Key risk factors and adverse outcomes in metachronous vertebral osteomyelitis following periprosthetic joint infection: A 5-year retrospective study.

Purpose: Periprosthetic joint infection (PJI) is a leading cause of joint arthroplasty failure, potentially leading to critical complications like vertebral osteomyelitis (VO). The factors contributing to VO after PJI and the outcomes for these patients are not well understood. Our study aims to (1) identify risk factors for VO following PJI and (2) assess the clinical outcomes in these cases. Methods: We included PJI patients treated surgically at our centre from January 2006 to December 2020, excluding those with simultaneous VO post-PJI. Our focus was on patients with VO occurring after PJI, monitored for at least 5 years. Analysis included patient comorbidities, PJI treatment approaches, pathogen identification and clinical outcomes. Results: Of 1701 PJI cases, 21 (1.23%) developed VO. Key risk factors for VO post-PJI were identified: systemic inflammatory response syndrome, substance misuse, polymicrobial infection and undergoing at least three stages of resection arthroplasty (odds ratios: 1.86, 54.28, 52.33 and 31.88, respectively). Adverse outcomes were noted in VO patients, with recurrent VO in 6/21 and repeated PJIs in 18/21 cases. Conclusions: Patients with PJI, especially those with certain risk factors, have an increased likelihood of developing VO and encountering negative outcomes. The potential role of bacteremia in the development of VO after PJI needs further exploration. Level of Evidence: Level III.

Chameleon-inspired tunable multi-layered infrared-modulating system via stretchable liquid metal microdroplets in elastomer film.

This report presents liquid metal-based infrared-modulating materials and systems with multiple modes to regulate the infrared reflection. Inspired by the brightness adjustment in chameleon skin, shape-morphing liquid metal droplets in silicone elastomer (Ecoflex) matrix are used to resemble the dispersed "melanophores". In the system, Ecoflex acts as hormone to drive the deformation of liquid metal droplets. Both total and specular reflectance-based infrared camouflage are achieved. Typically, the total and specular reflectances show change of ~44.8% and 61.2%, respectively, which are among the highest values reported for infrared camouflage. Programmable infrared encoding/decoding is explored by adjusting the concentration of liquid metal and applying areal strains. By introducing alloys with different melting points, temperature-dependent infrared painting/writing can be achieved. Furthermore, the multi-layered structure of infrared-modulating system is designed, where the liquid metal-based infrared modulating materials are integrated with an evaporated metallic film for enhanced performance of such system.

Robust inference for causal mediation analysis of recurrent event data.

Recurrent events, including cardiovascular events, are commonly observed in biomedical studies. Understanding the effects of various treatments on recurrent events and investigating the underlying mediation mechanisms by which treatments may reduce the frequency of recurrent events are crucial tasks for researchers. Although causal inference methods for recurrent event data have been proposed, they cannot be used to assess mediation. This study proposed a novel methodology of causal mediation analysis that accommodates recurrent outcomes of interest in a given individual. A formal definition of causal estimands (direct and indirect effects) within a counterfactual framework is given, and empirical expressions for these effects are identified. To estimate these effects, a semiparametric estimator with triple robustness against model misspecification was developed. The proposed methodology was demonstrated in a real-world application. The method was applied to measure the effects of two diabetes drugs on the recurrence of cardiovascular disease and to examine the mediating role of kidney function in this process.

Sodium-Glucose Cotransporter 2 Inhibitors Reduce the Risk of Hospitalization for Heart Failure and Amputation Rate Compared With Incretin-Based Therapy in Patients With Diabetic Foot Disease: A Nationwide Population-Based Study.

OBJECTIVE: Major adverse cardiovascular event (MACE) outcomes associated with sodium-glucose cotransporter 2 inhibitor (SGLT2i) and glucagon-like peptide-1 receptor agonist (GLP-1 RA) therapies remain unclear in patients with type 2 diabetes and newly diagnosed diabetic foot complications (DFCs). This study examined the impact of SGLT2i and GLP-1 RA use on the rates of MACEs and amputations in patients with type 2 diabetes and without cardiovascular disease. METHODS: Data from the Taiwan National Health Insurance Research Database (2004-2017) were analyzed, focusing on patients with type 2 diabetes without previous MACE and newly diagnosed DFCs. The primary outcome was the first MACE occurrence, and the secondary outcomes included MACE components, all-cause mortality, and lower extremity amputation (LEA) rates. RESULTS: SGLT2i users showed a significant decrease in the MACE (hazard ratio [HR], 0.64; 95% confidence interval [CI], 0.46-0.88) and hospitalization for heart failure (HR, 0.54; 95% CI, 0.35-0.83) rates compared with dipeptidyl peptidase-4 inhibitor users. The amputation rates were also lower in SGLT2i users without LEA at the first DFC diagnosis (HR, 0.28; 95% CI, 0.10-0.75) and did not increase in those with a history of peripheral artery disease or LEA. No significant differences were observed between dipeptidyl peptidase-4 inhibitor and GLP-1 RA users in terms of the primary or secondary outcomes. CONCLUSION: In patients with type 2 diabetes initially diagnosed with DFC, SGLT2i are effective in significantly reducing the hospitalization for heart failure and MACE rates. SGLT2i lower the amputation rates, especially in patients who have not previously had a LEA, than the dipeptidyl peptidase-4 inhibitor therapy.

Manipulation of Convection Using Infrared Light Emitted from Human Hands.

Control of convection plays an important role in heat transfer regulation, bio/chemical sensing, phase separation, etc. Current convection controlling systems generally depend on engineered energy sources to drive and manipulate the convection, which brings additional energy consumption into the system. Here the use of human hand as a natural and sustainable infrared (IR) radiation source for the manipulation of liquid convection is demonstrated. The fluid can sense the change of the relative position or the shape of the hand with the formation of different convection patterns. Besides the generation of static complex patterns, dynamic manipulation of convections can also be realized via moving of hand or finger. The use of such sustainable convections to control the movement of a floating "boat" is further achieved. The use of human hands as the natural energy sources provides a promising approach for the manipulation of liquid convection without the need of extra external energy, which may be further utilized for low-cost and intelligent bio/chemical sensing and separation.

Multiply robust estimation of natural indirect effects with multiple ordered mediators.

Multiple mediation analysis is a powerful methodology to assess causal effects in the presence of multiple mediators. Several methodologies, such as G-computation and inverse-probability-weighting, have been widely used to draw inferences about natural indirect effects (NIEs). However, a limitation of these methods is their potential for model misspecification. Although powerful semiparametric methods with high robustness and consistency have been developed for inferring average causal effects and for analyzing the effects of a single mediator, a comparably robust method for multiple mediation analysis is still lacking. Therefore, this theoretical study proposes a method of using multiply robust estimators of NIEs in the presence of multiple ordered mediators. We show that the proposed estimators not only enjoy the multiply robustness to model misspecification, they are also consistent and asymptotically normal under regular conditions. We also performed simulations for empirical comparisons of the finite-sample properties between our multiply robust estimators and existing methods. In an illustrative example, a dataset for liver disease patients in Taiwan is used to examine the mediating roles of liver damage and liver cancer in the pathway from hepatitis B/C virus infection to mortality. The model is implemented in the open-source R package "MedMR."

Biological and Bioinspired Thermal Energy Regulation and Utilization.

The regulation and utilization of thermal energy is increasingly important in modern society due to the growing demand for heating and cooling in applications ranging from buildings, to cooling high power electronics, and from personal thermal management to the pursuit of renewable thermal energy technologies. Over billions of years of natural selection, biological organisms have evolved unique mechanisms and delicate structures for efficient and intelligent regulation and utilization of thermal energy. These structures also provide inspiration for developing advanced thermal engineering materials and systems with extraordinary performance. In this review, we summarize research progress in biological and bioinspired thermal energy materials and technologies, including thermal regulation through insulation, radiative cooling, evaporative cooling and camouflage, and conversion and utilization of thermal energy from solar thermal radiation and biological bodies for vapor/electricity generation, temperature/infrared sensing, and communication. Emphasis is placed on introducing bioinspired principles, identifying key bioinspired structures, revealing structure-property-function relationships, and discussing promising and implementable bioinspired strategies. We also present perspectives on current challenges and outlook for future research directions. We anticipate that this review will stimulate further in-depth research in biological and bioinspired thermal energy materials and technologies, and help accelerate the growth of this emerging field.

Network pharmacology mechanism of Scutellarin to inhibit RGC pyroptosis in diabetic retinopathy.

To investigate the effect of scutellarin (SCU) in diabetic retinopathy (DR) and explore the associated molecular network mechanism. The animal model of DR was established from diabetic mellitus (DM) rats by intraperitoneally injected streptozotocin (STZ) at dosage 55 mg/kg. Meanwhile, SCU was intraperitoneally administrated to protect retina from cell pyroptosis induced by DM, and cell pyroptosis was detected by using HE, Nissl staining, and immunofluorescence recognition. Moreover, the hub gene involving in pyroptosis in DR was screened by bioinformatics and network pharmacology, designated as Venny intersection screen, GO and KEGG analysis, PPI protein interaction, and molecular docking. Lastly, the expressional change of hub genes were validated with experimental detection. Cell pyroptosis of the DR, specifically in retina ganglion cells (RGC), was induced in DM rats; SCU administration results in significant inhibition in the cell pyroptosis in DR. Mechanically, 4084 genes related to DR were screened from GeneCards and OMIM databases, and 120 SCU therapeutic targets were obtained, by using GeneCards, TCMSP with Swiss Target Prediction databases. Moreover, 357 targets related to pyroptosis were found using GenenCards database, and Drug, disease and phenotypic targets were analyzed online using the Draw Venn Diagram website, and 12 cross targets were obtained. Through GO function and KEGG pathway enrichment analysis, 659 BP related items, 7 CC related items, 30 MF related items, and 70 signal pathways were screened out; Of these, eleven proteins screened from cross-target PPI network were subsequently docked with the SCU, and their expressions including caspase-1, IL-1ß, IL-18, GSDMD and NLRP3 in RGC indicated by immunofluorescence, and the mRNA expression for caspase-1 in DR indicated by quantitative PCR, were successfully validated. SCU can effectively protect RGC pyroptosis in DR, and underlying mechanisms are involved in the inhibition of caspase-1, GSDMD, NLRP3, IL-1ß and IL-18. Our findings therefore provide crucial evidence to support the clinic practice of SCU for the treatment of DR, and explained the underlying molecular network mechanism.

Causal Mediation Analysis with Multiple Time-varying Mediators.

In longitudinal studies with time-varying exposures and mediators, the mediational g-formula is an important method for the assessment of direct and indirect effects. However, current methodologies based on the mediational g-formula can deal with only one mediator. This limitation makes these methodologies inapplicable to many scenarios. Hence, we develop a novel methodology by extending the mediational g-formula to cover cases with multiple time-varying mediators. We formulate two variants of our approach that are each suited to a distinct set of assumptions and effect definitions and present nonparametric identification results of each variant. We further show how complex causal mechanisms (whose complexity derives from the presence of multiple time-varying mediators) can be untangled. We implemented a parametric method, along with a user-friendly algorithm, in R software. We illustrate our method by investigating the complex causal mechanism underlying the progression of chronic obstructive pulmonary disease. We found that the effects of lung function impairment mediated by dyspnea symptoms accounted for 14.6% of the total effect and that mediated by physical activity accounted for 11.9%. Our analyses thus illustrate the power of this approach, providing evidence for the mediating role of dyspnea and physical activity on the causal pathway from lung function impairment to health status. See video abstract at, http://links.lww.com/EDE/B988 .

Complete effect decomposition for an arbitrary number of multiple ordered mediators with time-varying confounders: A method for generalized causal multi-mediation analysis.

Causal mediation analysis is advantageous for mechanism investigation. In settings with multiple causally ordered mediators, path-specific effects have been introduced to specify the effects of certain combinations of mediators. However, most path-specific effects are unidentifiable. An interventional analog of path-specific effects is adapted to address the non-identifiability problem. Moreover, previous studies only focused on cases with two or three mediators due to the complexity of the mediation formula in a large number of mediators. In this study, we provide a generalized definition of traditional path-specific effects and interventional path-specific effects with a recursive formula, along with the required assumptions for nonparametric identification. Subsequently, a general approach is developed with an arbitrary number of multiple ordered mediators and with time-varying confounders. All methods and software proposed in this study contribute to comprehensively decomposing a causal effect confirmed by data science and help disentangling causal mechanisms in the presence of complicated causal structures among multiple mediators.

Regimen comprising GLP-1 receptor agonist and basal insulin can decrease the effect of food on glycemic variability compared to a pre-mixed insulin regimen.

BACKGROUND: Increasing evidence suggests that glucagon-like peptide 1 (GLP-1) receptor agonists (RA) can stabilize glycemic variability (GV) and interfere with eating behavior. This study compared the impact of insulin, GLP-1 RA, and dietary components on GV using professional continuous glucose monitoring (CGM). METHODS: Patients with type 2 diabetes underwent CGM before and after switching from a twice-daily pre-mixed insulin treatment regimen to a GLP-1 RA (liraglutide) plus basal insulin regimen. The dietary components were recorded and analyzed by a certified dietitian. The interactions between the medical regimen, GV indices, and nutrient components were analyzed. RESULTS: Sixteen patients with type 2 diabetes were enrolled in this study. No significant differences in the diet components and total calorie intake between the two regimens were found. Under the pre-mixed insulin regimen, for increase in carbohydrate intake ratio, mean amplitude of glucose excursion (MAGE) and standard deviation (SD) increased; in contrast, under the new regimen, for increase in fat intake ratio, MAGE and SD decreased, while when the protein intake ratio increased, the coefficient of variation (CV) decreased. The impact of the food intake ratio on GV indices disappeared under the GLP-1 RA regimen. After switching to the GLP-1 RA regimen, the median MAGE, SD, and CV values decreased significantly. However, the significant difference in GV between the two regimens decreased during the daytime. CONCLUSION: A GLP-1 RA plus basal insulin regimen can stabilize GV better than a regimen of twice-daily pre-mixed insulin, especially in the daytime, and can diminish the effect of food components on GV.

On the Conventional Definition of Path-specific Effects: Fully Mediated Interaction With Multiple Ordered Mediators.

Path-specific effects are a critical measure for assessing mediation in the presence of multiple mediators. However, the conventional definition of path-specific effects has generated controversy because it often causes misinterpretation of the results of multiple mediator analysis. For in-depth analysis of this issue, we propose the concept of decomposing fully mediated interaction from the average causal effect. We show that misclassification of fully mediated interaction is the main cause of misinterpretation of path-specific effects. We propose two strategies for specifying fully mediated interaction: isolating and reclassifying fully mediated interaction. The choice of strategy depends on the objective. Isolating fully mediated interaction is the superior strategy when the main objective is elucidating the mediation mechanism, whereas reclassifying it is superior when the main objective is precisely interpreting the mediation analysis results. To compare performance, this study used the two proposed strategies and the conventional decomposition strategy to analyze the mediating roles of dyspnea and anxiety in the effect of impaired lung function on poor health status in a population of patients with chronic obstructive pulmonary disease. The estimation result showed that the conventional decomposition strategy underestimates the importance of dyspnea as a mechanism of this disease. Specifically, the strategy of reclassifying fully mediated interaction revealed that 50% of the average causal effect is attributable to mediating effects, particularly the mediating effect of dyspnea.

Population attributable fraction based on marginal sufficient component cause model for mediation settings.

PURPOSE: Population attributable fraction (PAF), defined as the proportion of the occurrence of a disease which will be reduced by eliminating risk factors in a population, is one of the most common measurements for evaluating the benefit of a health-related policy in epidemiologic study. In this article, we propose an alternative PAF defined based on sufficient cause framework, which decompose the occurrence of a disease into several pathways including mediation and mechanistic interaction. METHODS: We propose a formal statistical definition and regression-based estimator for PAF based on sufficient cause framework within mediation settings. Under monotonicity assumption, the proposed method can decompose the occurrence of a disease into nine PAFs corresponding to all types of mechanisms attributing to exposure and the mediator, including the portion attributing to exposure directly, to mediator, to indirect effect through mediator, to the mechanistic interaction, to both of mediation and interaction, and to none of exposure or mediator. RESULTS: We apply the proposed method to explore the mechanism of a hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC) mediated by and/or interacted with alanine aminotransferase (ALT) and hepatitis B virus (HBV). When treating ALT as mediator, 56.77% of diseased subjects can be attributable to either HCV or abnormal ALT. When treating HBV as mediator, HCC is mainly induced by an exogenous high HBV viral load directly. CONCLUSIONS: The proposed method can identify the impact of exposure and pathway effects, and benefit to allocate the resources on intervention strategies.

Genome-wide causal mediation analysis identifies genetic loci associated with uterine fibroids mediated by age at menarche.

STUDY QUESTION: Could the direct contribution of genetic variants to the pathophysiology of uterine fibroids and the contribution mediated by age at menarche be different? SUMMARY ANSWER: Age at menarche plays a mediation role in the genetic influence on uterine fibroids, and four causal genetic mechanisms underlying the age at menarche-mediated effects of common genetic loci on uterine fibroid development were identified. WHAT IS KNOWN ALREADY: Uterine fibroids are common benign tumors developing from uterine smooth muscle. Genome-wide association studies (GWASs) have identified over 30 genetic loci associated with uterine fibroids in different ethnic populations. Several genetic variations in or nearby these identified loci were also associated with early age at menarche, one of the major risk factors of uterine fibroids. Although the results of GWASs reveal how genetic variations affect uterine fibroids, the genetic mechanism of uterine fibroids mediated by age at menarche remains elusive. STUDY DESIGN, SIZE, DURATION: In this study, we conducted a genome-wide causal mediation analysis in two cohorts covering a total of 69 552 females of Han Chinese descent from the Taiwan Biobank (TWB). TWB is an ongoing community- and hospital-based cohort aiming to enroll 200 000 individuals from the general Taiwanese population between 30 and 70 years old. It has been enrolling Taiwanese study participants since 2012 and has extensive phenotypic data collected from 148 291 individuals as of May 2021. PARTICIPANTS/MATERIALS, SETTING, METHODS: We recruited individuals in two cohorts, with 13 899 females in TWB1 and 55 653 females in TWB2. The two sets of individuals are almost distinct, with only 730 individuals enrolled in both cohorts. Over 99% of the participants are Han Chinese. Approximately 21% of participants developed uterine fibroids. DNA samples from both cohorts were genotyped using two different customized chips (TWB1 and TWB2 arrays). After quality control and genotype imputation, 646 973 TWB1 single-nucleotide polymorphisms (SNPs) and 686 439 TWB2 SNPs were assessed in our analysis. There were 99 939 SNPs which overlapped between the TWB1 and TWB2 arrays, 547 034 TWB1 array-specific SNPs and 586 500 TWB2 array-specific SNPs. We performed GWASs for screening potential risk SNPs for age at menarche and for uterine fibroids. We subsequently identified causal mediation effects of risk SNPs on uterine fibroids mediated by age at menarche. MAIN RESULTS AND THE ROLE OF CHANCE: In addition to known loci at LIN28B associated with age at menarche and loci at WNT4 associated with uterine fibroids, we identified 162 SNPs in 77 transcripts that were associated with menarche-mediated causal effects on uterine fibroids via four different causal genetic mechanisms: a both-harmful group with 52 SNPs, a both-protective group with 34 SNPs, a mediator-harmful group with 22 SNPs and a mediator-protective group with 54 SNPs. Among these SNPs, rs809302 in SLK significantly increased the risk of developing uterine fibroids by 3.92% through a mechanism other than age at menarche (P < 10-10), and rs371721345 in HLA-DOB was associated with a 2.70% decreased risk (P < 10-10) in the occurrence of uterine fibroids, mediated by age at menarche. These findings provide insights into the mechanism underlying the effect of genetic loci on uterine fibroids mediated by age at menarche. LIMITATIONS, REASONS FOR CAUTION: A potential issue is that the present study relied upon self-reported age at menarche and uterine fibroid information. Due to the experimental design, the consistency between self-reports and medical records for uterine fibroids in Taiwan cannot be checked. Fortunately, the literature support that self-reporting even years later remains a practical means for collecting data on menarche and uterine fibroids. We found that the impact of under-reporting of uterine fibroids is less in our study. In addition, the rate of reporting a diagnosis of uterine fibroids was within the rates of medical diagnosis based on national health insurance data. Future work investigating the consistency between self-reports and medical records in Taiwan can remedy this issue. WIDER IMPLICATIONS OF THE FINDINGS: This study is the first to investigate whether and to what extent age at menarche mediates the causal effects of genetic variants on uterine fibroids by using genome-wide causal mediation analysis. By treating age at menarche as a mediator, this report provides an insight into the genetic risk factors for developing uterine fibroids. Thus, this article represents a step forward in deciphering the role of intermediated risk factors in the genetic mechanism of disease. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the China Medical University, Taiwan (CMU110-ASIA-13 and CMU107-Z-04), the Ministry of Science and Technology, Taiwan (MOST 110-2314-B-039-058) and the International Joint Usage/Research Center, the Institute of Medical Science, the University of Tokyo, Japan (K2104). The authors have no competing interests. TRIAL REGISTRATION NUMBER: N/A.

Identification and robust estimation of swapped direct and indirect effects: Mediation analysis with unmeasured mediator-outcome confounding and intermediate confounding.

Counterfactual-model-based mediation analysis can yield substantial insight into the causal mechanism through the assessment of natural direct effects (NDEs) and natural indirect effects (NIEs). However, the assumptions regarding unmeasured mediator-outcome confounding and intermediate mediator-outcome confounding that are required for the determination of NDEs and NIEs present practical challenges. To address this problem, we introduce an instrumental blocker, a novel quasi-instrumental variable, to relax both of these assumptions, and we define a swapped direct effect (SDE) and a swapped indirect effect (SIE) to assess the mediation. We show that the SDE and SIE are identical to the NDE and NIE, respectively, based on a causal interpretation. Moreover, the empirical expressions of the SDE and SIE are derived with and without an intermediate mediator-outcome confounder. Then, a multiply robust estimation method is derived to mitigate the model misspecification problem. We prove that the proposed estimator is consistent, asymptotically normal, and achieves the semiparametric efficiency bound. As an illustration, we apply the proposed method to genomic datasets of lung cancer to investigate the potential role of the epidermal growth factor receptor in the treatment of lung cancer.

Path-specific effects in the presence of a survival outcome and causally ordered multiple mediators with application to genomic data.

Causal multimediation analysis (i.e. the causal mediation analysis with multiple mediators) is critical for understanding the effectiveness of interventions, especially in medical research. Deriving the path-specific effects of exposure on the outcome through a set of mediators can provide detail about the causal mechanism of interest However, existing models are usually restricted to partial decomposition, which can only be used to evaluate the cumulative effect of several paths. In genetics studies, partial decomposition fails to reflect the real causal effects mediated by genes, especially in complex gene regulatory networks. Moreover, because of the lack of a generalized identification procedure, the current multimediation analysis cannot be applied to the estimation of path-specific effects for any number of mediators. In this study, we derive the interventional analogs of path-specific effect for complete decomposition to address the difficulty of nonidentifiability. On the basis of two survival models of the outcome, we derive the generalized analytic forms for interventional analogs of path-specific effects by assuming the normal distributions of mediators. We apply the new methodology to investigate the causal mechanism of signature genes in lung cancer based on the cell cycle pathway, and the results clarify the gene pathway in cancer.

Robust inference on effects attributable to mediators: A controlled-direct-effect-based approach for causal effect decomposition with multiple mediators.

Effect decomposition is a critical technique for mechanism investigation in settings with multiple causally ordered mediators. Causal mediation analysis is a standard method for effect decomposition, but the assumptions required for the identification process are extremely strong. Moreover, mediation analysis focuses on addressing mediating mechanisms rather than interacting mechanisms. Mediation and interaction for mediators both contribute to the occurrence of disease, and therefore unifying mediation and interaction in effect decomposition is important to causal mechanism investigation. By extending the framework of controlled direct effects, this study proposes the effect attributable to mediators (EAM) as a novel measure for effect decomposition. For policymaking, EAM represents how much an effect can be eliminated by setting mediators to certain values. From the perspective of mechanism investigation, EAM contains information about how much a particular mediator or set of mediators is involved in the causal mechanism through mediation, interaction, or both. EAM is more appropriate than the conventional path-specific effect for application in clinical or medical studies. The assumptions of EAM for identification are considerably weaker than those of causal mediation analysis. We develop a semiparametric estimator of EAM with robustness to model misspecification. The asymptotic property is fully realized. We applied EAM to assess the magnitude of the effect of hepatitis C virus infection on mortality, which was eliminated by controlling alanine aminotransferase and treating hepatocellular carcinoma.

Risk factors of first and recurrent genitourinary tract infection in patients with type 2 diabetes treated with SGLT2 inhibitors: A retrospective cohort study.

AIMS: This retrospective study investigated the risk factors of sodium-glucose cotransporter 2 inhibitors (SGLT2i) -related genitourinary tract infection (GUTI). METHODS: We used longitudinal claims data from May 2016 to December 2017 from the Chang Gung Research Database. Diabetic patients who used SGLT2i were included. The baseline characteristics risk factors between patients who had GUTI and no GUTI were analyzed. RESULTS: There were 428(3.43%) patients with the first occurrence of urinary tract infection (UTI) and 5(0.04%) patients with genital tract infection (GTI). Female patients aged ≥ 65 years with HbA1c ≥ 9%, eGFR < 60 ml/min/1.73 m2, urine albumin/creatinine ratio (UACR) level ≥30 mg/g, dyslipidemia, diabetic microvascular complications and mood disorder had a higher risk of having the first occurrence of UTI. There was no significant risk factor of GTI. 117 UTI and 3 GTI patients received SGLT2i rechallenging. The recurrent UTI rate was 28.2% and no recurrent GTI was diagnosed. The risk factors included CHD, eGRF < 45 ml/min/1.73 m2, and mood disorder (OR, 95% CI: 4.39, 1.15-16.74; 4.11, 1.51-11.19; 5.93, 1.39-25.34, respectively). CONCLUSIONS: In diabetic patients who had underlying disease of eGRF < 45 ml/min/1.73 m2, CHD, and mood disorder had higher risk of recurrent UTI after rechallenging SGLT2i.

Noncontact human-machine interaction based on hand-responsive infrared structural color.

Noncontact human-machine interaction provides a hygienic and intelligent approach for the communication between human and robots. Current noncontact human-machine interactions are generally limited by the interaction distance or conditions, such as in the dark. Here we explore the utilization of hand as an infrared light source for noncontact human-machine interaction. Metallic gratings are used as the human-machine interface to respond to infrared radiation from hand and the generated signals are visualized as different infrared structural colors. We demonstrate the applications of the infrared structural color-based human-machine interaction for user-interactive touchless display and real-time control of a robot vehicle. The interaction is flexible to the hand-interface distance ranging from a few centimeters to tens of centimeters and can be used in low lighting condition or in the dark. The findings in this work provide an alternative and complementary approach to traditional noncontact human-machine interactions, which may further broaden the potential applications of human-machine interaction.