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\"Reframing Leadership translates Bolman & Deal's influential four-frame model of leadership and organizations developed in their bestselling Jossey-Bass Book, Reframing Organizations: Artistry, Choice and Leadership, (over 300,000 copies sold in 4 editions, $7M in net revenue) into a thought-provoking and practical guide for leaders in business and other organizations. This book will offer leaders a template and guide for understanding four major dimensions of organizational life: structure, people, politics, and symbols (or culture) that will enable them to decode the messy world in which they live, see a broader range of options, and find more powerful and elegant strategies for leading\"-- Provided by publisher.

Inadequacies in healthcare access and utilization substantially impact outcomes for diabetic patients. The All of Us database offers extensive survey data pertaining to social determinants that is not routinely available in electronic health records. This study assesses whether social determinants were associated with an increased risk of developing proliferative diabetic retinopathy or related complications (e.g. related diagnoses or procedures). We identified 729 adult participants in the National Institutes of Health All of Us Research Program data repository with diabetic retinopathy (DR) who answered survey questions pertaining to healthcare access and utilization. Electronic health record data regarding co-morbidities, laboratory values, and procedures were extracted. Multivariable logistic regression with bi-directional stepwise variable selection was performed from a wide range of predictors. Statistical significance was defined as p<0.05. The mean (standard deviation) age of our cohort was 64.9 (11.4) years. 15.2% identified as Hispanic or Latino, 20.4% identified as Black, 60.6% identified as White, and 19.3% identified as Other. 10-20% of patients endorsed several reasons for avoiding or delaying care, including financial concerns and lack of access to transportation. Additional significant social determinants included race and religion discordance between healthcare provider and patient (odds ratio [OR] 1.20, 95% confidence interval [CI] 1.02-1.41, p = 0.03) and caregiver responsibilities toward others (OR 3.14, 95% CI 1.01-9.50, p = 0.04). Nationwide data demonstrate substantial barriers to healthcare access among DR patients. In addition to financial and social determinants, race and religion discordance between providers and patients may increase the likelihood of PDR and related complications.

Mucosal healing (MH) in inflammatory bowel disease has been associated with improved long-term clinical outcomes. Uncertainty remains as to the magnitude of this effect and to how this association changes with time and degree of healing.MethodsPubMed, EMBASE, and Web of Science searches identified 1570 citations. Screening of abstracts identified 155 articles for full-text review, of which 19 met inclusion criteria. For 3 outcomes of interest (surgeries, hospitalizations, remission), weighted random-effects meta-analysis was performed.ResultsIn pooled analysis, MH predicted fewer major abdominal surgeries (relative risk [RR], 0.34; 95% confidence interval [CI], 0.26–0.46), increased remission (RR, 1.84; 95% CI, 1.43–2.36), and fewer hospitalizations (RR, 0.58; 95% CI, 0.42–0.78). Complete MH and partial MH both showed significantly higher rates of favorable outcomes. Separate analyses for Crohn's disease and ulcerative colitis showed identical patterns for surgeries and remission. When subjects with no healing were excluded, and complete versus partial healing was compared, rates of surgery were not significantly different (RR, 0.82; 95% CI, 0.46–1.44). However, complete healing was superior in predicting corticosteroid-free remission (RR, 1.71; 95% CI, 1.24–2.34). Meta-regression found that the predictive power of this complete versus partial healing distinction was strongly associated with the duration of follow-up after endoscopy.ConclusionsMH is a strong predictor of fewer surgeries, long-term clinical remission, and fewer hospitalizations. Complete healing is not significantly more favorable than partial healing for predicting surgeries or hospitalizations, but it did predict higher rates of clinical remission. This benefit of complete MH over partial healing increases with follow-up time.

Predictive analytics using electronic health record (EHR) data have rapidly advanced over the last decade. While model performance metrics have improved considerably, best practices for implementing predictive models into clinical settings for point-of-care risk stratification are still evolving. Here, we conducted a systematic review of articles describing predictive models integrated into EHR systems and implemented in clinical practice. We conducted an exhaustive database search and extracted data encompassing multiple facets of implementation. We assessed study quality and level of evidence. We obtained an initial 3393 articles for screening, from which a final set of 44 articles was included for data extraction and analysis. The most common clinical domains of implemented predictive models were related to thrombotic disorders/anticoagulation (25%) and sepsis (16%). The majority of studies were conducted in inpatient academic settings. Implementation challenges included alert fatigue, lack of training, and increased work burden on the care team. Of 32 studies that reported effects on clinical outcomes, 22 (69%) demonstrated improvement after model implementation. Overall, EHR-based predictive models offer promising results for improving clinical outcomes, although several gaps in the literature remain, and most study designs were observational. Future studies using randomized controlled trials may help improve the generalizability of findings.

When general anesthesia is used for endovascular thrombectomy (EVT) for acute ischemic stroke (AIS), the choice of anesthetic agents for maintenance remains inconclusive. The different effects of intravenous anesthetic and volatiles agents on cerebral hemodynamics are known and may explain differences in outcomes of patients with cerebral pathologies exposed to the different anesthetic modalities. In this single institutional retrospective study, we assessed the impact of total intravenous (TIVA) and inhalational anesthesia on outcomes after EVT. We conducted a retrospective analysis of all patients ≥ 18 years who underwent EVT for AIS of the anterior or posterior circulation under general anesthesia. Baseline patient characteristics, anesthetic agents, intra operative hemodynamics, stroke characteristics, time intervals and clinical outcome data were collected and analyzed. The study cohort consisted of 191 patients. After excluding 76 patients who were lost to follow up at 90 days, 51 patients received inhalational anesthesia and 64 patients who received TIVA were analyzed. The clinical characteristics between the groups were comparable. Multivariate logistic regression analysis of outcome measures for TIVA versus inhalational anesthesia showed significantly increased odds of good functional outcome (mRS 0–2) at 90 days (adjusted odds ratio, 3.24; 95% CI, 1.25–8.36; p = 0.015) and a non-significant trend towards decreased mortality (adjusted odds ratio, 0.73; CI, 0.15–3.6; p = 0.70). Patients who had TIVA for mechanical thrombectomy had significantly increased odds of good functional outcome at 90 days and a non-significant trend towards decrease in mortality. These findings warrant further investigation with large randomized, prospective trials.

•When comparing stroke admissions from March 1st-May 10th in 2019 and 2020 at a single comprehensive stroke center in Middle East, there was a 41.9% increase in stroke admissions in 2020. A higher rate of large vessel occlusion (LVO) and significant delay in initiation of mechanical thrombectomy after hospital arrival was observed in 2020.•Among all COVID-19 admissions in 2020, 5.24% patients suffered stroke including 3.21% with ischemic and 2% with hemorrhagic stroke.•Patients with COVID-19 and ischemic stroke were significantly younger, predominantly male, had fewer vascular risk factors, had more severe clinical presentation, and higher rate of LVO ccompared to ischemic stroke patients without COVID-19•For hemorrhagic stroke, COVID-19 patients did not differ from non-COVID-19 patients. To compare ischemic and hemorrhagic stroke patients with COVID-19 to non-COVID-19 controls, and to describe changes in stroke admission patterns during the pandemic. This is a single center, retrospective, observational study. All consecutive patients admitted with primary diagnosis of ischemic/ hemorrhagic stroke between March1st -May10th 2020 were included and compared with the same time period in 2019. There was a 41.9% increase in stroke admissions in 2020 (148 vs 210,P = .001). When comparing all ischemic strokes, higher rate of large vessel occlusion (LVO) (18.3% vs 33.8%,P = .008) and significant delay in initiation of mechanical thrombectomy after hospital arrival (67.75 vs 104.30 minutes,P = .001) was observed in 2020. When comparing all hemorrhagic strokes, there were no differences between the two years. Among 591 COVID-19 admissions, 31 (5.24%) patients with stroke including 19 with ischemic (3.21%) and 12 with hemorrhagic stroke (2.03%) were identified. Patients with COVID-19 and ischemic stroke were significantly younger (58.74 vs 48.11 years,P = .002), predominantly male (68.18% vs 94.74%,P = .016), had lesser vascular risk factors, had more severe clinical presentation (NIHSS 7.01 vs 17.05,P < .001), and higher rate of LVO (23.6% vs. 63.1%,P = .006). There was no difference in the rate of endovascular thrombectomy, but time to groin puncture was significantly longer in COVID-19 patients (83.41 vs 129.50 minutes,P = .003). For hemorrhagic stroke, COVID-19 patients did not differ from non-COVID-19 patients. Stroke continues to occur during this pandemic and stroke pathways have been affected by the pandemic. Stroke occurs in approximately 5% of patients with COVID-19. COVID-19 associated ischemic stroke occurs in predominantly male patients who are younger, with fewer vascular risk factors, can be more severe, and have higher rates of LVO. Despite an increase in LVO during the pandemic, treatment with mechanical thrombectomy has not increased. COVID-19 associated hemorrhagic stroke does not differ from non-COVID-19 hemorrhagic stroke patients.

[This corrects the article DOI: 10.1371/journal.pone.0269231.].

This manuscript presents a proof-of-concept for a generalizable strategy, the full algorithm , designed to estimate disease risk using real-world clinical tabular data systems, such as electronic health records (EHR) or claims databases. By integrating classic statistical methods and modern artificial intelligence techniques, this strategy automates the production of a disease prediction model that comprehensively reflects the dynamics contained within the underlying data system. Specifically, the full algorithm parses through every facet of the data (e.g., encounters, diagnoses, procedures, medications, labs, chief complaints, flowsheets, vital signs, demographics, etc.), selects which factors to retain as predictor variables by evaluating the data empirically against statistical criteria, structures and formats the retained data into time-series, trains a neural network-based prediction model, then subsequently applies this model to current patients to generate risk estimates. A distinguishing feature of the proposed strategy is that it produces a self-adaptive prediction system, capable of evolving the prediction mechanism in response to changes within the data: as newly collected data expand/modify the dataset organically, the prediction mechanism automatically evolves to reflect these changes. Moreover, the full algorithm operates without the need for a-priori data curation and aims to harness all informative risk and protective factors within the real-world data. This stands in contrast to traditional approaches, which often rely on highly curated datasets and domain expertise to build static prediction models based solely on well-known risk factors. As a proof-of-concept, we codified the full algorithm and tasked it with estimating 12-month risk of initial stroke or myocardial infarction using our hospital’s real-world EHR. A 66-month pseudo-prospective validation was conducted using records from 558,105 patients spanning April 2015 to September 2023, totalling 3,424,060 patient-months. Area under the receiver operating characteristic curve (AUROC) values ranged from .830 to .909, with an improving trend over time. Odds ratios describing model precision for patients 1–100 and 101–200 (when ranked by estimated risk) ranged from 15.3 to 48.1 and 7.2 to 45.0, respectively, with both groups showing improving trends over time. Findings suggest the feasibility of developing high-performing disease risk calculators in the proposed manner.

Purpose Phakic lens implantation in the ciliary sulcus of the eye can be complicated by coincident ciliary body cysts (CBC). We developed an ultrasound imaging and mapping protocol for these cysts. Methods This is a retrospective case series of all patients who underwent ICL workup at a single institution from April 2015 to October 2019. A standardized ultrasound biomicroscopy (UBM) imaging protocol was developed to screen for CBCs in either the ciliary body or sulcus. The locations and dimensions of all CBCs were graphically represented. Results The prevalence of CBCs in 158 patients undergoing ICL workup was 34.8%. Among the 159 CBCs detected in 55 patients, 83 were in the sulcus (52%) and 76 were restricted to the ciliary body (48%). ICLs were implanted in 40 eyes with CBCs and 3 eyes with CBCs located within the sulcus horizontally required ICL repositioning due to ICL rotation or iris chafing. Conclusion CBCs were incidentally found in 34.8% of patients undergoing ICL workup. ICL implantation was complicated in 3 of the eyes with CBCs in the horizontal sulcus. Although CBCs are not an absolute contraindication for ICL surgery, we recommend preoperative UBM screening of the ciliary sulcus.