Sex and ethnic disparities in hepatitis B evaluation and treatment across the world.

BACKGROUND & AIMS: Oral antiviral therapy with nucleos(t)ide analogues (NAs) for chronic hepatitis B (CHB) is well-tolerated and lifesaving, but real-world data on utilization are limited. We examined rates of evaluation and treatment in patients from the REAL-B consortium. METHODS: This was a cross-sectional study nested within our retrospective multinational clinical consortium (2000-2021). We determined the proportions of patients receiving adequate evaluation, meeting AASLD treatment criteria, and initiating treatment at any time during the study period. We also identified factors associated with receiving adequate evaluation and treatment using multivariable logistic regression analyses. RESULTS: We analyzed 12,566 adult treatment-naïve patients with CHB from 25 centers in 9 countries (mean age 47.1 years, 41.7% female, 96.1% Asian, 49.6% Western region, 8.7% cirrhosis). Overall, 73.3% (9,206 patients) received adequate evaluation. Among the adequately evaluated, 32.6% (3,001 patients) were treatment eligible by AASLD criteria, 83.3% (2,500 patients) of whom were initiated on NAs, with consistent findings in analyses using EASL criteria. On multivariable logistic regression adjusting for age, sex, cirrhosis, and ethnicity plus region, female sex was associated with adequate evaluation (adjusted odds ratio [aOR] 1.13, p = 0.004), but female treatment-eligible patients were about 50% less likely to initiate NAs (aOR 0.54, p <0.001). Additionally, the lowest evaluation and treatment rates were among Asian patients from the West, but no difference was observed between non-Asian patients and Asian patients from the East. Asian patients from the West (vs. East) were about 40-50% less likely to undergo adequate evaluation (aOR 0.60) and initiate NAs (aOR 0.54) (both p <0.001). CONCLUSIONS: Evaluation and treatment rates were suboptimal for patients with CHB in both the East and West, with significant sex and ethnic disparities. Improved linkage to care with linguistically competent and culturally sensitive approaches is needed. IMPACT AND IMPLICATIONS: Significant sex and ethnic disparities exist in hepatitis B evaluation and treatment, with female treatment-eligible patients about 50% less likely to receive antiviral treatment and Asian patients from Western regions also about 50% less likely to receive adequate evaluation or treatment compared to Asians from the East (there was no significant difference between Asian patients from the East and non-Asian patients). Improved linkage to care with linguistically competent and culturally sensitive approaches is needed.

Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial.

INTRODUCTION: Both artificial intelligence (AI) and distal attachment devices have been shown to improve adenoma detection rate and reduce miss rate during colonoscopy. We studied the combined effect of Endocuff and AI on enhancing detection rates of various colonic lesions. METHODS: This was a 3-arm prospective randomized colonoscopy study involving patients aged 40 years or older. Participants were randomly assigned in a 1:1:1 ratio to undergo Endocuff with AI, AI alone, or standard high-definition (HD) colonoscopy. The primary outcome was adenoma detection rate (ADR) between the Endocuff-AI and AI groups while secondary outcomes included detection rates of polyp (PDR), sessile serrated lesion (sessile detection rate [SDR]), and advanced adenoma (advanced adenoma detection rate) between the 2 groups. RESULTS: A total of 682 patients were included (mean age 65.4 years, 52.3% male), with 53.7% undergoing diagnostic colonoscopy. The ADR for the Endocuff-AI, AI, and HD groups was 58.7%, 53.8%, and 46.3%, respectively, while the corresponding PDR was 77.0%, 74.0%, and 61.2%. A significant increase in ADR, PDR, and SDR was observed between the Endocuff-AI and AI groups (ADR difference: 4.9%, 95% CI: 1.4%-8.2%, P = 0.03; PDR difference: 3.0%, 95% CI: 0.4%-5.8%, P = 0.04; SDR difference: 6.4%, 95% CI: 3.4%-9.7%, P < 0.01). Both Endocuff-AI and AI groups had a higher ADR, PDR, SDR, and advanced adenoma detection rate than the HD group (all P < 0.01). DISCUSSION: Endocuff in combination with AI further improves various colonic lesion detection rates when compared with AI alone.

Artificial intelligence-assisted real-time monitoring of effective withdrawal time during colonoscopy: a novel quality marker of colonoscopy.

BACKGROUND AND AIMS: The importance of withdrawal time during colonoscopy cannot be overstated in mitigating the risk of missed lesions and postcolonoscopy colorectal cancer. We evaluated a novel colonoscopy quality metric called the effective withdrawal time (EWT), which is an artificial intelligence (AI)-derived quantitative measure of quality withdrawal time, and its association with various colonic lesion detection rates as compared with standard withdrawal time (SWT). METHODS: Three hundred fifty video recordings of colonoscopy withdrawal (from the cecum to the anus) were assessed by the new AI model. The primary outcome was adenoma detection rate (ADR) according to different quintiles of EWT. Multivariate logistic regression, adjusting for baseline covariates, was used to determine the adjusted odd ratios (ORs) for EWT on lesion detection rates, with the lowest quintile as reference. The area under the receiver-operating characteristic curve of EWT was compared with SWT. RESULTS: The crude ADR in different quintiles of EWT, from lowest to highest, was 10.0%, 31.4%, 33.3%, 53.5%, and 85.7%. The ORs of detecting adenomas and polyps were significantly higher in all top 4 quintiles when compared with the lowest quintile. Each minute increase in EWT was associated with a 49% increase in ADR (aOR, 1.49; 95% confidence interval [CI], 1.36-1.65). The area under the receiver-operating characteristic curve of EWT was also significantly higher than SWT on adenoma detection (.80 [95% CI, .75-.84] vs .70 [95% CI, .64-.74], P < .01). CONCLUSIONS: AI-derived monitoring of EWT is a promising novel quality indicator for colonoscopy, which is more associated with ADR than SWT.

OpenCap: Human movement dynamics from smartphone videos.

Measures of human movement dynamics can predict outcomes like injury risk or musculoskeletal disease progression. However, these measures are rarely quantified in large-scale research studies or clinical practice due to the prohibitive cost, time, and expertise required. Here we present and validate OpenCap, an open-source platform for computing both the kinematics (i.e., motion) and dynamics (i.e., forces) of human movement using videos captured from two or more smartphones. OpenCap leverages pose estimation algorithms to identify body landmarks from videos; deep learning and biomechanical models to estimate three-dimensional kinematics; and physics-based simulations to estimate muscle activations and musculoskeletal dynamics. OpenCap's web application enables users to collect synchronous videos and visualize movement data that is automatically processed in the cloud, thereby eliminating the need for specialized hardware, software, and expertise. We show that OpenCap accurately predicts dynamic measures, like muscle activations, joint loads, and joint moments, which can be used to screen for disease risk, evaluate intervention efficacy, assess between-group movement differences, and inform rehabilitation decisions. Additionally, we demonstrate OpenCap's practical utility through a 100-subject field study, where a clinician using OpenCap estimated musculoskeletal dynamics 25 times faster than a laboratory-based approach at less than 1% of the cost. By democratizing access to human movement analysis, OpenCap can accelerate the incorporation of biomechanical metrics into large-scale research studies, clinical trials, and clinical practice.

Does prehabilitation before esophagectomy improve postoperative outcomes? A systematic review and meta-analysis.

Esophagectomy for esophageal cancer is associated with high morbidity. It remains unclear whether prehabilitation, a strategy aimed at optimizing patients' physical and mental functioning prior to surgery, improves postoperative outcomes. A systematic review and meta-analysis was conducted to evaluate the effect of prehabilitation on post-operative outcomes after esophagectomy. Data sources included Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, CINAHL, and PEDro, with information from 1 January 2000 to 5 August 2023. The analysis included randomized controlled trials and observational studies that compared prehabilitation interventions to standard care prior to esophagectomy. A random effects model was used to generate a pooled estimate for pairwise meta-analysis, meta-analysis of proportions, and meta-analysis of means. A total of 1803 patients were included with 584 in randomized controlled trials (RCTs) and 1219 in observational studies. In the randomized evidence, there were no significant differences between prehabilitation and control in the odds of postoperative pneumonia (15.0 vs. 18.9%, odds ratio (OR) 1.06 [95% confidence interval (CI): 0.66;1.72]) or pulmonary complications (14 vs. 25.6%, OR 0.68 [95% CI: 0.32;1.45]). In the observational data, there was a reduction in both postoperative pneumonia (22.5 vs. 32.9%, OR 0.48 [95% CI: 0.28;0.83]) and pulmonary complications (26.1 vs. 52.3%, OR 0.35 [95% CI: 0.17;0.75]) with prehabilitation. Hospital and intensive care unit length of stay (days), operative mortality, and severe complications (Clavien-Dindo ≥ 3) did not differ between groups in both the randomized data and observational data. Prehabilitation demonstrated reductions in postoperative pneumonia and pulmonary complications in observational studies, but not RCTs. The overall certainty of these findings is limited by the low quality of the available evidence.

Computer-assisted detection versus conventional colonoscopy for proximal colonic lesions: a multicenter, randomized, tandem-colonoscopy study.

BACKGROUND AND AIMS: Computer-assisted detection (CADe) is a promising technologic advance that enhances adenoma detection during colonoscopy. However, the role of CADe in reducing missed colonic lesions is uncertain. The aim of this study was to determine the miss rates of proximal colonic lesions by CADe and conventional colonoscopy. METHODS: This was a prospective, multicenter, randomized, tandem-colonoscopy study conducted in 3 Asian centers. Patients were randomized to receive CADe or conventional white-light colonoscopy during the first withdrawal of the proximal colon (cecum to splenic flexure), immediately followed by tandem examination of the proximal colon with white light in both groups. The primary outcome was adenoma/polyp miss rate, which was defined as any adenoma/polyp detected during the second examination. RESULTS: Of 223 patients (48.6% men; median age, 63 years) enrolled, 7 patients did not have tandem examination, leaving 108 patients in each group. There was no difference in the miss rate for proximal adenomas (CADe vs conventional: 20.0% vs 14.0%, P = .07) and polyps (26.7% vs 19.6%, P = .06). The CADe group, however, had significantly higher proximal polyp (58.0% vs 46.7%, P = .03) and adenoma (44.7% vs 34.6%, P = .04) detection rates than the conventional group. The mean number of proximal polyps and adenomas detected per patient during the first examination was also significantly higher in the CADe group (polyp: 1.20 vs .86, P = .03; adenoma, .91 vs .61, P = .03). Subgroup analysis showed that CADe enhanced proximal adenoma detection in patients with fair bowel preparation, shorter withdrawal time, and endoscopists with lower adenoma detection rate. CONCLUSIONS: This multicenter trial from Asia confirmed that CADe can further enhance proximal adenoma and polyp detection but may not be able to reduce the number of missed proximal colonic lesions. (Clinical trial registration number: NCT04294355.).

Blue-light imaging or narrow-band imaging for proximal colonic lesions: a prospective randomized tandem colonoscopy study.

BACKGROUND AND AIMS: Blue-light imaging (BLI) is a new image-enhanced endoscopy with a wavelength filter similar to narrow-band imaging (NBI). We compared the 2 with white-light imaging (WLI) on proximal colonic lesion detection and miss rates. METHODS: In this 3-arm prospective randomized study with tandem examination of the proximal colon, we enrolled patients aged ≥40 years. Eligible patients were randomized in 1:1:1 ratio to receive BLI, NBI, or WLI during the first withdrawal from the proximal colon. The second withdrawal was performed using WLI in all patients. Primary outcomes were proximal polyp (pPDRs) and adenoma (pADRs) detection rates. Secondary outcomes were miss rates of proximal lesions found on tandem examination. RESULTS: Of 901 patients included (mean age, 64.7 years; 52.9% men), 48.1% underwent colonoscopy for screening or surveillance. The corresponding pPDRs of the BLI, NBI, and WLI groups were 45.8%, 41.6, and 36.6%, whereas the corresponding pADRs were 36.6%, 33.8%, and 28.3%. There was a significant difference in pPDR and pADR between BLI and WLI groups (difference, 9.2% [95% confidence interval {CI}, 3.3-16.9] and 8.3% [95% CI, 2.7-15.9]) and between NBI and WLI groups (difference, 5.0% [95% CI, 1.4-12.9] and 5.6% [95% CI, 2.1-13.3]). Proximal adenoma miss rates were significantly lower with BLI (19.4%) than with WLI (27.4%; difference, -8.0%; 95% CI, -15.8 to -.1) but not between NBI (27.2%) and WLI. CONCLUSIONS: Both BLI and NBI were superior to WLI on detecting proximal colonic lesions, but only BLI had lower proximal adenoma miss rates than WLI. (Clinical trial registration number: NCT03696992.).

Fabrication of Multifunctional Electronic Textiles Using Oxidative Restructuring of Copper into a Cu-Based Metal-Organic Framework.

This paper describes a novel synthetic approach for the conversion of zero-valent copper metal into a conductive two-dimensional layered metal-organic framework (MOF) based on 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP) to form Cu3(HHTP)2. This process enables patterning of Cu3(HHTP)2 onto a variety of flexible and porous woven (cotton, silk, nylon, nylon/cotton blend, and polyester) and non-woven (weighing paper and filter paper) substrates with microscale spatial resolution. The method produces conductive textiles with sheet resistances of 0.1-10.1 MΩ/cm2, depending on the substrate, and uniform conformal coatings of MOFs on textile swatches with strong interfacial contact capable of withstanding chemical and physical stresses, such as detergent washes and abrasion. These conductive textiles enable simultaneous detection and detoxification of nitric oxide and hydrogen sulfide, achieving part per million limits of detection in dry and humid conditions. The Cu3(HHTP)2 MOF also demonstrated filtration capabilities of H2S, with uptake capacity up to 4.6 mol/kgMOF. X-ray photoelectron spectroscopy and diffuse reflectance infrared spectroscopy show that the detection of NO and H2S with Cu3(HHTP)2 is accompanied by the transformation of these species to less toxic forms, such as nitrite and/or nitrate and copper sulfide and Sx species, respectively. These results pave the way for using conductive MOFs to construct extremely robust electronic textiles with multifunctional performance characteristics.

MicroRNA-150 (miR-150) and Diabetic Retinopathy: Is miR-150 Only a Biomarker or Does It Contribute to Disease Progression?

Diabetic retinopathy (DR) is a chronic disease associated with diabetes mellitus and is a leading cause of visual impairment among the working population in the US. Clinically, DR has been diagnosed and treated as a vascular complication, but it adversely impacts both neural retina and retinal vasculature. Degeneration of retinal neurons and microvasculature manifests in the diabetic retina and early stages of DR. Retinal photoreceptors undergo apoptosis shortly after the onset of diabetes, which contributes to the retinal dysfunction and microvascular complications leading to vision impairment. Chronic inflammation is a hallmark of diabetes and a contributor to cell apoptosis, and retinal photoreceptors are a major source of intraocular inflammation that contributes to vascular abnormalities in diabetes. As the levels of microRNAs (miRs) are changed in the plasma and vitreous of diabetic patients, miRs have been suggested as biomarkers to determine the progression of diabetic ocular diseases, including DR. However, few miRs have been thoroughly investigated as contributors to the pathogenesis of DR. Among these miRs, miR-150 is downregulated in diabetic patients and is an endogenous suppressor of inflammation, apoptosis, and pathological angiogenesis. In this review, how miR-150 and its downstream targets contribute to diabetes-associated retinal degeneration and pathological angiogenesis in DR are discussed. Currently, there is no effective treatment to stop or reverse diabetes-caused neural and vascular degeneration in the retina. Understanding the molecular mechanism of the pathogenesis of DR may shed light for the future development of more effective treatments for DR and other diabetes-associated ocular diseases.

MicroRNA-150 and its target ETS-domain transcription factor 1 contribute to inflammation in diabetic photoreceptors.

Obesity-associated type 2 diabetes (T2D) is on the rise in the United States due to the obesity epidemic, and 60% of T2D patients develop diabetic retinopathy (DR) in their lifetime. Chronic inflammation is a hallmark of obesity and T2D and a well-accepted major contributor to DR, and retinal photoreceptors are a major source of intraocular inflammation and directly contribute to vascular abnormalities in diabetes. However, how diabetic insults cause photoreceptor inflammation is not well known. In this study, we used a high-fat diet (HFD)-induced T2D mouse model and cultured photoreceptors treated with palmitic acid (PA) to decipher major players that mediate high-fat-induced photoreceptor inflammation. We found that PA-elicited microRNA-150 (miR-150) decreases with a consistent upregulation of ETS-domain transcription factor 1 (Elk1), a downstream target of miR-150, in PA-elicited photoreceptor inflammation. We compared wild-type (WT) and miR-150 null (miR-150-/- ) mice fed with an HFD and found that deletion of miR-150 exacerbated HFD-induced photoreceptor inflammation in conjunction with upregulated ELK1. We further delineated the critical cellular localization of phosphorylated ELK1 at serine 383 (pELK1S383 ) and found that decreased miR-150 exacerbated the T2D-induced inflammation in photoreceptors by upregulating ELK1 and pELK1S383 , and knockdown of ELK1 alleviated PA-elicited photoreceptor inflammation.

New insights on missed colonic lesions during colonoscopy through artificial intelligence-assisted real-time detection (with video).

BACKGROUND AND AIMS: Meta-analysis shows that up to 26% of adenomas could be missed during colonoscopy. We investigated whether the use of artificial intelligence (AI)-assisted real-time detection could provide new insights into mechanisms underlying missed lesions during colonoscopy. METHODS: A validated real-time deep-learning AI model for the detection of colonic polyps was first tested in videos of tandem colonoscopy of the proximal colon for missed lesions. The real-time AI model was then prospectively validated in a total colonoscopy in which the endoscopist was blinded to real-time AI findings. Segmental unblinding of the AI findings were provided, and the colonic segment was then re-examined when missed lesions were detected by AI but not the endoscopist. All polyps were removed for histologic examination as the criterion standard. RESULTS: Sixty-five videos of tandem examination of the proximal colon were reviewed by AI. AI detected 79.1% (19/24) of missed proximal adenomas in the video of the first-pass examination. In 52 prospective colonoscopies, real-time AI detection detected at least 1 missed adenoma in 14 patients (26.9%) and increased the total number of adenomas detected by 23.6%. Multivariable analysis showed that a missed adenoma(s) was more likely when there were multiple polyps (adjusted odds ratio, 1.05; 95% confidence interval, 1.02-1.09; P < .0001) or colonoscopy was performed by less-experienced endoscopists (adjusted odds ratio, 1.30; 95% confidence interval, 1.05-1.62; P = .02). CONCLUSIONS: Our findings provide new insights on the prominent role of human factors, including inexperience and distraction, on missed colonic lesions. With the use of real-time AI assistance, up to 80% of missed adenomas could be prevented. (Clinical trial registration number: NCT04227795.).

Mechanistic Investigation of the Formation of Isoindole N-Oxides in the Electron Transfer-Mediated Oxidative Cyclization of 2'-Alkynylacetophenone Oximes.

This paper describes a joint experiment-theory investigation of the formation and cyclization of 2'-alkynylacetophenone oxime radical cations using photoinduced electron transfer (PET) with DCA as the photosensitizer. Using a combination of experimental 1H and 13C nuclear magnetic resonance (NMR) spectra, high-resolution mass spectrometry, and calculated NMR chemical shifts, we identified the products to be isoindole N-oxides. The reaction was found to be stereoselective; only one of the two possible stereoisomers is formed under these conditions. A detailed computational investigation of the cyclization reaction mechanism suggests facile C-N bond formation in the radical cation leading to a 5-exo intermediate. Back-electron transfer from the DCA radical anion followed by barrierless intramolecular proton transfer leads to the final product. We argue that the final proton transfer step in the mechanism is responsible for the stereoselectivity observed in experiment. As a whole, this work provides new insights into the formation of complex heterocycles through oxime and oxime ether radical cation intermediates produced via PET. Moreover, it represents the first reported formation of isoindole N-oxides.

Improving hospital readmission prediction using individualized utility analysis.

OBJECTIVE: Machine learning (ML) models for allocating readmission-mitigating interventions are typically selected according to their discriminative ability, which may not necessarily translate into utility in allocation of resources. Our objective was to determine whether ML models for allocating readmission-mitigating interventions have different usefulness based on their overall utility and discriminative ability. MATERIALS AND METHODS: We conducted a retrospective utility analysis of ML models using claims data acquired from the Optum Clinformatics Data Mart, including 513,495 commercially-insured inpatients (mean [SD] age 69 [19] years; 294,895 [57%] Female) over the period January 2016 through January 2017 from all 50 states with mean 90 day cost of $11,552. Utility analysis estimates the cost, in dollars, of allocating interventions for lowering readmission risk based on the reduction in the 90-day cost. RESULTS: Allocating readmission-mitigating interventions based on a GBDT model trained to predict readmissions achieved an estimated utility gain of $104 per patient, and an AUC of 0.76 (95% CI 0.76, 0.77); allocating interventions based on a model trained to predict cost as a proxy achieved a higher utility of $175.94 per patient, and an AUC of 0.62 (95% CI 0.61, 0.62). A hybrid model combining both intervention strategies is comparable with the best models on either metric. Estimated utility varies by intervention cost and efficacy, with each model performing the best under different intervention settings. CONCLUSION: We demonstrate that machine learning models may be ranked differently based on overall utility and discriminative ability. Machine learning models for allocation of limited health resources should consider directly optimizing for utility.

Employing Conductive Metal-Organic Frameworks for Voltammetric Detection of Neurochemicals.

This paper describes the first implementation of an array of two-dimensional (2D) layered conductive metal-organic frameworks (MOFs) as drop-casted film electrodes that facilitate voltammetric detection of redox active neurochemicals in a multianalyte solution. The device configuration comprises a glassy carbon electrode modified with a film of conductive MOF (M3HXTP2; M = Ni, Cu; and X = NH, 2,3,6,7,10,11-hexaiminotriphenylene (HITP) or O, 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP)). The utility of 2D MOFs in voltammetric sensing is measured by the detection of ascorbic acid (AA), dopamine (DA), uric acid (UA), and serotonin (5-HT) in 0.1 M PBS (pH = 7.4). In particular, Ni3HHTP2 MOFs demonstrated nanomolar detection limits of 63 ± 11 nM for DA and 40 ± 17 nM for 5-HT through a wide concentration range (40 nM-200 µM). The applicability in biologically relevant detection was further demonstrated in simulated urine using Ni3HHTP2 MOFs for the detection of 5-HT with a nanomolar detection limit of 63 ± 11 nM for 5-HT through a wide concentration range (63 nM-200 µM) in the presence of a constant background of DA. The implementation of conductive MOFs in voltammetric detection holds promise for further development of highly modular, sensitive, selective, and stable electroanalytical devices.

Linked color imaging versus narrow-band imaging for colorectal polyp detection: a prospective randomized tandem colonoscopy study.

BACKGROUND AND AIMS: Linked color imaging (LCI) is a newly available image-enhanced endoscopy (IEE) system that emphasizes the red mucosal color. No study has yet compared LCI with other available IEE systems. Our aim was to investigate polyp detection rates using LCI compared with narrow-band imaging (NBI). METHODS: This is a prospective randomized tandem colonoscopy study. Eligible patients who underwent colonoscopy for symptoms or screening/surveillance were randomized in a 1:1 ratio to receive tandem colonoscopy with both colonoscope withdrawals using LCI or NBI. The primary outcome was the polyp detection rate. RESULTS: Two hundred seventy-two patients were randomized (mean age, 62 years; 48.2% male; colonoscopy for symptoms, 72.8%) with 136 in each arm. During the first colonoscopy, the polyp detection rate (71.3% vs 55.9%; P = .008), serrated lesion detection rate (34.6% vs 22.1%; P = .02), and mean number of polyps detected (2.04 vs 1.35; P = .02) were significantly higher in the NBI group than in the LCI group. There was also a trend of higher adenoma detection rate in the NBI group compared with the LCI group (51.5% vs 39.7%, respectively; P = .05). Multivariable analysis confirmed that use of NBI (adjusted odds ratio, 1.99; 95% confidence interval, 1.09-3.68) and withdrawal time >8 minutes (adjusted odds ratio, 5.11; 95% confidence interval, 2.79-9.67) were associated with polyp detection. Overall, 20.5% of polyps and 18.1% of adenomas were missed by the first colonoscopy, but there was no significant difference in the miss rates between the 2 groups. CONCLUSION: NBI was significantly better than LCI for colorectal polyp detection. However, both LCI and NBI missed 20.5% of polyps. (Clinical trial registration number: NCT03336359.).

Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments.

BACKGROUND: Risk adjustment models are employed to prevent adverse selection, anticipate budgetary reserve needs, and offer care management services to high-risk individuals. We aimed to address two unknowns about risk adjustment: whether machine learning (ML) and inclusion of social determinants of health (SDH) indicators improve prospective risk adjustment for health plan payments. METHODS: We employed a 2-by-2 factorial design comparing: (i) linear regression versus ML (gradient boosting) and (ii) demographics and diagnostic codes alone, versus additional ZIP code-level SDH indicators. Healthcare claims from privately-insured US adults (2016-2017), and Census data were used for analysis. Data from 1.02 million adults were used for derivation, and data from 0.26 million to assess performance. Model performance was measured using coefficient of determination (R2), discrimination (C-statistic), and mean absolute error (MAE) for the overall population, and predictive ratio and net compensation for vulnerable subgroups. We provide 95% confidence intervals (CI) around each performance measure. RESULTS: Linear regression without SDH indicators achieved moderate determination (R2 0.327, 95% CI: 0.300, 0.353), error ($6992; 95% CI: $6889, $7094), and discrimination (C-statistic 0.703; 95% CI: 0.701, 0.705). ML without SDH indicators improved all metrics (R2 0.388; 95% CI: 0.357, 0.420; error $6637; 95% CI: $6539, $6735; C-statistic 0.717; 95% CI: 0.715, 0.718), reducing misestimation of cost by $3.5 M per 10,000 members. Among people living in areas with high poverty, high wealth inequality, or high prevalence of uninsured, SDH indicators reduced underestimation of cost, improving the predictive ratio by 3% (~$200/person/year). CONCLUSIONS: ML improved risk adjustment models and the incorporation of SDH indicators reduced underpayment in several vulnerable populations.

Serum Mac-2-binding protein glycosylation isomer and risk of hepatocellular carcinoma in entecavir-treated chronic hepatitis B patients.

BACKGROUND AND AIM: Hepatocellular carcinoma (HCC) can still develop in chronic hepatitis B (CHB) patients receiving antiviral treatment. Serum Mac-2-binding protein glycosylation isomer (M2BPGi) is a novel marker for liver fibrosis. We investigated its role on incidence of HCC in entecavir (ETV)-treated CHB patients. METHODS: We identified HCC cases diagnosed at ≥ 1 year of ETV treatment. CHB patients without HCC (matched for age, gender, baseline hepatitis B virus-DNA, and duration of ETV treatment) were identified in approximately 1:2 ratio (HCC: non-HCC) for comparison. Serum samples were retrieved at baseline (initiation of ETV), 3, and 5 years of ETV for serum M2BPGi measurement (expressed in cut-off index [COI]). RESULTS: One hundred HCC cases were matched with 185 CHB patients without HCC (median age 56.7 years, 78.9% male, baseline hepatitis B virus-DNA 5.6 logIU/mL, and median follow-up 7.1 years). Median time from ETV initiation to incident HCC was 3.9 years. Serum M2BPGi levels were significantly higher in HCC cases compared with controls at baseline and year 3 (1.25 vs 0.98 [P = 0.004], 0.89 vs 0.74 [P = 0.018] COI, respectively). Multivariate analysis showed that baseline M2BPGi was the only independent factor associated with incident HCC (odds ratio 1.241, 95% confidence interval 1.039-1.482, P = 0.017). Using a cut-off value of 1.15 COI, the sensitivity, specificity, positive predictive value, and negative predictive value of baseline serum M2BPGi in cirrhotic patients to predict incident HCC were 90%, 53.8%, 69.6%, and 82.1%, respectively. CONCLUSIONS: Baseline and 3-year serum M2BPGi may be useful to identify high risk patients on antiviral treatment for subsequent HCC development.

Porous Scaffolds for Electrochemically Controlled Reversible Capture and Release of Ethylene.

This Communication describes the use of porous coordination polymers (PCP) with integrated metal bis(dithiolene) units to achieve electrochemically controlled capture and release of ethylene in the solid state. Applying positive potential (+2.0 V) to these PCPs promotes ethylene capture, and subsequent dose of negative potential (-2.0 V) induces the release. These materials are resistant to poisoning by small reactive gases (CO and H2S) that may interact with embedded metallic sites.

Drawing Sensors with Ball-Milled Blends of Metal-Organic Frameworks and Graphite.

The synthetically tunable properties and intrinsic porosity of conductive metal-organic frameworks (MOFs) make them promising materials for transducing selective interactions with gaseous analytes in an electrically addressable platform. Consequently, conductive MOFs are valuable functional materials with high potential utility in chemical detection. The implementation of these materials, however, is limited by the available methods for device incorporation due to their poor solubility and moderate electrical conductivity. This manuscript describes a straightforward method for the integration of moderately conductive MOFs into chemiresistive sensors by mechanical abrasion. To improve electrical contacts, blends of MOFs with graphite were generated using a solvent-free ball-milling procedure. While most bulk powders of pure conductive MOFs were difficult to integrate into devices directly via mechanical abrasion, the compressed solid-state MOF/graphite blends were easily abraded onto the surface of paper substrates equipped with gold electrodes to generate functional sensors. This method was used to prepare an array of chemiresistors, from four conductive MOFs, capable of detecting and differentiating NH3, H2S and NO at parts-per-million concentrations.