psoas muscle volumes and intermuscular adipose tissue (IMAT) using the same software. We calculated Pearson's correlation coefficients, individual intra-class correlation coefficients (ICC), and Bland-Altman limits of agreement together with Bland-Altman plots to show the inter- and intra-observer agreement between Tissue Compass and commercially available software. In the animal study, the agreement between Tissue Compass and commercial software was r > 0.93 and ICC > 0.93 for rat femur measurements. Bland-Altman limits of agreement was - 720.89 (- 1.5e+04, 13,074.00) for MAT, 4421.11 (- 1.8e+04, 27,149.73) for HBM and - 6073.32 (- 2.9e+04, 16,388.37) for bone. The inter-observer agreement for QCT human study between two observers was r > 0.99 and ICC > 0.99. Bland-Altman limits of agreement was 0.01 (- 0.07, 0.10) for MAT in hip, 0.02 (- 0.08, 0.12) for HBM in hip, 0.05 (- 0.15, 0.25) for bone in hip, 0.02 (- 0.18, 0.22) for MAT in L1, 0.00 (- 0.16, 0.16) for HBM in L1, and 0.02 (- 0.23, 0.27) for bone in L1. The intra-observer agreement for QCT human study between the two applications was r > 0.997 and ICC > 0.99. Bland-Altman limits of agreement was 0.03 (- 0.13, 0.20) for MAT in hip, 0.05 (- 0.08, 0.18) for HBM in hip, 0.05 (- 0.24, 0.34) for bone in hip, - 0.02 (- 0.34, 0.31) for MAT in L1, - 0.14 (- 0.44, 0.17) for HBM in L1, - 0.29 (- 0.62, 0.05) for bone in L1, 0.03 (- 0.08, 0.15) for IMAT in psoas, and 0.02 (- 0.35, 0.38) for muscle in psoas. Compared to a conventional application, Tissue Compass demonstrated high accuracy and non-inferiority while also facilitating easier analyses. Tissue Compass could become the tool of choice to diagnose tissue loss/gain syndromes in the future by requiring a small number of CT sections to detect tissue volumes and fat infiltration.

Background: Thiopurine co‐therapy with anti‐tumour necrosis factor‐alpha (anti‐TNFα) agents is associated with higher anti‐TNFα drug levels and reduced immunogenicity in inflammatory bowel disease (IBD). Aims: We aimed to evaluate the association between 6‐thioguanine nucleotide (6‐TGN) and anti‐TNFα levels and the optimal 6‐TGN threshold level associated with higher anti‐TNFα levels in combination therapy. Methods: We performed a retrospective cross‐sectional multicentre study of patients with IBD on combination anti‐TNFα and thiopurine maintenance therapy between January 2015 and August 2021. Primary outcomes were infliximab and adalimumab levels. Secondary outcomes were antibodies to infliximab (ATI) or adalimumab (ATA). Univariable and multivariable linear regression were performed to identify variables associated with anti‐TNFα levels. Receiver operator characteristic curves were used to define the optimal 6‐TGN cut‐off levels associated with therapeutic anti‐TNFα levels. Results: The study included 743 paired 6‐TGN and anti‐TNFα levels (640 infliximab and 103 adalimumab). 6‐TGN levels were associated with infliximab levels, but not adalimumab levels, on univariable and multivariable regression. The optimal 6‐TGN cut‐off associated with therapeutic infliximab levels (≥5 mcg/mL) was 261 pmol/8 × 108 red blood cell (RBC) (area under the curve (AUC) = 0.57) for standard infliximab dosing and 227.5 pmol/8 × 108 RBC (AUC = 0.58) for escalated dosing. For therapeutic adalimumab levels (≥7.5 mcg/mL), the 6‐TGN cut‐off was 218.5 pmol/8 × 108 RBC (AUC = 0.59) for standard adalimumab dosing and 237.5 pmol/8 × 108 RBC (AUC = 0.63) for escalated dosing. Conclusion: 6‐TGN levels were weakly associated with infliximab but not adalimumab levels in combination therapy. 6‐TGN levels in the lower end of the therapeutic range (230–260 pmol/8 × 108 RBC) may be adequate to maintain higher infliximab levels, particularly with escalated infliximab dosing. [ABSTRACT FROM AUTHOR]

Background Patient-reported penicillin allergy labels (PALs) are associated with adverse patient outcomes and inappropriate antibiotic prescribing. Removal of PALs via direct oral challenge (DOC) is associated with increased penicillin utilization post removal. Objectives To assess the impact of direct delabelling (allergy label removal via medical reconciliation alone) of type A adverse drug reaction (ADR) PALs on inpatient prescribing. Methods From January 2019 to December 2022 at two tertiary hospitals in Melbourne, patients aged ≥18 years with type A ADR PALs, as defined by the validated Antibiotic Allergy Assessment Tool, were offered direct delabelling or single-dose DOC. The primary endpoint was antibiotic use pre- and post-assessment (during index admission and 90 days post assessment). The secondary endpoint was the proportion of patients delabelled in the direct delabelling and DOC cohorts in the electronic medical record at 90 days post assessment. Results Allergy labels (n  = 4108) were assessed for 488 participants, with 490 individual type A ADR PAL assessments included. Three hundred and thirty-seven patients were directly delabelled, 69 underwent DOC and 84 were not delabelled. There was increased use of any penicillin following direct delabelling (OR 19.19, 95% CI 2.48–148.36) and DOC (OR 56.98, 95% CI 6.82–476.19) during the index admission, higher in the DOC group compared with direct delabelling (OR 2.97, 95% CI 1.39–6.37). Relabelling at 90 days was low with no statistically significant difference between direct delabelling (5/337; 1.5%) and DOC (0/69; 0%). Conclusions Both direct delabelling and DOC of type A ADR PALs increased penicillin usage; however, the impact was greatest with DOC. Most patients remain delabelled at 90 days. [ABSTRACT FROM AUTHOR]

Background and Aims: Accurate biomarkers to predict outcomes following discontinuation of nucleos(t)ide analogue (NA) therapy are needed. We evaluated serum hepatitis B core‐related antigen (HBcrAg) level as a biomarker for predicting outcomes after NA discontinuation. Methods: Patients with HBeAg‐negative chronic hepatitis B (CHB) without cirrhosis were enrolled in a prospective trial evaluating clinical outcomes until 96 weeks after NA discontinuation. End of treatment (EOT) and off‐treatment levels of serum HBcrAg, HBsAg, HBV RNA and HBV DNA were used to predict key clinical outcomes including hepatitis flare (ALT ≥5 × ULN and HBV DNA > 2000 IU/mL). The SCALE‐B score was calculated for the purposes of model validation. Results: HBcrAg was tested amongst 65 participants. The median age was 54 years, 54% were male and 83% were Asian. HBcrAg was detectable in 86% patients. HBcrAg level ≥4 log U/mL at EOT was predictive of hepatitis flare [8/10 (80%) vs. 17/55 (31%), p =.001]. The presence of either HBcrAg ≥4 log U/mL or detectable HBV RNA at EOT predicted for both biochemical relapse and hepatitis flare. The SCALE‐B model at EOT predicted for virological relapse, biochemical relapse, hepatitis flare and HBsAg loss in this cohort. An increase in the serum HBcrAg level off‐treatment was also associated with hepatitis flare. No participant with EOT HBcrAg level ≥4 log U/mL achieved HBsAg loss. Conclusions: High levels of serum HBcrAg predict for hepatitis flare after stopping NA therapy and low likelihood of HBsAg loss at week 96. People with high levels of serum HBcrAg are not suitable candidates for NA discontinuation. [ABSTRACT FROM AUTHOR]

Summary: Hypoglycaemia during sleep is a common and clinically important issue for people living with insulin‐treated diabetes. Continuous glucose monitoring devices can help to identify nocturnal hypoglycaemia and inform treatment strategies. However, sleep is generally inferred, with diabetes researchers and physicians using a fixed‐overnight period as a proxy for sleep–wake status when analysing and interpretating continuous glucose monitoring data. No study to date has validated such an approach with established sleep measures. Continuous glucose monitoring and research‐grade actigraphy devices were worn and sleep diaries completed for 2 weeks by 28 older adults (mean age 67 years [SD 5]; 17 (59%) women) with type 1 diabetes. Using continuous glucose monitoring data from a total of 356 nights, fixed‐overnight (using the recommended period of 00:00 hours–06:00 hours) and objectively‐measured sleep periods were compared. The fixed‐overnight period approach missed a median 57 min per night (interquartile range: 49–64) of sleep for each participant, including five continuous glucose monitoring‐detected hypoglycaemia episodes during objectively‐measured sleep. Twenty‐seven participants (96%) had at least 1 night with continuous glucose monitoring time‐in‐range and time‐above‐range discrepancies both ≥ 10 percentage points, a clinically significant discrepancy. The utility of fixed‐overnight time continuous glucose monitoring as a proxy for sleep–awake continuous glucose monitoring is inadequate as it consistently excludes actual sleep time, obscures glycaemic patterns, and misses sensor hypoglycaemia episodes during sleep. The use of validated measures of sleep to aid interpretation of continuous glucose monitoring data is encouraged. [ABSTRACT FROM AUTHOR]

Background and Aims The risk of intrahepatic cholestasis of pregnancy [ICP] is increased in thiopurine-exposed pregnancies. Thiopurine 'shunting', with a 6-methylmercaptopurine [MMP] to 6-thioguanine [TGN] ratio of >11, progresses over pregnancy, and may promote ICP development. We aimed to explore the association between thiopurine exposure and ICP, including the hypothesised impact of thiopurine shunting, and identify risk minimisation strategies. Methods This prospective multicentre cohort study compared thiopurine and biologic monotherapy-exposed pregnant participants. Disease activity and obstetric outcome data, thiopurine metabolites, bile acids, and transaminases were obtained before conception, in each trimester, at delivery, and postpartum. Thiopurine dose management was at the discretion of the treating physician. Results Included were 131 thiopurine and 147 biologic monotherapy-exposed pregnancies. MMP/TGN ratio increased from preconception to third trimester [ p  <0.01], with approximately 25% of participants shunting in pregnancy. Second trimester split dosing led to a decrease in the median MMP/TGN ratio from 18 (interquartile range [IQR] 6-57) to 3 [IQR 2-3.5] at delivery [ p  = 0.04]. The risk of ICP was increased in thiopurine-exposed pregnancies (6.7% [7/105] vs 0% [0/112], p  <0.001), with all ICP cases occurring in the setting of antenatal thiopurine shunting. Thiopurine dose increases (risk ratio [RR] 8.10, 95% confidence interval [CI] 1.88-34.85, p  = 0.005) and shunting in third trimester [6.20, 1.21-30.73, p  = 0.028] and at delivery [14.18, 1.62-123.9, p  = 0.016] were associated with an increased risk of ICP. Conclusions Thiopurine exposure is associated with an increased risk of ICP, particularly following dose increases antenatally and with shunting in late pregnancy. The latter may be effectively managed with split dosing, although further studies are warranted. [ABSTRACT FROM AUTHOR]