Within-hospital Temporal Clustering of Postoperative Complications and Implications for Safety Monitoring and Benchmarking Using ACS-NSQIP Data.

Objective: To determine the extent to which within-hospital temporal clustering of postoperative complications is observed in the American College of Surgeons, National Surgical Quality Improvement Program (ACS-NSQIP). Background: ACS-NSQIP relies on periodic and on-demand reports for quality benchmarking. However, if rapid increases in postoperative complication rates (clusters) are common, other reporting methods might be valuable additions to the program. This article focuses on estimating the incidence of within-hospital temporal clusters. Methods: ACS-NSQIP data from 1,547,440 patients, in 425 hospitals, over a 2-year period was examined. Hospital-specific Cox proportional hazards regression was used to estimate the incidence of mortality, morbidity, and surgical site infection (SSI) over a 30-day postoperative period, with risk adjustment for patient and procedure and with additional adjustments for linear trend, day-of-week, and season. Clusters were identified using scan statistics, and cluster counts were compared, using unpaired and paired t tests, for different levels of adjustment and when randomization of cases across time eliminated all temporal influences. Results: Temporal clusters were rarely observed. When clustering was adjusted only for patient and procedure risk, an annual average of 0.31, 0.85, and 0.51 clusters were observed per hospital for mortality, morbidity, and SSI, respectively. The number of clusters dropped after adjustment for linear trend, day-of-week, and season (0.31-0.24; P = 0.012; 0.85-0.80; P = 0.034; and 0.51-0.36; P < 0.001; using paired t tests) for mortality, morbidity, and SSI, respectively. There was 1 significant difference in the number of clusters when comparing data with all adjustments and after data were randomized (0.24 and 0.25 for mortality; P = 0.853; 0.80 and 0.82 for morbidity; P = 0.529; and 0.36 and 0.46 [randomized data had more clusters] for SSI; P = 0.001; using paired t tests) for mortality, morbidity, and SSI, respectively. Conclusions: Temporal clusters of postoperative complications were rarely observed in ACS-NSQIP data. The described methodology may be useful in assessing clustering in other surgical arenas.

Octogenarians unable to return home by postoperative-day 30.

BACKGROUND: For older adults undergoing surgery, returning home is instrumental for functional independence. We quantified octogenarians unable to return home by POD-30, assessed geriatric factors in a predictive model, and identified risk factors to inform decision-making and quality improvement. METHODS: This retrospective cohort study examined patients ≥80 years old from the ACS NSQIP Geriatric Surgery Pilot, using sequential logistic regression modelling. The primary outcome was non-home living location at POD-30. RESULTS: Of 4946 patients, 19.8 â€‹% lived in non-home facilities at POD-30. Increased odds of non-home living location were seen in patients with preoperative fall history (OR 2.92, 95%CI 2.06-4.14) and new postoperative pressure ulcer (OR 2.66, 95%CI 1.50-4.71) Other significant geriatric-specific risk factors included mobility aid use, surrogate-signed consent, and postoperative delirium, with odds ratios ranging from 1.42 (1.19-1.68) to 1.97 (1.53-2.53). CONCLUSIONS: These geriatric-specific risk factors highlight the importance of preoperative vulnerability screening and intervention to inform surgical decision-making.

Targeting ALDOA to modulate tumorigenesis and energy metabolism in retinoblastoma.

This study aims to elucidate the pivotal role of aldolase A (ALDOA) in retinoblastoma (RB) and evaluate the potential of the ALDOA inhibitor itaconate in impeding RB progression. Utilizing single-cell RNA sequencing, ALDOA consistently exhibits overexpression across diverse cell types, particularly in cone precursor cells, retinoma-like cells, and retinoblastoma-like cells. This heightened expression is validated in RB tissues and cell lines. ALDOA knockdown significantly diminishes RB cell viability, impedes colony formation, and induces notable metabolic alterations. RNA-seq analysis identifies SUSD2, ARHGAP27, and CLK2 as downstream genes associated with ALDOA. The application of itaconate demonstrates efficacy in inhibiting RB cell proliferation, validated through in vitro and in vivo models. This study emphasizes ALDOA as a promising target for innovative RB therapies, with potential implications for altering tumor energy metabolism.

Deciphering metabolic heterogeneity in retinoblastoma unravels the role of monocarboxylate transporter 1 in tumor progression.

BACKGROUND: Tumors exhibit metabolic heterogeneity, influencing cancer progression. However, understanding metabolic diversity in retinoblastoma (RB), the primary intraocular malignancy in children, remains limited. METHODS: The metabolic landscape of RB was constructed based on single-cell transcriptomic sequencing from 11 RB and 5 retina samples. Various analyses were conducted, including assessing overall metabolic activity, metabolic heterogeneity, and the correlation between hypoxia and metabolic pathways. Additionally, the expression pattern of the monocarboxylate transporter (MCT) family in different cell clusters was examined. Validation assays of MCT1 expression and function in RB cell lines were performed. The therapeutic potential of targeting MCT1 was evaluated using an orthotopic xenograft model. A cohort of 47 RB patients was analyzed to evaluate the relationship between MCT1 expression and tumor invasion. RESULTS: Distinct metabolic patterns in RB cells, notably increased glycolysis, were identified. This metabolic heterogeneity correlated closely with hypoxia. MCT1 emerged as the primary monocarboxylate transporter in RB cells. Disrupting MCT1 altered cell viability and energy metabolism. In vivo studies using the MCT1 inhibitor AZD3965 effectively suppressed RB tumor growth. Additionally, a correlation between MCT1 expression and optic nerve invasion in RB samples suggested prognostic implications. CONCLUSIONS: This study enhances our understanding of RB metabolic characteristics at the single-cell level, highlighting the significance of MCT1 in RB pathogenesis. Targeting MCT1 holds promise as a therapeutic strategy for combating RB, with potential prognostic implications.

Identifying Population-Level and Within-Hospital Disparities in Surgical Care.

BACKGROUND: The lack of consensus on equity measurement and its incorporation into quality-assessment programs at the hospital and system levels may be a barrier to addressing disparities in surgical care. This study aimed to identify population-level and within-hospital differences in the quality of surgical care provision. STUDY DESIGN: The analysis included 657 NSQIP participating hospitals with more than 4 million patients (2014 to 2018). Multilevel random slope, random intercept modeling was used to examine for population-level and in-hospital disparities. Disparities in surgical care by Area Deprivation Index (ADI), race, and ethnicity were analyzed for 5 measures: all-case inpatient mortality, all-case urgent readmission, all-case postoperative surgical site infection, colectomy mortality, and spine surgery complications. RESULTS: Population-level disparities were identified across all measures by ADI, 2 measures for Black race (all-case readmissions and spine surgery complications), and none for Hispanic ethnicity. Disparities remained significant in the adjusted models. Before risk adjustment, in all measures examined, within-hospital disparities were detected in: 25.8% to 99.8% of hospitals for ADI, 0% to 6.1% of hospitals for Black race, and 0% to 0.8% of hospitals for Hispanic ethnicity. After risk adjustment, in all measures examined, less than 1.1% of hospitals demonstrated disparities by ADI, race, or ethnicity. CONCLUSIONS: After risk adjustment, very few hospitals demonstrated significant disparities in care. Disparities were more frequently detected by ADI than by race and ethnicity. The lack of substantial in-hospital disparities may be due to the use of postoperative metrics, small sample sizes, the risk adjustment methodology, and healthcare segregation. Further work should examine surgical access and healthcare segregation.

Heterogeneous Expression Patterns of the Minichromosome Maintenance Complex Members in Retinoblastoma Unveil Its Clinical Significance.

Purpose: To explore the expression patterns and clinical significance of minichromosome maintenance (MCM) complex members in retinoblastoma (RB). Methods: Single-cell RNA sequencing datasets from five normal retina, six intraocular, and five extraocular RB samples were integrated to characterize the expression patterns of MCM complex members at the single-cell level. Western blot and quantitative PCR were used to detect the expression of MCM complex members in RB cell lines. Immunohistochemistry was conducted to validate the expression of MCM complex members in RB patient samples and a RB mouse model. Results: The expression of MCM2-7 is increased in RB tissue, with MCM2/3/7 showing particularly higher levels in extraocular RB. MCM3/7 are abundantly detected in cell types associated with oncogenesis. Both mRNA and protein levels of MCM3/4/6/7 are increased in RB cell lines. Immunohistochemistry further confirmed the elevated expression of MCM3 in extraocular RB, with MCM6 being the most abundantly expressed MCM in RB. Conclusions: The distinct MCM expression patterns across various RB cell types suggest diverse functional roles, offering valuable insights for targeted therapeutic strategies. The upregulation of MCM3, MCM4, MCM6, and MCM7 in RB, with a specific emphasis on MCM6 as a notable marker, highlights their potential significance.

Single-cell transcriptomics enable the characterization of local extension in retinoblastoma.

Retinoblastoma (RB) is the most prevalent ocular tumor of childhood, and its extraocular invasion significantly increases the risk of metastasis. Nevertheless, a single-cell characterization of RB local extension has been lacking. Here, we perform single-cell RNA sequencing on four RB samples (two from intraocular and two from extraocular RB patients), and integrate public datasets of five normal retina samples, four intraocular samples, and three extraocular RB samples to characterize RB local extension at the single-cell level. A total of 128,454 qualified cells are obtained in nine major cell types. Copy number variation inference reveals chromosome 6p amplification in cells derived from extraocular RB samples. In cellular heterogeneity analysis, we identified 10, 8, and 7 cell subpopulations in cone precursor like cells, retinoma like cells, and MKI67+ photoreceptorness decreased (MKI67+ PhrD) cells, respectively. A high expression level of SOX4 was detected in cells from extraocular samples, especially in MKI67+ PhrD cells, which was verified in additional clinical RB samples. These results suggest that SOX4 might drive RB local extension. Our study presents a single-cell transcriptomic landscape of intraocular and extraocular RB samples, improving our understanding of RB local extension at the single-cell resolution and providing potential therapeutic targets for RB patients.

Surgical Outcomes of Standardized Endoscopical Deep Medial Orbital Decompression in Dysthyroid Optic Neuropathy.

INTRODUCTION: The aim of the study was to standardize the endoscopic deep medial orbital decompression surgery for better relief of optic nerve compression in dysthyroid optic neuropathy (DON). METHODS: A total of 128 eyes from patients received the standardized endoscopic deep medial orbital decompression surgery were recruited in this study. The efficacy of the procedure was assessed at a 1-month follow-up by the best-corrected visual acuity (VA), visual field (VF), and visual evoked potential (VEP). Clinical data were collected to explore the factors that affected visual recovery. Oxygen saturation of retinal blood vessels, retinal thickness, and vessel density were measured to demonstrate the potential recovery mechanisms. RESULTS: After surgery, the ratio of extraocular muscle volume in the orbital apex to orbital apex volume significantly decreased from 44.32 ± 22.31% to 36.82 ± 12.02% (p < 0.001). 96.87% of eyes' final VA improved; average VA improved from 0.93 ± 0.73 to 0.50 ± 0.60 at 1 week (p < 0.001) and 0.40 ± 0.53 at 1 month (p < 0.001). Postoperatively, VF and VEP also improved, the oxygen saturation of retinal arteries increased, and the retinal thickness was reduced. Preoperative VA, visual impairment duration, and clinical activity score evaluation were associated with visual recovery. CONCLUSION: In this study, we standardized the endoscopic deep medial orbital decompression, of which key point was to relieve pressure in the orbital apex and achieved satisfactory visual recovery in DON patients.

The Accuracy of the NSQIP Universal Surgical Risk Calculator Compared to Operation-Specific Calculators.

Objective: To compare the performance of the ACS NSQIP "universal" risk calculator (N-RC) to operation-specific RCs. Background: Resources have been directed toward building operation-specific RCs because of an implicit belief that they would provide more accurate risk estimates than the N-RC. However, operation-specific calculators may not provide sufficient improvements in accuracy to justify the costs in development, maintenance, and access. Methods: For the N-RC, a cohort of 5,020,713 NSQIP patient records were randomly divided into 80% for machine learning algorithm training and 20% for validation. Operation-specific risk calculators (OS-RC) and OS-RCs with operation-specific predictors (OSP-RC) were independently developed for each of 6 operative groups (colectomy, whipple pancreatectomy, thyroidectomy, abdominal aortic aneurysm (open), hysterectomy/myomectomy, and total knee arthroplasty) and 14 outcomes using the same 80%/20% rule applied to the appropriate subsets of the 5M records. Predictive accuracy was evaluated using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), and Hosmer-Lemeshow (H-L) P values, for 13 binary outcomes, and mean squared error for the length of stay outcome. Results: The N-RC was found to have greater AUROC (P = 0.002) and greater AUPRC (P < 0.001) compared to the OS-RC. No other statistically significant differences in accuracy, across the 3 risk calculator types, were found. There was an inverse relationship between the operation group sample size and magnitude of the difference in AUROC (r = -0.278; P = 0.014) and in AUPRC (r = -0.425; P < 0.001) between N-RC and OS-RC. The smaller the sample size, the greater the superiority of the N-RC. Conclusions: While operation-specific RCs might be assumed to have advantages over a universal RC, their reliance on smaller datasets may reduce their ability to accurately estimate predictor effects. In the present study, this tradeoff between operation specificity and accuracy, in estimating the effects of predictor variables, favors the N-R, though the clinical impact is likely to be negligible.

Integrated Transcriptome Analysis of Long Noncoding RNA and mRNA in Developing and Aging Mouse Retina.

Mice have emerged as a widely employed model for investigating various retinal diseases. However, the availability of comprehensive datasets capturing the entire developmental and aging stages of the mouse retina, particularly during the elderly period, encompassing integrated lncRNA and mRNA expression profiles, is limited. In this study, we assembled a total of 18 retina samples from mice across 6 distinct stages of development and aging (5 days, 3 weeks, 6 weeks, 10 weeks, 6 months, and 15 months) to conduct integrated lncRNA and mRNA sequencing analysis. This invaluable dataset offers a comprehensive transcriptomic resource of mRNA and lncRNA expression profiles during the natural progression of retinal development and aging. The discoveries stemming from this investigation will significantly contribute to the elucidation of the underlying molecular mechanisms associated with various retinal diseases, such as congenital retinal dysplasia and retinal degenerative diseases.

The Genetic, Pharmacogenomic, and Immune Landscapes Associated with Protein Expression across Human Cancers.

Proteomics is a powerful approach that can rapidly enhance our understanding of cancer development. Detailed characterization of the genetic, pharmacogenomic, and immune landscape in relation to protein expression in patients with cancer could provide new insights into the functional roles of proteins in cancer. By taking advantage of the genotype data from The Cancer Genome Atlas and protein expression data from The Cancer Proteome Atlas, we characterized the effects of genetic variants on protein expression across 31 cancer types and identified approximately 100,000 protein quantitative trait loci (pQTL). Among these, over 8000 pQTLs were associated with patient overall survival. Furthermore, characterization of the impact of protein expression on more than 350 imputed anticancer drug responses in patients revealed nearly 230,000 significant associations. In addition, approximately 21,000 significant associations were identified between protein expression and immune cell abundance. Finally, a user-friendly data portal, GPIP (https://hanlaboratory.com/GPIP), was developed featuring multiple modules that enable researchers to explore, visualize, and browse multidimensional data. This detailed analysis reveals the associations between the proteomic landscape and genetic variation, patient outcome, the immune microenvironment, and drug response across cancer types, providing a resource that may offer valuable clinical insights and encourage further functional investigations of proteins in cancer. SIGNIFICANCE: Comprehensive characterization of the relationship between protein expression and the genetic, pharmacogenomic, and immune landscape of tumors across cancer types provides a foundation for investigating the role of protein expression in cancer development and treatment.

Multi-omics characterization of autophagy-related molecular features for therapeutic targeting of autophagy.

Autophagy is a major contributor to anti-cancer therapy resistance. Many efforts have been made to understand and overcome autophagy-mediated therapy resistance, but these efforts have been unsuccessful in clinical applications. In this study, we establish an autophagy signature to estimate tumor autophagy status. We then classify approximately 10,000 tumor samples across 33 cancer types from The Cancer Genome Atlas into autophagy score-high and autophagy score-low groups. We characterize the associations between multi-dimensional molecular features and tumor autophagy, and further analyse the effects of autophagy status on drug response. In contrast to the conventional view that the induction of autophagy serves as a key resistance mechanism during cancer therapy, our analysis reveals that autophagy induction may also sensitize cancer cells to anti-cancer drugs. We further experimentally validate this phenomenon for several anti-cancer drugs in vitro and in vivo, and reveal that autophagy inducers potentially sensitizes tumor cells to etoposide through downregulating the expression level of DDIT4. Our study provides a comprehensive landscape of molecular alterations associated with tumor autophagy and highlights an opportunity to leverage multi-omics analysis to utilize multiple drug sensitivity induced by autophagy.

Real-time imaging of intracellular cysteine level fluctuations during Cu2+ or H2O2 induced redox imbalance using a turn-on fluorescence sensor.

Redox balance is a necessary guarantee to maintain the normal physiological activities of organisms. Cysteine (Cys), a critical biological thiol, has the effect of maintaining redox balance in the body. The concentration of intracellular Cys is abnormal under redox imbalance, thereby resulting in multiple diseases. Additionally, studies have revealed that Cu2+ can stimulate the body to produce excess reactive oxygen species (ROS, similar to H2O2), and the generated ROS will consume reducing substances (such as Cys) in the body, leading to redox imbalance. Thus, finding a simple and effective method to monitor Cys under redox imbalance is pressing. Here, a turn on probe (DDNO) was proposed by connecting SBD-Cl to a red dye (HDM). The probe can specifically recognize Cys with rapid response (180 s) and low detection limit (0.61 µM) through substitution-rearrangement reaction between sulfhydryl and chlorine atom. Bioimaging experiments indicated that the probe has good biocompatibility and cell membrane permeability, which can be applied to monitor the fluctuation of Cys levels in live cells and zebrafish under the redox imbalance induced by Cu2+ or H2O2.

Association of antibiotic treatment with immune-related adverse events in patients with cancer receiving immunotherapy.

BACKGROUND: To determine whether antibiotic treatment is a risk factor for immune-related adverse events (irAEs) across different patients with cancer receiving anti-PD-1/PD-L1 therapies. METHODS: The retrospective analysis includes clinical information from 767 patients with cancer treated at Hunan Cancer Hospital from 2017 to 2020. The pharmacovigilance data analysis includes individual cases of 38,705 safety reports from the US Food and Drug Administration Adverse Event Reporting System (FAERS) from 2014 to 2020, and 25,122 cases of safety reports from the World Health Organization database VigiBase from 2014 to 2019. All cases that received anti-PD-1/PD-L1 treatment were included. Multiomics data from patients across 25 cancer types were download from The Cancer Genome Atlas. Logistic regression and propensity score algorithm was employed to calculate OR of irAEs. RESULTS: Retrospective analysis of in-house patients showed that irAE potential risks are higher in all cancer (OR 2.12, 95% CI 1.38 to 3.22, false discovery rate (FDR) adjusted-p=1.93×10-3) and patients with lung cancer (OR 3.16, 95% CI 1.67 to 5.95, FDR adjusted-p=1.93×10-3) when using antibiotics. Potential risk of irAEs in patients with lung cancer with antibiotic treatment is significantly higher in FAERS (OR 1.39, 95% CI 1.21 to 1.59; FDR adjusted-p=1.62×10-5) and VigiBase (OR 1.32, 95% CI 1.09 to 1.59, FDR adjusted-p=0.05). Mechanistically, decreased microbial diversity caused by antibiotics use may increase the irAE risk through mediating the irAE-related factors. CONCLUSIONS: Our study is the first to comprehensively demonstrate the associations of irAEs and antibiotic during anti-PD-1/PD-L1 therapy across a wide spectrum of cancers by analyzing multisource data. Administration of antibiotics should be carefully evaluated in patients with cancer treated by anti-PD-1/PD-L1 to avoid potentially increasing irAE risk.

GPEdit: the genetic and pharmacogenomic landscape of A-to-I RNA editing in cancers.

Altered A-to-I RNA editing has been widely observed in many human cancers and some editing sites are associated with drug sensitivity, implicating its therapeutic potential. Increasing evidence has demonstrated that a quantitative trait loci mapping approach is effective to understanding the genetic basis of RNA editing. We systematically performed RNA editing quantitative trait loci (edQTL) analysis in 33 human cancer types for >10 000 cancer samples and identified 320 029 edQTLs. We also identified 1688 ed-QTLs associated with patient overall survival and 4672 ed-QTLs associated with GWAS risk loci. Furthermore, we demonstrated the associations between RNA editing and >1000 anti-cancer drug response with ∼3.5 million significant associations. We developed GPEdit (https://hanlab.uth.edu/GPEdit/) to facilitate a global map of the genetic and pharmacogenomic landscape of RNA editing. GPEdit is a user-friendly and comprehensive database that provides an opportunity for a better understanding of the genetic impact and the effects on drug response of RNA editing in cancers.

Validation study of the ACS NSQIP surgical risk calculator for two procedures in Japan.

INTRODUCTION: The ACS NSQIP Surgical Risk Calculator (SRC) assesses risk to support goal-concordant care. While it accurately predicts US outcomes, its performance internationally is unknown. This study evaluates SRC accuracy in predicting mortality following low anterior resection (LAR) and pancreaticoduodenectomy (PD) in NSQIP patients and accuracy retention when applied to native Japanese patients (National Clinical Database, NCD). METHODS: NSQIP (41,260 LAR; 15,114 PD) and NCD cases (61,220 LAR; 27,901 PD) from 2015 to 2017 were processed through the SRC mortality model. Country-specific calibration and discrimination were assessed with and without an intercept correction applied to the Japanese data. RESULTS: The SRC exhibited acceptable calibration for LAR and PD when applied to NSQIP data but miscalibration for NCD data. A simple correction to the model intercept, motivated by lower mortality rates in the Japanese data, successfully remediated the miscalibration. CONCLUSIONS: The SRC may inaccurately predict surgical risk when applied to the native Japanese population. An intercept correction method is suggested when miscalibration is encountered; it is simple to implement and may permit effective international use of the SRC.

Association Between Sex and Immune-Related Adverse Events During Immune Checkpoint Inhibitor Therapy.

BACKGROUND: Accumulated evidence supports the existence of sex-associated differences in immune systems. Understanding the role of sex in immune-related adverse events (irAEs) is important for management of irAE in patients receiving immunotherapy. METHODS: We performed meta-analysis on published clinical study data and multivariable logistic regression on pharmacovigilance data and applied a propensity algorithm to The Cancer Genome Atlas omics data. We further validated our observations in 2 independent in-house cohorts of 179 and 767 cancer patients treated with immune checkpoint inhibitors. RESULTS: A meta-analysis using 13 clinical studies that reported on 1096 female patients (36.8%, 95% confidence interval [CI] = 35.0% to 38.5%) and 1886 male patients (63.2%, 95% CI = 61.5% to 65.0%) demonstrated no statistically significant irAE risk difference between the sexes (odds ratio [OR] = 1.19, 95% CI = 0.91 to 1.54, 2-sided P = .21). Multivariable logistic regression analysis of 12 225 patients from the Food and drug administration Adverse Event Reporting System (FAERS) and 10 979 patients from VigiBase showed no statistically significant difference in irAEs by sex. A propensity score algorithm used on multi-omics data for 6019 patients from The Cancer Genome Atlas found no statistically significant difference by sex for irAE-related factors or pathways. The retrospective analysis of 2 in-house patient cohorts validated these results (OR = 1.55, 95% CI = 0.98 to 2.47, false discovery rate = 0.13, for cohort 1; OR = 1.16, 95% CI = 0.86 to 1.57, false discovery rate = 0.39, for cohort 2). CONCLUSIONS: We observed minimal sex-associated differences in irAEs among cancer patients who received immune checkpoint inhibitor therapy. It may be unnecessary to consider sex effects for irAE management in clinical practice.

Tunable NIR AIE-active optical materials for lipid droplet imaging in typical model organisms and photodynamic therapy.

Near infrared (NIR) luminescent materials with aggregation-induced emission (AIE) features have attracted enormous attention in the areas of medical imaging and diagnostic therapeutics because of their low background fluorescence and strong tissue penetration. This study reports a series of easily synthesized AIEgen molecules that feature NIR emission. These molecules have a donor-donor-π-acceptor (D1-D2-π-A) structure with intramolecular charge transfer (ICT) character. The nature of charge transfer transition can be modified by different structures of D2, i.e. phenyl, thiophene, and furan ring. These AIEgens have high selectivity towards lipid droplets (LDs) in vitro and in vivo, such as zebrafish, Caenorhabditis elegans, and oil crop tissue. In addition, the effect of photodynamic therapy (PDT) on SMMC-7721 cells was investigated, and the results indicate that these AIEgens have potential application for PDT on cancer cells with white light illumination. This study reveals that these triphenylamine (TPA)-based AIEgens have great potential for biological imaging and preclinical applications of PDT.

Defining the risk of liver failure after minor hepatectomy: a NSQIP analysis of 7029 patients.

BACKGROUND: Post-hepatectomy liver failure (PHLF) remains a significant complication after hepatic resection. This study aims to determine the rate of PHLF in patients undergoing resection of 3 or fewer segments and analyze the association of PHLF with perioperative characteristics and postoperative complications. METHODS: The American College of Surgeons hepatectomy-targeted National Surgical Quality Improvement Program database was queried for patients undergoing left hemi-hepatectomy or partial resection from 2014 to 2018. The primary outcome was PHLF, defined by ISGLS. Multivariable logistic regression models assessed the association between PHLF, preoperative and operative variables and postoperative complications. RESULTS: Among 7029 patients, 187 (2.7%) experienced PHLF, with clinically significant (grade B/C) PHLF in 1.4%. PHLF was associated with older age, male gender, higher ASA classification, ascites, and elevated SGOT. Preoperative ascites (OR 4.94, 95%CI: 2.45-9.94, p < 0.001) had the strongest association with PHLF. There was no association between PHLF and concurrent colorectal resection, neoadjuvant therapy, or concurrent ablation. Surgical site infection (OR 3.64, 95%CI: 2.40-5.54, p < 0.001), sepsis (OR 3.78, 95%CI: 2.16-6.61, p < 0.001), postoperative invasive procedure (OR 6.92, 95%CI: 4.91-9.76, p < 0.001), and bile leak (OR 4.65, 95%CI: 3.04-7.12, p < 0.001) were associated with PHLF. CONCLUSION: PHLF after minor hepatectomy is rare and associated with signs of preoperative liver dysfunction. The association with infectious complications suggests a multifactorial etiology and provides targets for quality improvement.