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Background Admitted patients who fall and injure themselves during an acute hospitalization incur increased costs, morbidity, and mortality, but little research has been conducted on identifying inpatients at high risk to injure themselves in a fall. Falls risk assessment tools have been unsuccessful due to their low positive predictive value when applied broadly to entire hospital populations. We aimed to identify variables associated with the risk of or protection against injurious fall in the inpatient setting. We also aimed to test the variables in the ABCs mnemonic ( A ge > 85, B ones-orthopedic conditions, anti- C oagulation and recent s urgery) for correlation with injurious fall. Methods We performed a retrospective case-control study at an academic tertiary care center comparing admitted patients with injurious fall to admitted patients without fall. We collected data on the demographics, medical and fall history, outcomes, and discharge disposition of injured fallers and control patients. We performed multivariate analysis of potential risk factors for injurious fall with logistic regression to calculate adjusted odds ratios. Results We identified 117 injured fallers and 320 controls. There were no differences in age, anti-coagulation use or fragility fractures between cases and controls. In multivariate analysis, recent surgery (OR 0.46, p  = 0.003) was protective; joint replacement (OR 5.58, P  = 0.002), psychotropic agents (OR 2.23, p  = 0.001), the male sex (OR 2.08, p  = 0.003) and history of fall (OR 2.08, p  = 0.02) were significantly associated with injurious fall. Conclusion In this study, the variables in the ABCs parameters were among the variables not useful for identifying inpatients at risk of injuring themselves in a fall, while other non-ABCs variables demonstrated a significant association with injurious fall. Recent surgery was a protective factor, and practices around the care of surgical patients could be extrapolated to reduce the in-hospital fall rates.

Background Achieving an academic section’s educational mission and vision is difficult, particularly when individual faculty contributions may be self-directed and uncoordinated. Balanced scorecards have been used in other environments; however, a process for developing one focusing on the educational mission of an academic medical section has not previously been described. We aimed to develop and use an educational scorecard to help our academic clinical section achieve its educational mission and vision. Methods Six medical educators participated in a task force that developed, implemented, and evaluated an educational scorecard that incorporates four domains of educational value and six stakeholder perspectives. A modified Delphi process using 14 experts built expert consensus on the most valuable metrics. The task force then developed performance targets for each metric. Results Review of the scorecard at the sectional level resulted in both sectional and individual strategies which lead to a more balanced educational impact, including service structure changes and increased mentorship. Our section has used the scorecard and metrics to evaluate performance since 2014. Conclusion An educational scorecard is a feasible way for academic groups to communicate educational goals, engage faculty, and provide objective information with which to base strategic decisions affecting their educational mission.

Key Clinical Message Sodium thiosulfate (STS), first‐line treatment for calcific uremic arteriolopathy, causes a mild asymptomatic acidosis in many patients. However, severe, life‐threatening acidosis out of proportion with the expected acid load of STS may occur, potentially due to metabolism of STS to hydrogen sulfide. Sodium thiosulfate (STS), first‐line treatment for calcific uremic arteriolopathy, causes a mild asymptomatic acidosis in many patients. However, severe, life‐threatening acidosis out of proportion with the expected acid load of STS may occur, potentially due to metabolism of STS to hydrogen sulfide.

Background: Little research to date has examined the quality of data obtained from resident performance evaluations. This study sought to address this need and compared inter-rater reliability obtained from norm-referenced and criterion-referenced evaluation scaling approaches for faculty completing resident performance evaluations.Methods: Resident performance evaluation data were examined from 2 institutions (3 programs, 2 internal medicine and 1 surgery; 426 residents in total), with 4 evaluation forms: 2 criterion-referenced (1 with an additional norm-referenced item) and 2 norm-referenced. Faculty inter-rater reliability was calculated with intraclass correlation coefficients (ICCs) (1,10) for each competency area within the form. ICCs were transformed to z-scores, and 95% CIs were computed. Reliabilities for each evaluation form and competency, averages within competency, and averages within scaling type were examined.Results: Inter-rater reliability averages were higher for all competencies that used criterion-referenced scaling relative to those that used norm-referenced scaling. Aggregate scores of all independent categories (competencies and the items assessing overall competence) for criterion-referenced scaling demonstrated higher reliability (z=1.37, CI 1.26-1.48) than norm-referenced scaling (z=0.88, CI 0.77-0.99). Moreover, examination of the distributions of composite scores (average of all competencies and raters for each individual being rated) suggested that the criterion-referenced evaluations better represented the performance continuum.Conclusion: Criterion-referenced evaluation approaches appear to provide superior inter-rater reliability relative to norm-referenced evaluation scaling approaches. Although more research is needed to identify resident evaluation best practices, using criterion-referenced scaling may provide more valid data than norm-referenced scaling.

Background Written comments by medical student supervisors provide written foundation for grade narratives and deans’ letters and play an important role in student’s professional development. Written comments are widely used but little has been published about the quality of written comments. We hypothesized that medical students share an understanding of qualities inherent to a high-quality and a low-quality narrative comment and we aimed to determine the features that define high- and low-quality comments. Methods Using the well-established anthropological pile-sort method, medical students sorted written comments into ‘helpful’ and ‘unhelpful’ piles, then were interviewed to determine how they evaluated comments. We used multidimensional scaling and cluster analysis to analyze data, revealing how written comments were sorted across student participants. We calculated the degree of shared knowledge to determine the level of internal validity in the data. We transcribed and coded data elicited during the structured interview to contextualize the student’s answers. Length of comment was compared using one-way analysis of variance; valence and frequency comments were thought of as helpful were analyzed by chi-square. Results Analysis of written comments revealed four distinct clusters. Cluster A comments reinforced good behaviors or gave constructive criticism for how changes could be made. Cluster B comments exhorted students to continue non-specific behaviors already exhibited. Cluster C comments used grading rubric terms without giving student-specific examples. Cluster D comments used sentence fragments lacking verbs and punctuation. Student data exhibited a strong fit to the consensus model, demonstrating that medical students share a robust model of attributes of helpful and unhelpful comments. There was no correlation between valence of comment and perceived helpfulness. Conclusions Students find comments demonstrating knowledge of the student and providing specific examples of appropriate behavior to be reinforced or inappropriate behavior to be eliminated helpful, and comments that are non-actionable and non-specific to be least helpful. Our research and analysis allow us to make recommendations helpful for faculty development around written feedback.

The ciliate Tetrahymena thermophila is a model organism for molecular and cellular biology. Like other ciliates, this species has separate germline and soma functions that are embodied by distinct nuclei within a single cell. The germline-like micronucleus (MIC) has its genome held in reserve for sexual reproduction. The soma-like macronucleus (MAC), which possesses a genome processed from that of the MIC, is the center of gene expression and does not directly contribute DNA to sexual progeny. We report here the shotgun sequencing, assembly, and analysis of the MAC genome of T. thermophila, which is approximately 104 Mb in length and composed of approximately 225 chromosomes. Overall, the gene set is robust, with more than 27,000 predicted protein-coding genes, 15,000 of which have strong matches to genes in other organisms. The functional diversity encoded by these genes is substantial and reflects the complexity of processes required for a free-living, predatory, single-celled organism. This is highlighted by the abundance of lineage-specific duplications of genes with predicted roles in sensing and responding to environmental conditions (e.g., kinases), using diverse resources (e.g., proteases and transporters), and generating structural complexity (e.g., kinesins and dyneins). In contrast to the other lineages of alveolates (apicomplexans and dinoflagellates), no compelling evidence could be found for plastid-derived genes in the genome. UGA, the only T. thermophila stop codon, is used in some genes to encode selenocysteine, thus making this organism the first known with the potential to translate all 64 codons in nuclear genes into amino acids. We present genomic evidence supporting the hypothesis that the excision of DNA from the MIC to generate the MAC specifically targets foreign DNA as a form of genome self-defense. The combination of the genome sequence, the functional diversity encoded therein, and the presence of some pathways missing from other model organisms makes T. thermophila an ideal model for functional genomic studies to address biological, biomedical, and biotechnological questions of fundamental importance.

Background: Physicians and patients frequently overestimate likelihood of survival after in-hospital cardiopulmonary resuscitation. Discussions and decisions around resuscitation after in-hospital cardiopulmonary arrest often take place without adequate or accurate information. Methods: We conducted a retrospective chart review of 470 instances of resuscitation after in-hospital cardiopulmonary arrest. Individuals were randomly assigned to a derivation cohort and a validation cohort. Logistic Regression and Linear Discriminant Analysis were used to perform multivariate analysis of the data. The resultant best performing rule was converted to a weighted integer tool, and thresholds of survival and nonsurvival were determined with an attempt to optimize sensitivity and specificity for survival. Results: A 10-feature rule, using thresholds for survival and nonsurvival, was created; the sensitivity of the rule on the validation cohort was 42.7% and specificity was 82.4%. In the Dartmouth Score (DS), the features of age (greater than 70 years of age), history of cancer, previous cardiovascular accident, and presence of coma, hypotension, abnormal PaO^sub 2^, and abnormal bicarbonate were identified as the best predictors of nonsurvival. Angina, dementia, and chronic respiratory insufficiency were selected as protective features. Conclusions: Utilizing information easily obtainable on admission, our clinical prediction tool, the DS, provides physicians individualized information about their patients' probability of survival after in-hospital cardiopulmonary arrest. The DS may become a useful addition to medical expertise and clinical judgment in evaluating and communicating an individual's probability of survival after in-hospital cardiopulmonary arrest after it is validated by other cohorts.

International incidence rates (IRs) and trends of childhood type 1 diabetes (T1D) vary. Recent data from Ireland and other high incidence countries suggested a stabilisation in IRs of T1D in children aged under 15 years. Our primary objective was to report the IR of T1D in children in Ireland from 2019 to 2021 and evaluate if age, sex and season of diagnosis had changed. Incident cases of T1D in those aged under 15 years were identified prospectively by clinicians nationally and reported to the Irish Childhood Diabetes National Register (ICDNR). Following case verification, capture-recapture methodology was applied, and IRs calculated. Numbers of children including age, sex and season of diagnosis per year were evaluated. There were 1027 cases, 542 males (53%). The direct standardised incidence rates (SIRs) increased by 21% overall and were 31.1, 32.2 and 37.6/100,000/year, respectively, with no significant sex difference. The highest IRs were in the 10–14-year category until 2021, then changed to the 5–9-year category (40% of cases). Whilst autumn and winter remain dominant diagnostic seasons, seasonality differed in 2021 with a greater number presenting in spring. Conclusion : The incidence of childhood T1D in Ireland is increasing, observed prior to the COVID-19 pandemic, and shifting to an earlier age at diagnosis for the first time. The pattern of seasonality also appears to have changed. This may reflect an increased severity of diabetes with important implications for healthcare providers. What is Known: • Ireland has a very high incidence of T1D in childhood, which had stabilised following a rapid rise, similar to other high incidence countries. • The incidence rate is consistently highest in older children (10–14 years). What is New: • Irish IR is no longer stable and has increased again, with the highest incidence occurring in the younger 5-9 age category for the first time. • The seasonality of diagnosis has changed during the COVID-19 pandemic years of 2020–2021.

The Irish Childhood Diabetes National Register (ICDNR) was established in 2008 to define accurately the incidence and monitor the epidemiology of type 1 diabetes (T1D) in the Irish population. Here, we report data from the first 6 years of the National Register and compare with previous national data. Prospective national incident data regarding T1D in those under 15 years resident in Ireland were collected from 2008 to 2013 and national incidence rates (IRs) calculated. Ascertainment completeness was assessed using capture-recapture methodology. The period identified 1566 new cases of T1D, ascertainment reached 96.8 % in 2013. The standardised incidence rate was 27.5 in 2008 stabilising at 28.7 and 28.8 cases /100,000/year in 2012 and 2013. There was no evidence that the incidence changed significantly in the 6-year period either overall or for each age group and gender. There was evidence of a difference in the incidence of T1D across the age groups with the overall incidence highest in the 10–14 year age category. A strong seasonal association was demonstrated. Conclusions : This study confirms Ireland as a high-incidence country for type 1 diabetes whilst demonstrating that the previous marked increase in IR from 16.3 cases/100,000/year in 1997 has not continued. Ongoing monitoring through the robust mechanism of the ICDNR is required to clarify whether this is a fluctuation or if the incidence of T1D diabetes has stopped rising in our population. Alternatively, this apparent stabilisation may reflect a shift to a later age at diagnosis. “What is known :” • The incidence of Type 1 diabetes (T1D) is increasing in most populations worldwide although in certain high-incidence populations, it may be stabilising • There was a marked increase in T1D in Ireland between 1997 and 2008 • T1D incidence increases with affluence “What is New:” • The high incidence of T1D in Ireland has been confirmed at 28.8 cases/100,000/year in 2013 and has been effectively stable in the period 2008–2013 • Incidence is highest in Irish 10–14 year olds • Changes in incidence possibly reflecting life style and economic climate • Marked seasonality of diagnosis confirmed

AimPrior to the work of the Irish Childhood Diabetes National Register (ICDNR) there were no reliable data regarding the incidence of Type 1 Diabetes (T1D) in Ireland (a basic WHO health indicator). Limited data suggested Ireland had the lowest incidence in Europe, at 6.8 cases/100,000/year. A 1997 feasibility national incidence study was undertaken prior to the commencement of the ICDNR in 2008. The ICDNR collaborates with EURODIAB. The aim of this study was to report the incidence rates and annual percentage change (APC) since first calculated in 1997 up to the most recent rates in 2021.Material and MethodThe 1997 study and ICDNR employed the same methodology. All institutions responsible for the diagnosis and treatment of children with T1D under fifteen years nationally participate and prospectively reported all eligible new T1D cases. Following written informed consent, a detailed case report form was completed, and all cases verified. Following full registration capture-recapture methodology was applied collaborating with the Primary Care Reimbursement and Eligibility Service (PCRES). Standardised incidence rates (SIRs), using the direct method, were calculated to permit comparison internationally and over time. Population data derived from national census data from the Central Statistics Office was employed.ResultsThe baseline national study found the SIR for all children was 16.3 per 100,000/year, in the top 25% for Europe. In the 11-year period, to 2008, the incidence increased by 69.2% to 27.5/100,000/yr. The annual rate of change varied over the period (table 1).Abstract PP-019 Table 1Annual percentage change in standardised incidence rates by sex 1997–2021 Years Males and Females Percentage (%) Males (%) Females (%) 1997 - 2008 + 6.3 + 7.1 + 5.4 2008 - 2009 - 5.7 - 11.5 + 0.9 2009 - 2010 - 1.5 + 2.7 - 6.1 2010 - 2011 + 11.7 - 1.1 + 25.7 2011 - 2012 + 0.3 + 17.5 - 14.0 2012 - 2013 + 0.6 - 5.3 + 6.4 2013 - 2014 - 2.9 - 2.2 - 2.7 2014 - 2015 + 5.4 + 5.2 + 5.8 2015 - 2016 + 4.5 + 11.3 - 3.2 2016 - 2017 - 12.4 - 10.2 - 15.2 2017 - 2018 + 0.4 - 2.1 + 3.6 2018 - 2019 + 14.2 + 7.3 + 22.9 2019 - 2020 + 4.3 + 6.1 + 2.3 2020 - 2021 + 16.9 + 15.7 + 18.4 ConclusionsThe rate of change in the SIR stabilised, with minor fluctuations to 2018 after which it increased, again prior to and during the COVID-19 pandemic. This pattern is similar to other high incidence countries. In the periods of highest increase, the age category of diagnosis changed from 10–14 years to the younger 5–9.99 year age category, likely due to increased environmental pressure.