Dashboard of Short-Term Postoperative Patient Outcomes for Anesthesiologists: Development and Preliminary Evaluation.

BACKGROUND: Anesthesiologists require an understanding of their patients' outcomes to evaluate their performance and improve their practice. Traditionally, anesthesiologists had limited information about their surgical outpatients' outcomes due to minimal contact post discharge. Leveraging digital health innovations for analyzing personal and population outcomes may improve perioperative care. BC Children's Hospital's postoperative follow-up registry for outpatient surgeries collects short-term outcomes such as pain, nausea, and vomiting. Yet, these data were previously not available to anesthesiologists. OBJECTIVE: This quality improvement study aimed to visualize postoperative outcome data to allow anesthesiologists to reflect on their care and compare their performance with their peers. METHODS: The postoperative follow-up registry contains nurse-reported postoperative outcomes, including opioid and antiemetic administration in the postanesthetic care unit (PACU), and family-reported outcomes, including pain, nausea, and vomiting, within 24 hours post discharge. Dashboards were iteratively co-designed with 5 anesthesiologists, and a department-wide usability survey gathered anesthesiologists' feedback on the dashboards, allowing further design improvements. A final dashboard version has been deployed, with data updated weekly. RESULTS: The dashboard contains three sections: (1) 24-hour outcomes, (2) PACU outcomes, and (3) a practice profile containing individual anesthesiologist's case mix, grouped by age groups, sex, and surgical service. At the time of evaluation, the dashboard included 24-hour data from 7877 cases collected from September 2020 to February 2023 and PACU data from 8716 cases collected from April 2021 to February 2023. The co-design process and usability evaluation indicated that anesthesiologists preferred simpler designs for data summaries but also required the ability to explore details of specific outcomes and cases if needed. Anesthesiologists considered security and confidentiality to be key features of the design and most deemed the dashboard information useful and potentially beneficial for their practice. CONCLUSIONS: We designed and deployed a dynamic, personalized dashboard for anesthesiologists to review their outpatients' short-term postoperative outcomes. This dashboard facilitates personal reflection on individual practice in the context of peer and departmental performance and, hence, the opportunity to evaluate iterative practice changes. Further work is required to establish their effect on improving individual and department performance and patient outcomes.

Imbalanced prediction of emergency department admission using natural language processing and deep neural network.

The emergency department (ED) plays a very significant role in the hospital. Owing to the rising number of ED visits, medical service points, and ED market, overcrowding of EDs has become serious worldwide. Overcrowding has long been recognized as a vital issue that increases the risk to patients and negative emotions of medical personnel and impacts hospital cost management. For the past years, many researchers have been applying artificial intelligence to reduce crowding situations in the ED. Nevertheless, the datasets in ED hospital admission are naturally inherent with the high-class imbalance in the real world. Previous studies have not considered the imbalance of the datasets, particularly addressing the imbalance. This study purposes to develop a natural language processing model of a deep neural network with an attention mechanism to solve the imbalanced problem in ED admission. The proposed framework is used for predicting hospital admission so that the hospitals can arrange beds early and solve the problem of congestion in the ED. Furthermore, the study compares a variety of methods and obtains the best composition that has the best performance for forecasting hospitalization in ED. The study used the data from a specific hospital in Taiwan as an empirical study. The experimental result demonstrates that almost all imbalanced methods can improve the model's performance. In addition, the natural language processing model of Bi-directional Long Short-Term Memory with attention mechanism has the best results in all-natural language processing methods.

Primary cicatricial alopecias are characterized by dysregulation of shared gene expression pathways.

The primary forms of cicatricial (scarring) alopecia (PCA) are a group of inflammatory, irreversible hair loss disorders characterized by immune cell infiltrates targeting hair follicles (HFs). Lichen planopilaris (LPP), frontal fibrosing alopecia (FFA), and centrifugal cicatricial alopecia (CCCA) are among the main subtypes of PCAs. The pathogenesis of the different types of PCAs are poorly understood, and current treatment regimens yield inconsistent and unsatisfactory results. We performed high-throughput RNA-sequencing on scalp biopsies of a large cohort PCA patients to develop gene expression-based signatures, trained into machine-learning-based predictive models and pathways associated with dysregulated gene expression. We performed morphological and cytokine analysis to define the immune cell populations found in PCA subtypes. We identified a common PCA gene signature that was shared between LPP, FFA, and CCCA, which revealed a significant over-representation of mast cell (MC) genes, as well as downregulation of cholesterogenic pathways and upregulation of fibrosis and immune signaling genes. Immunohistological analyses revealed an increased presence of MCs in PCAs lesions. Our gene expression analyses revealed common pathways associated with PCAs, with a strong association with MCs. The indistinguishable differences in gene expression profiles and immune cell signatures between LPP, FFA, and CCCA suggest that similar treatment regimens may be effective in treating these irreversible forms of hair loss.

Regulatory network analysis defines unique drug mechanisms of action and facilitates patient-drug matching in alopecia areata clinical trials.

Not all therapeutics are created equal in regards to individual patients. The problem of identifying which compound will work best with which patient is a significant burden across all disease contexts. In the context of autoimmune diseases such as alopecia areata, several formulations of JAK/STAT inhibitors have demonstrated efficacy in clinical trials. All of these compounds demonstrate different rates of response, and here we observed that this coincided with different molecular effects on patients undergoing treatment. Using these data, we have developed a computational model that is capable of predicting which patient-drug pairs have the highest likelihood of response. We achieved this by integrating inferred mechanism of action data and gene regulatory networks derived from an independent patient cohort with baseline patient data prior to beginning treatment.

Utilizing online stochastic optimization on scheduling of intensity-modulate radiotherapy therapy (IMRT).

According to Ministry of Health and Welfare of Taiwan, cancer has been one of the major causes of death in Taiwan since 1982. The Intensive-Modulated Radiation Therapy (IMRT) is one of the most important radiotherapies of cancers, especially for Nasopharyngeal cancers, Digestive system cancers and Cervical cancers. For patients, if they can receive the treatment at the earliest possibility while diagnosed with cancers, their survival rate increases. However, the discussion of effective patient scheduling models of IMRT to reduce patients' waiting time is still limited in literature. This study proposed a mathematical model to improve the efficiency of patient scheduling. The research was composed of two stages. In the first stage, the online stochastic algorithm was proposed to improve the performance of present scheduling system. In the second stage the impact of future treatment to reduce patients' waiting time was considered. A genetic algorithm (GA) was then proposed to solve the online stochastic scheduling problem. This research collected data from a practical medical institute and the proposed model was validated with real data. It contributes to both theory and practice by proposing a practical model to assist the medical institute in implementing patient scheduling in a more efficient manner.

IKZF1 Enhances Immune Infiltrate Recruitment in Solid Tumors and Susceptibility to Immunotherapy.

Immunotherapies are some of the most promising emergent treatments for several cancers, yet there remains a majority of patients who do not benefit from them due to immune-resistant tumors. One avenue for enhancing treatment for these patients is by converting these tumors to an immunoreactive state, thereby restoring treatment efficacy. By leveraging regulatory networks we previously characterized in autoimmunity, here we show that overexpression of the master regulator IKZF1 leads to enhanced immune infiltrate recruitment and tumor sensitivity to PD1 and CTLA4 inhibitors in several tumors that normally lack IKZF1 expression. This work provides proof of concept that tumors can be rendered susceptible by hijacking immune cell recruitment signals through molecular master regulators. On a broader scale, this work also demonstrates the feasibility of using computational approaches to drive the discovery of novel molecular mechanisms toward treatment.

Out of Many, One: Computational Reconstruction of Mouse Skin using Single-Cell Transcriptomics.

Mammalian skin is a complex and heterogeneous tissue with several distinct compartments and stem cell populations. Joost et al. (2016) now use single-cell RNaseq to comprehensively reconstruct this complexity, revealing spatial and pseudotemporal differences between transcriptional programs in distinct compartments and a common basal program in skin stem cell populations.

Safety and efficacy of the JAK inhibitor tofacitinib citrate in patients with alopecia areata.

BACKGROUND: Alopecia areata (AA) is an autoimmune disease characterized by hair loss mediated by CD8+ T cells. There are no reliably effective therapies for AA. Based on recent developments in the understanding of the pathomechanism of AA, JAK inhibitors appear to be a therapeutic option; however, their efficacy for the treatment of AA has not been systematically examined. METHODS: This was a 2-center, open-label, single-arm trial using the pan-JAK inhibitor, tofacitinib citrate, for AA with >50% scalp hair loss, alopecia totalis (AT), and alopecia universalis (AU). Tofacitinib (5 mg) was given twice daily for 3 months. Endpoints included regrowth of scalp hair, as assessed by the severity of alopecia tool (SALT), duration of hair growth after completion of therapy, and disease transcriptome. RESULTS: Of 66 subjects treated, 32% experienced 50% or greater improvement in SALT score. AA and ophiasis subtypes were more responsive than AT and AU subtypes. Shorter duration of disease and histological peribulbar inflammation on pretreatment scalp biopsies were associated with improvement in SALT score. Drug cessation resulted in disease relapse in 8.5 weeks. Adverse events were limited to grade I and II infections. An AA responsiveness to JAK/STAT inhibitors score was developed to segregate responders and nonresponders, and the previously developed AA disease activity index score tracked response to treatment. CONCLUSIONS: At the dose and duration studied, tofacitinib is a safe and effective treatment for severe AA, though it does not result in a durable response. Transcriptome changes reveal unexpected molecular complexity within the disease. TRIAL REGISTRATION: ClinicalTrials.gov NCT02197455 and NCT02312882. FUNDING: This work was supported by the US Department of Veterans Affairs Office of Research and Development, National Institute of Arthritis and Musculoskeletal and Skin Diseases National Institutes of Health grant R01 AR47223 and U01 AR67173, the National Psoriasis Foundation, the Swedish Society of Medicine, the Fernström Foundation, the Locks of Love Foundation, the National Alopecia Areata Foundation, and the Ranjini and Ajay Poddar Resource Fund for Dermatologic Diseases Research.

Molecular signatures define alopecia areata subtypes and transcriptional biomarkers.

Alopecia areata (AA) is an autoimmune disease typified by nonscarring hair loss with a variable clinical course. In this study, we conducted whole genome gene expression analysis of 96 human scalp skin biopsy specimens from AA or normal control subjects. Based on gene expression profiling, samples formed distinct clusters based on the presence or absence of disease as well as disease phenotype (patchy disease compared with alopecia totalis or universalis). Differential gene expression analysis allowed us to robustly demonstrate graded immune activity in samples of increasing phenotypic severity and generate a quantitative gene expression scoring system that classified samples based on interferon and cytotoxic T lymphocyte immune signatures critical for disease pathogenesis.

Master regulators of infiltrate recruitment in autoimmune disease identified through network-based molecular deconvolution.

Network-based molecular modeling of physiological behaviors has proven invaluable in the study of complex diseases such as cancer, but these approaches remain largely untested in contexts involving interacting tissues such as autoimmunity. Here, using Alopecia Areata (AA) as a model, we have adapted regulatory network analysis to specifically isolate physiological behaviors in the skin that contribute to the recruitment of immune cells in autoimmune disease. We use context-specific regulatory networks to deconvolve and identify skin-specific regulatory modules with IKZF1 and DLX4 as master regulators (MRs). These MRs are sufficient to induce AA-like molecular states in vitro in three cultured cell lines, resulting in induced NKG2D-dependent cytotoxicity. This work demonstrates the feasibility of a network-based approach for compartmentalizing and targeting molecular behaviors contributing to interactions between tissues in autoimmune disease.

Pharmacologic inhibition of JAK-STAT signaling promotes hair growth.

Several forms of hair loss in humans are characterized by the inability of hair follicles to enter the growth phase (anagen) of the hair cycle after being arrested in the resting phase (telogen). Current pharmacologic therapies have been largely unsuccessful in targeting pathways that can be selectively modulated to induce entry into anagen. We show that topical treatment of mouse and human skin with small-molecule inhibitors of the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway results in rapid onset of anagen and subsequent hair growth. We show that JAK inhibition regulates the activation of key hair follicle populations such as the hair germ and improves the inductivity of cultured human dermal papilla cells by controlling a molecular signature enriched in intact, fully inductive dermal papillae. Our findings open new avenues for exploration of JAK-STAT inhibition for promotion of hair growth and highlight the role of this pathway in regulating the activation of hair follicle stem cells.

DIGGIT: a Bioconductor package to infer genetic variants driving cellular phenotypes.

UNLABELLED: Identification of driver mutations in human diseases is often limited by cohort size and availability of appropriate statistical models. We propose a method for the systematic discovery of genetic alterations that are causal determinants of disease, by prioritizing genes upstream of functional disease drivers, within regulatory networks inferred de novo from experimental data. Here we present the implementation of Driver-gene Inference by Genetical-Genomic Information Theory as an R-system package. AVAILABILITY AND IMPLEMENTATION: The diggit package is freely available under the GPL-2 license from Bioconductor (http://www.bioconductor.org).

Identification of causal genetic drivers of human disease through systems-level analysis of regulatory networks.

Identification of driver mutations in human diseases is often limited by cohort size and availability of appropriate statistical models. We propose a framework for the systematic discovery of genetic alterations that are causal determinants of disease, by prioritizing genes upstream of functional disease drivers, within regulatory networks inferred de novo from experimental data. We tested this framework by identifying the genetic determinants of the mesenchymal subtype of glioblastoma. Our analysis uncovered KLHL9 deletions as upstream activators of two previously established master regulators of the subtype, C/EBPß and C/EBPδ. Rescue of KLHL9 expression induced proteasomal degradation of C/EBP proteins, abrogated the mesenchymal signature, and reduced tumor viability in vitro and in vivo. Deletions of KLHL9 were confirmed in > 50% of mesenchymal cases in an independent cohort, thus representing the most frequent genetic determinant of the subtype. The method generalized to study other human diseases, including breast cancer and Alzheimer's disease.

Microenvironmental reprogramming by three-dimensional culture enables dermal papilla cells to induce de novo human hair-follicle growth.

De novo organ regeneration has been observed in several lower organisms, as well as rodents; however, demonstrating these regenerative properties in human cells and tissues has been challenging. In the hair follicle, rodent hair follicle-derived dermal cells can interact with local epithelia and induce de novo hair follicles in a variety of hairless recipient skin sites. However, multiple attempts to recapitulate this process in humans using human dermal papilla cells in human skin have failed, suggesting that human dermal papilla cells lose key inductive properties upon culture. Here, we performed global gene expression analysis of human dermal papilla cells in culture and discovered very rapid and profound molecular signature changes linking their transition from a 3D to a 2D environment with early loss of their hair-inducing capacity. We demonstrate that the intact dermal papilla transcriptional signature can be partially restored by growth of papilla cells in 3D spheroid cultures. This signature change translates to a partial restoration of inductive capability, and we show that human dermal papilla cells, when grown as spheroids, are capable of inducing de novo hair follicles in human skin.

Spinal cord infarction remote from maximal compression in a patient with Morquio syndrome.

Morquio syndrome, or mucopolysaccharidosis type IV, is a rare enzyme deficiency disorder and results in skeletal dysplasia. Odontoid dysplasia is common among affected patients, resulting in atlantoaxial instability and spinal cord compression. Surgical treatments include decompression and prophylactic fusion, during which intraoperative neuromonitoring is important to alert the surgical team to changes in cord function so that they can prevent or mitigate spinal cord injury. This report describes a 16-year-old girl with Morquio syndrome who developed paraplegia due to thoracic spinal cord infarction during foramen magnum and atlantal decompression. This tragic event demonstrates the following: 1) that patients with Morquio syndrome are at risk for ischemic spinal cord injury at levels remote from areas of maximal anatomical compression while under anesthesia in the prone position, possibly due to impaired cardiac output; 2) the significance of absent motor evoked potential responses in the lower limbs with preserved upper-limb responses in an ambulatory patient; 3) the importance of establishing intraoperative neuromonitoring baseline assessments prior to turning patients to the prone position following induction of anesthesia; and 4) the importance of monitoring cardiac output during prone positioning in patients with chest wall deformity.

Talaporfin sodium.

IMPORTANCE OF THE FIELD: Despite therapeutic advances, cancer remains the cause of an estimated 23% of deaths in the USA. New treatments for malignancy are greatly needed. AREAS COVERED IN THIS REVIEW: Talaporfin sodium is a light-activated drug that causes tissue death through induction of apoptosis. Systemic antitumor effects mediated by CD8(+) T cells have been demonstrated in preclinical studies, providing a mechanism for distant response of tumors noted in clinical trials. Talaporfin sodium is approved in Japan for early-stage endobronchial cancer. Phase I and II studies in solid tumors have shown tumor regression in patients refractory to other therapies. Phase III pivotal studies against hepatocellular carcinoma as monotherapy and liver-metastatic colorectal cancer in combination with chemotherapy are ongoing. Talaporfin sodium is also in studies in men with symptomatic benign prostatic hyperplasia. Substantial safety data from clinical trials so far indicate that the drug is well tolerated. WHAT THE READER WILL GAIN: Talaporfin sodium has a broad safety profile and a mode of action that could affect growth in treated and untreated tumors. TAKE HOME MESSAGE: Clinical and preclinical studies indicate that talaporfin sodium treatment may offer a powerful option to synergize current therapies, as well as an alternative monotherapy in treating cancer.

A multicenter Phase I safety study of intratumoral photoactivation of talaporfin sodium in patients with refractory solid tumors.

BACKGROUND: Photodynamic therapy (PDT) currently is approved for the palliative treatment of malignancies of the aerodigestive tract using laser-activated porfimer sodium. A new approach has been developed, based on intratumoral placement of a nonlaser light device that activates talaporfin sodium, that may expand the use of PDT to include a broader range of treatment-resistant malignancies. The safety of this approach was assessed in a Phase I study in patients with locally advanced, refractory tumors. METHODS: Twenty-one patients with radiation-resistant or chemotherapy-resistant or inoperable malignancies were enrolled in four cohorts representing four light doses. Patients were treated with a single intratumoral light device and a fixed photosensitizer dose. Safety assessments were based on review of adverse events (AEs) and serious adverse events (SAEs), and independent evaluation of computed tomography (CT) images. RESULTS: The observed occurrence of treatment-related AEs and SAEs was minimal. No cutaneous phototoxicity was observed in any patient. The overall observed tumor response rate was 33%. CONCLUSIONS: Photoactivation of talaporfin sodium using intratumoral nonlaser light was found to be safe in the patient population of the current study at all light dose levels tested.