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PURPOSE: Pancreatic cancer is one of the most malignant cancers with poor survival. The latest edition of the American Joint Committee on Cancer (AJCC) staging system classifies the majority of operable pancreatic cancer patients as stage-III, while dramatic heterogeneity is observed among these patients. Therefore, subgrouping is required to accurately predict their prognosis and define a treatment plan. This study conducts a cohort study to provide a more precise classification system for stage-III pancreatic cancer patients by utilizing clinical variables. METHODS: We analyzed survival using log-rank tests, univariate Cox-regression models, and Kaplan-Meier survival curves for stage-III pancreatic ductal adenocarcinoma (PDAC) patients from the Taiwan Cancer Registry (TCR). Patients were further divided into subgroups using classification and regression tree (CART) algorithm. All results were validated using the SEER database. RESULTS: Among stage-III PDAC patients, lymph node and tumor grade showed significant association with survival. Patients with N2 stage had higher mortality risks (hazard ratio [HR] = 2.30, 95% confidence interval [CI] 1.71-3.08, p < 0.0001) than N0 patients. Patients with grade 3 also had higher risk of mortality (HR = 3.80, 95% CI 2.25-6.39, p < 0.0001) than grade 1 patients. The CART algorithm stratified stage-III patients into four subgroups with significantly different survival rates. The median survival of the four subgroups was 23.5, 18.4, 14.5, and 9.0 months, respectively (p < 0.0001). Similar results were observed with SEER data. CONCLUSIONS: Lymph node involvement and tumor grade are predictive factors for survival in stage-III PDAC patients. This new precise classification system can be used to guide treatment planning in advanced-stage pancreatic cancer.
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Neoplasias Pancreáticas , Estudios de Cohortes , Humanos , Estadificación de Neoplasias , Neoplasias Pancreáticas/patología , Neoplasias Pancreáticas/cirugía , Pronóstico , Sistema de Registros , Programa de VERF , Taiwán/epidemiologíaRESUMEN
PURPOSE: Colon cancer is the third most incident and life-threatening cancer in Taiwan. A comprehensive survival prediction system would greatly benefit clinical practice in this area. This study was designed to develop an accurate prognostic model for colon cancer patients by using clinicopathological variables obtained from the Taiwan Cancer Registry database. METHODS: We analyzed 20,218 colon cancer patients from the Taiwan Cancer Registry database, who were diagnosed between 2007 and 2015, were followed up until December 31, 2017, and had undergone curative surgery. We proposed two prognostic models, with different combinations of predictors. The first model used only traditional clinical features. The second model included several colon cancer site-specific factors (circumferential resection margin, perineural invasion, obstruction, and perforation), in addition to the traditional features. Both prediction models were developed by using a Cox proportional hazards model. Furthermore, we investigated whether race is a significant predictor of survival in colon cancer patients by using Model 1 on the Surveillance, Epidemiology, and End Results (SEER) cancer registry dataset. RESULTS: The proposed models displayed a robust prediction performance (all Harrell's c-index >0.8). For both the calibration and validation steps, the differences between the predicted and observed mortality were mostly less than 5%. CONCLUSIONS: The prediction model (Model 1) is an effective predictor of survival regardless of the ethnic background of patients and can potentially help to provide better prediction of colon cancer-specific survival outcomes, thus allowing physicians to improve treatment plans.
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Neoplasias del Colon , Neoplasias del Colon/patología , Humanos , Estadificación de Neoplasias , Pronóstico , Modelos de Riesgos Proporcionales , Sistema de Registros , Programa de VERF , Taiwán/epidemiologíaRESUMEN
Photodetectors based on reduced graphene oxide (rGO) have attracted much attention owing to their simple and low-cost fabrication process. However, the aggregation and defects of rGO flakes still limit the performance of rGO photodetectors. Controlling the composition of rGO has become a vital factor for its prospective applications. For example, the interconnection between rGO and polymers for modified morphologies of rGO films leads to an enhanced performance of devices. In this work, a practical approach to engineer surface uniformity and enhance the performance of a photodetector by modifying the rGO film with hydrophilic polymers poly(vinyl alcohol) (PVA) is reported. Compared with the rGO photodetector, the on/off ratio for the PVA/rGO photodetector shows 3.5 times improvement, and the detectivity shows 53% enhancement even when the photodetector is operated at a low bias of 0.3 V. This study provides an effective route to realize PVA/rGO photodetectors with a low-power operation which shows promising opportunities for the future development of green systems.
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During an investigation of microbes associated with arthropods living in decaying coconut trees, a Pseudomonas isolate, Milli4T, was cultured from the digestive tract of the common Asian millipede, Trigoniulus corallinus. Sequence analysis of 16S rRNA and rpoB genes found that Milli4T was closely related but not identical to Pseudomonas panipatensis Esp-1T, Pseudomonas knackmussi B13T and Pseudomonas humi CCA1T. Whole genome sequencing suggested that this isolate represents a new species, with average nucleotide identity (OrthoANIu) values of around 83.9-87.7% with its closest relatives. Genome-to-genome distance calculations between Milli4T and its closest relatives also suggested they are distinct species. The genomic DNA G+C content of Milli4T was approximately 65.0 mol%. Phenotypic and chemotaxonomic characterization and fatty acid methyl ester analysis was performed on Milli4T and its related type strains. Based on these data, the new species Pseudomonas schmalbachii sp. nov. is proposed, and the type strain is Milli4T (=BCRC 81294T=JCM 34414T=CIP 111980T).
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Artrópodos , Filogenia , Pseudomonas/clasificación , Animales , Artrópodos/microbiología , Técnicas de Tipificación Bacteriana , Composición de Base , Cocos , ADN Bacteriano/genética , Ácidos Grasos/química , Hibridación de Ácido Nucleico , Pseudomonas/aislamiento & purificación , ARN Ribosómico 16S/genética , Análisis de Secuencia de ADNRESUMEN
In this study, poly(N-vinylcarbazole) (PVK) polymer was blended with various dimensional CdSe/ZnS core-shell quantum dots to be used as a single emissive layer of white quantum dots light-emitting diodes (WQLEDs). Besides, the nanostructured ITO/ZnO nanorod array was used as electron transport/injection layer to shorten carrier transport distance, accelerate carrier transport velocity, and enhance carrier transport surface area. Consequently, luminance and luminous efficiency were increased by the resulting increase of the carrier injection current density and the hole-electron recombination opportunity. The CIE of (0.329, 0.331) was obtained for the WQLEDs by using the weight ratio of 1.5:1.3:2.2 of the red, green, and blue (RGB) quantum dots. Compared with the WQLEDs without the nanorod array, the WQLEDs with the 1.5-µm-periodic ITO/ZnO nanorod array obtained an increased luminance of 16333 cd/m2 (compared with 7191 cd/m2) and an increased luminous efficiency of 3.13 cd/A (compared with 2.30 cd/A).
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In the study, the yttrium (Y)-doped vanadium oxide (VOx:Y) films used as the sensitive layers of microbolometers were deposited using a radio frequency magnetron co-sputtering system. The temperature coefficient of resistance (TCR) of the VOx:Y films was enhanced from -1.88%/°C to -2.85%/°C in comparison with that of the VOx films. To further improve the performance of microbolometers, the nanomesh antireflection layer was placed on the top surface of the microbolometers to reduce the infrared reflection. The responsivity, thermal time constant, thermal conductivity, absorptance, and detectivity of the VOx:Y microbolometers with nanomesh antireflection layer were 931.89 ± 48 kV/W, 4.48 ms, 6.19×10-8 W/K, 74.41% and 2.20×108 cmHz0.5W-1, respectively.
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In this work, Ga2O3 films were deposited on sapphire substrates using a plasma-enhanced atomic layer deposition system with trimethylgallium precursor and oxygen (O2) plasma. To improve the quality of Ga2O3 films, they were annealed in an O2 ambient furnace system for 15 min at 700, 800, and 900 °C, respectively. The performance improvement was verified from the measurement results of X-ray diffraction, X-ray photoelectron spectroscopy, and photoluminescence spectroscopy. The optical bandgap energy of the Ga2O3 films decreased with an increase of annealing temperatures. Metal-semiconductor-metal ultraviolet C photodetectors (MSM UVC-PDs) with various Ga2O3 active layers were fabricated and studied in this work. The cut-off wavelength of the MSM UVC-PDs with the Ga2O3 active layers annealed at 800 °C was 250 nm. Compared with the performance of the MSM UVC-PDs with the as-grown Ga2O3 active layers, the MSM UVC-PDs with the 800 °C-annealed Ga2O3 active layers under a bias voltage of 5 V exhibited better performances including photoresponsivity of 22.19 A/W, UV/visible rejection ratio of 5.98 × 104, and detectivity of 8.74 × 1012 cmHz1/2W-1.
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This article describes a high-efficiency light-induced dielectrophoresis biochip containing a thin film prepared through inductively coupled plasma chemical vapor deposition (ICPCVD). The biochip comprises two ITO glass substrates and a photoconductive amorphous silicon thin film. The biochip can effectively sort particular particles (or cells) by projecting visible light onto the surface of the silicon thin film. The sorting efficiency of biochips is highly associated with the quality of the deposited amorphous silicon thin films; therefore, the choice of deposition technique is extremely critical. However, no study has examined this problem. Hence, the current study thoroughly compared the efficiency of the biochip when films produced through plasma-enhanced chemical vapor deposition and ICPCVD are used.
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Electroforesis/instrumentación , Dispositivos Laboratorio en un Chip , Luz , Gases em Plasma/química , Impedancia Eléctrica , VolatilizaciónRESUMEN
The combination of ZnO, InN, and GaN epitaxial layers is explored to provide long wavelength photodetection capability in the GaN based materials. Growth temperature optimization was performed to obtain the best quality of InN epitaxial layer in the MOCVD system. The temperature dependent photoluminescence (PL) can provide the information about thermal quenching in the InN PL transitions and at least two non-radiative processes can be observed. X-ray diffraction and energy dispersive spectroscopy are applied to confirm the inclusion of indium and the formation of InN layer. The band alignment of such system shows a typical double heterojunction, which is preferred in optoelectronic device operation. The photodetector manufactured by this ZnO/GaN/InN layer can exhibit extended long-wavelength quantum efficiency, as high as 3.55%, and very strong photocurrent response under solar simulator illumination.
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With CO2 laser assistance, crystalline Ge nanocluster-embedded Ge films were deposited at low temperature using a conventional plasma-enhanced chemical vapor deposition system. Raman spectrum showed a wavenumber peak at 290 cm(-1) which corresponded to the crystalline Ge nanoclusters in the Ge film deposited with CO2 laser assistance. Crystalline Ge nanoclusters embedded in Ge matrices were observed from transmission electron microscopy (TEM) images and electron diffraction pattern. The electroluminescent devices constructed with multilayered Ge nanoclusters-embedded Ge films were fabricated. The experimental results demonstrated that the electroluminescence emission originated from the radiative recombination of the electron-hole pairs in the Ge nanoclusters.
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In this work, guanidinium (GA+) was doped into methylammonium lead triiodide (MAPbI3) perovskite film to fabricate perovskite solar cells (PSCs). To determine the optimal formulation of the resulting guanidinium-doped MAPbI3 ((GA)x(MA)1-xPbI3) for the perovskite active layer in PSCs, the perovskite films with various GA+ doping concentrations, annealing temperatures, and thicknesses were systematically modulated and studied. The experimental results demonstrated a 400-nm-thick (GA)x(MA)1-xPbI3 film, with 5% GA+ doping and annealed at 90 °C for 20 min, provided optimal surface morphology and crystallinity. The PSCs configured with the optimal (GA)x(MA)1-xPbI3 perovskite active layer exhibited an open-circuit voltage of 0.891 V, a short-circuit current density of 24.21 mA/cm2, a fill factor of 73.1%, and a power conversion efficiency of 15.78%, respectively. Furthermore, the stability of PSCs featuring this optimized (GA)x(MA)1-xPbI3 perovskite active layer was significantly enhanced.
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In this work, a vapor cooling condensation system was utilized to deposit various amounts of p-type gold-black nanoparticles (NPs) onto the surface of n-type gallium oxide (Ga2O3) nanorods forming p-n heterojunction-structured sensing membranes of nitrogen dioxide (NO2) gas sensors. The role and the sensing mechanism of the various gold-black NP-decorated Ga2O3 nanorods in NO2 gas sensors were investigated. The coverage and atomic percentage of the sensing membranes were observed using high-resolution transmission electron microscopy (HRTEM) measurements and energy-dispersive spectroscopy (EDS), respectively. For the NO2 gas sensor using the sensing membrane of 60 s-deposited gold-black NP-decorated Ga2O3 nanorods under a NO2 concentration of 10 ppm, the highest responsivity of 5221.1% was obtained. This result was attributed to the spillover effect and the formation of the p-n heterojunction, which increased more ionized-oxygen adsorption sites and promoted the reaction between NO2 gas and Ga2O3 nanorods. Furthermore, the NO2 gas sensor could detect the low NO2 concentration of 100 ppb and achieved a responsivity of 56.9%. The resulting NO2 gas sensor also exhibited excellent selectivity for detecting NO2 gas, with higher responsivity at a NO2 concentration of 10 ppm compared with that of the C2H5OH and NH3 concentrations of 100 ppm.
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Nanotubos , Dióxido de Nitrógeno , Adsorción , Gases , OroRESUMEN
Background: Early identification of impending in-hospital cardiac arrest (IHCA) improves clinical outcomes but remains elusive for practicing clinicians. Objective: We aimed to develop a multimodal machine learning algorithm based on ensemble techniques to predict the occurrence of IHCA. Methods: Our model was developed by the Multiparameter Intelligent Monitoring of Intensive Care (MIMIC)-IV database and validated in the Electronic Intensive Care Unit Collaborative Research Database (eICU-CRD). Baseline features consisting of patient demographics, presenting illness, and comorbidities were collected to train a random forest model. Next, vital signs were extracted to train a long short-term memory model. A support vector machine algorithm then stacked the results to form the final prediction model. Results: Of 23,909 patients in the MIMIC-IV database and 10,049 patients in the eICU-CRD database, 452 and 85 patients, respectively, had IHCA. At 13 hours in advance of an IHCA event, our algorithm had already demonstrated an area under the receiver operating characteristic curve of 0.85 (95% CI 0.815-0.885) in the MIMIC-IV database. External validation with the eICU-CRD and National Taiwan University Hospital databases also presented satisfactory results, showing area under the receiver operating characteristic curve values of 0.81 (95% CI 0.763-0.851) and 0.945 (95% CI 0.934-0.956), respectively. Conclusions: Using only vital signs and information available in the electronic medical record, our model demonstrates it is possible to detect a trajectory of clinical deterioration up to 13 hours in advance. This predictive tool, which has undergone external validation, could forewarn and help clinicians identify patients in need of assessment to improve their overall prognosis.
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This study evaluates the effect of crystallinity and point defects on time-dependent photoresponsivity and the cathodoluminescence (CL) properties of ß-Ga2O3 epilayers. A synchrotron high-resolution X-ray technique was used to understand the crystalline structure of samples. Rutherford backscattering spectroscopy was used to determine the net chemical composition of the samples to examine the type and ratio of their possible point defects. The results show that in functional time-dependent photoresponsivity of photodetectors based on ß-Ga2O3 epilayers, point defects contribution overcomes the contribution of crystallinity. However, the crystalline structure affects the intensities and emission regions of CL spectra more than point defects.
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Due to its high carrier mobility and electron transmission, the phenyl-C61-butyric acid methyl ester (PC61BM) is usually used as an electron transport layer (ETL) in perovskite solar cell (PSC) configurations. However, PC61BM films suffer from poor coverage on perovskite active layers because of their low solubility and weak adhesive ability. In this work, to overcome the above-mentioned shortcomings, 30 nm thick PC61BM ETLs with different concentrations were modeled. Using a 30 nm thick PC61BM ETL with a concentration of 50 mg/mL, the obtained performance values of the PSCs were as follows: an open-circuit voltage (Voc) of 0.87 V, a short-circuit current density (Jsc) of 20.44 mA/cm2, a fill factor (FF) of 70.52%, and a power conversion efficiency (PCE) of 12.54%. However, undesired fine cracks present on the PC61BM surface degraded the performance of the resulting PSCs. To further improve performance, multiple different thicknesses of ZnO interface layers were deposited on the PC61BM ETLs to release the fine cracks using a thermal evaporator. In addition to the pavement of fine cracks, the ZnO interface layer could also function as a hole-blocking layer due to its larger highest occupied molecular orbital (HOMO) energy level. Consequently, the PCE was improved to 14.62% by inserting a 20 nm thick ZnO interface layer in the PSCs.
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In this work, Ga2O3 nanorods were converted from GaOOH nanorods grown using the hydrothermal synthesis method as the sensing membranes of NO2 gas sensors. Since a sensing membrane with a high surface-to-volume ratio is a very important issue for gas sensors, the thickness of the seed layer and the concentrations of the hydrothermal precursor gallium nitrate nonahydrate (Ga(NO3)3·9H2O) and hexamethylenetetramine (HMT) were optimized to achieve a high surface-to-volume ratio in the GaOOH nanorods. The results showed that the largest surface-to-volume ratio of the GaOOH nanorods could be obtained using the 50-nm-thick SnO2 seed layer and the Ga(NO3)3·9H2O/HMT concentration of 12 mM/10 mM. In addition, the GaOOH nanorods were converted to Ga2O3 nanorods by thermal annealing in a pure N2 ambient atmosphere for 2 h at various temperatures of 300 °C, 400 °C, and 500 °C, respectively. Compared with the Ga2O3 nanorod sensing membranes annealed at 300 °C and 500 °C, the NO2 gas sensors using the 400 °C-annealed Ga2O3 nanorod sensing membrane exhibited optimal responsivity of 1184.6%, a response time of 63.6 s, and a recovery time of 135.7 s at a NO2 concentration of 10 ppm. The low NO2 concentration of 100 ppb could be detected by the Ga2O3 nanorod-structured NO2 gas sensors and the achieved responsivity was 34.2%.
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Terahertz (THz) plasmonic metamaterial, based on a metal-wire-woven hole array (MWW-HA), is investigated for the distinct power depletion in the transmittance spectrum of 0.1-2 THz, including the reflected waves from metal holes and woven metal wires. Woven metal wires have four orders of power depletion, which perform sharp dips in a transmittance spectrum. However, only the first-order dip at the metal-hole-reflection band dominates specular reflection with a phase retardation of approximately π. The optical path length and metal surface conductivity are modified to study MWW-HA specular reflection. This experimental modification shows that the first order of MWW-HA power depletion is sustainable and sensitively correlated with a bending angle of the woven metal wire. Specularly reflected THz waves are successfully presented in hollow-core pipe wave guidance specified from MWW-HA pipe wall reflectivity.
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Pulmonary hypertension should be preoperatively evaluated for optimal surgical planning to reduce surgical risk in lung cancer patients. Preoperative measurement of vascular diameter in computed tomography (CT) images is a noninvasive prediction method for pulmonary hypertension. However, the current estimation method, 2D manual arterial diameter measurement, may yield inaccurate results owing to low tissue contrast in non-contrast-enhanced CT (NECT). Furthermore, it provides an incomplete evaluation by measuring only the diameter of the arteries rather than the volume. To provide a more complete and accurate estimation, this study proposed a novel two-stage deep learning (DL) model for 3D aortic and pulmonary artery segmentation in NECT. In the first stage, a DL model was constructed to enhance the contrast of NECT; in the second stage, two DL models then applied the enhanced images for aorta and pulmonary artery segmentation. Overall, 179 patients were divided into contrast enhancement model (n = 59), segmentation model (n = 120), and testing (n = 20) groups. The performance of the proposed model was evaluated using Dice similarity coefficient (DSC). The proposed model could achieve 0.97 ± 0.66 and 0.93 ± 0.16 DSC for aortic and pulmonary artery segmentation, respectively. The proposed model may provide 3D diameter information of the arteries before surgery, facilitating the estimation of pulmonary hypertension and supporting preoperative surgical method selection based on the predicted surgical risks.
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Background: Preoperative two-dimensional manual measurement of pulmonary artery diameter in a single-cut axial view computed tomography (CT) image is a commonly used non-invasive prediction method for pulmonary hypertension. However, the accuracy may be unreliable. Thus, this study aimed to evaluate the correlation of short-term surgical outcomes and pulmonary artery/aorta (PA/Ao) diameter ratio measured by automated three-dimensional (3D) segmentation in lung cancer patients who underwent thoracoscopic lobectomy. Materials and methods: We included 383 consecutive lung cancer patients with thin-slice CT images who underwent lobectomy at a single institute between January 1, 2011 and December 31, 2019. Automated 3D segmentation models were used for 3D vascular reconstruction and measurement of the average diameters of Ao and PA. Propensity-score matching incorporating age, Charlson comorbidity index, and lobectomy performed by uniportal VATS was used to compare clinical outcomes in patients with PA/Ao ratio ≥1 and those <1. Results: Our segmentation method measured 29 (7.57%) patients with a PA/Ao ratio ≥1. After propensity-score matching, a higher overall postoperative complication classified by the Clavien-Dindo classification (p = 0.016) were noted in patients with 3D PA/Ao diameter ratio ≥1 than those of <1. By multivariate logistic regression, patients with a 3D PA/Ao ratio ≥ 1 (p = 0.013) and tumor diameter > 3 cm (p = 0.002) both significantly predict the incidence of postoperative complications. Conclusions: Pulmonary artery/aorta diameter ratio ≥ 1 measured by automated 3D segmentation may predict postoperative complications in lung cancer patients who underwent lobectomy.
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OBJECTIVE: Sepsis is the leading cause of in-hospital mortality in the United States (US). Quality improvement initiatives for improving sepsis care depend on accurate estimates of sepsis mortality. While hospital 30-day risk-standardized mortality rates have been published for patients hospitalized with acute myocardial infarction, heart failure, and pneumonia, risk-standardized mortality rates for sepsis have not been well characterized. We aimed to construct a sepsis risk-standardized mortality rate map for the United States, to illustrate disparities in sepsis care across the country. METHODS: This cross-sectional study included adults from the US Nationwide Inpatient Sample who were hospitalized with sepsis between 1 January 2010 and 30 December 2011. Hospital-level risk-standardized mortality rates were calculated using hierarchical logistic modelling, and were risk-adjusted with predicted mortality derived from (1) the Sepsis Risk Prediction Score, a logistic regression model, and (2) gradient-boosted decision trees, a supervised machine learning (ML) algorithm. RESULTS: Among 1,739,033 adults hospitalized with sepsis, 50% were female, and the median age was 71 years (interquartile range: 58-81). The national median risk-standardized mortality rate for sepsis was 18.4% (interquartile range: 17.0, 21.0) by the boosted tree model, which had better discrimination than the Sepsis Risk Prediction Score model (C-statistic 0.87 and 0.78, respectively). The highest risk-standardized mortality rates were found in Wyoming, North Dakota, and Mississippi, while the lowest were found in Arizona, Colorado, and Michigan. CONCLUSIONS: Wide variation exists in sepsis risk-standardized mortality rates across states, representing opportunities for improvement in sepsis care. This represents the first map of state-level variation of risk-standardized mortality rates in sepsis.