Background Transition to digital pathology usually takes months or years to be completed. We were familiarizing ourselves with digital pathology solutions at the time when the COVID-19 outbreak forced us to embark on an abrupt transition to digital pathology. Objective The aim of this study was to quantitatively describe how the abrupt transition to digital pathology might affect the quality of diagnoses, model possible causes by probabilistic modeling, and qualitatively gauge the perception of this abrupt transition. Methods A total of 17 pathologists and residents participated in this study; these participants reviewed 25 additional test cases from the archives and completed a final psychologic survey. For each case, participants performed several different diagnostic tasks, and their results were recorded and compared with the original diagnoses performed using the gold standard method (ie, conventional microscopy). We performed Bayesian data analysis with probabilistic modeling. Results The overall analysis, comprising 1345 different items, resulted in a 9% (117/1345) error rate in using digital slides. The task of differentiating a neoplastic process from a nonneoplastic one accounted for an error rate of 10.7% (42/392), whereas the distinction of a malignant process from a benign one accounted for an error rate of 4.2% (11/258). Apart from residents, senior pathologists generated most discrepancies (7.9%, 13/164). Our model showed that these differences among career levels persisted even after adjusting for other factors. Conclusions Our findings are in line with previous findings, emphasizing that the duration of transition (ie, lengthy or abrupt) might not influence the diagnostic performance. Moreover, our findings highlight that senior pathologists may be limited by a digital gap, which may negatively affect their performance with digital pathology. These results can guide the process of digital transition in the field of pathology.

Introduction Numerous scoring systems have been created to predict the risk of morbidity and mortality in patients undergoing emergency general surgery (EGS).In this article, we compared the different scoring systems utilized at Humanitas Research Hospital and analyzed which one performed the best when assessing geriatric patients (>65 years of age). The scoring systems that were utilized were the APACHE II (Acute Physiology and Chronic Health Evaluation II), ASA (American Society of Anesthesiologists), ACS-NSQIP (American College of Surgeons-National Surgical Quality Improvement Program), Clinical Frailty Score, and the Clavien–Dindo classification as control. Materials and Methods We compiled a database consisting of all patients over the age of 65 who underwent EGS in a consecutive 24-month period between January 1, 2017 and December 31, 2018. We used the biostatistical program “Stata Version 15” to analyze our results. Results We found 213 patients who matched our inclusion criteria. Regarding death, we found that the ACS-NSQIP death calculator performed the best with an area under the curve of 0.9017 (odds ratio: 1.09; 95% confidence interval: 1.06–1.12). The APACHE II score had the lowest discriminator when predicting death. Considering short-term complications, the Clavien–Dindo classification scored highly, while both the APACHE II score and Clinical Frailty Score produced the lowest results. Conclusion The results obtained from our research showed that scoring systems and classifications produced different results depending on whether they were used to predict deaths or short-term complications among geriatric patients undergoing EGS.

IntroductionDue to an aging population, the rising prevalence and incidence of hip fractures and the associated health and economic burden present a challenge to healthcare systems worldwide. Studies have shown that a complex interplay of physiological, psychological, and social factors often affects the recovery trajectories of older adults with hip fractures, often complicating the recovery process.MethodsThis research aims to actively engage stakeholders (including doctors, physiotherapists, hip fracture patients, and caregivers) using the systems modeling methodology of Group Model Building (GMB) to elicit the factors that promote or inhibit hip fracture recovery, incorporating a feedback perspective to inform system-wide interventions. Hip fracture stakeholder engagement was facilitated through the Group Model Building approach in a two-half-day workshop of 25 stakeholders. This approach combined different techniques to develop a comprehensive qualitative whole-system view model of the factors that promote or inhibit hip fracture recovery.ResultsA conceptual, qualitative model of the dynamics of hip fracture recovery was developed that draws on stakeholders' personal experiences through a moderated interaction. Stakeholders identified four domains (i.e., expectation formation, rehabilitation, affordability/availability, and resilience building) that play a significant role in the hip fracture recovery journey..DiscussionThe insight that recovery of loss of function due to hip fracture is attributed to (a) the recognition of a gap between pre-fracture physical function and current physical function; and (b) the marshaling of psychological resilience to respond promptly to a physical functional loss via uptake of rehabilitation services is supported by findings and has several policy implications.

Introduction Emergency General Surgery (EGS) deals with the most critical of patients. It is a field that requires the precise and timely execution of life-saving interventions. For this reason, many studies have been conducted in order to find the optimal management plans. Our research compared different scoring systems, to see which performed best in regard to Geriatric patients. Scoring systems included: APACHE II, ASA, ACS-NSQIP, MPI, and Frailty Score. The Clavien Dindo classification was utilised as a comparative tool. Our secondary objective was to determine which variables had the greatest effect on patient outcomes. These variables included Age, Sex, BMI, Time to Surgery, Beta-blockers, ‘Open Abdomen’ treatment, Blood Transfusions, Anticoagulants, and Vasopressors. Method The database included 212 patients who underwent EGS in a consecutive 24-month period. Results All of the scoring systems proved to be statistically significant with the ACS and the ASA being most effective for predicting death and short-term complications. Regarding variables, we performed both univariate and multivariate testing. For predicting the risk of death, ‘Open Abdomen treatment’, Blood Transfusions, and Vasopressors were statistically significant. For estimating the risk of short-term complications only Blood Transfusions and Vasopressors proved significant Conclusions We must take into consideration that the other systems had significant results, therefore we must contemplate if there were compounding factors. To rectify this, further studies should be conducted ensuring correct parameters are respected, for example, the APACHE II should only be used in ICU patients and within the first 24 hours of admission.