I-NURSE: Identifying and Automatically Detecting Topics in Nursing Handover Communications

I would like to thank The Ohio State University College of Arts and Sciences Honors Department for both the Summer Funding Grant and the Undergraduate Research Scholarship I received to pursue this project.Statement of the Problem Patient handovers have been described as the process of transferring primary authority and responsibility for providing clinical care to a patient from one departing caregiver to one oncoming caregiver. Patient handovers with incomplete and inaccurate information have repeatedly been identified as a patient safety risk. Recently a study using the mnemonic IPASS found that post-intervention the use of these strategies decreased medical errors by 23% and the rate of preventable adverse effects by 30%. The coding analysis used in the IPASS study and many others can be time consuming and cost-ineffective. As a result there is a desire to automate this analysis. Methodology 20 existing transcripts from a previously IRB-approved data collection of audio-recorded Intensive Care Unit Registered Nurse handovers containing 27 patient discussions collected from a single, academic tertiary care institution were analyzed for this study. First all 20 transcripts were manually coded using a codebook (IPASS) adapted from Starmer et. al’s paper Changes in Medical Errors after Implementation of a Handoff Program. Next, a novel codebook was manually generated from the transcripts in an effort to more accurately model nurse handovers. The categories which emerged were grouped into INURSE (Identification, Narrative, Unusual Symptoms, Response, Status, Expected Challenges). Finally, Linguistic Inquiry and Word Count (LIWC) software was used to identify family terms that fell under the INURSE codes Narrative Family and Expected Family Challenges. The manually coded transcripts were the gold standard against which the LIWC coded transcripts were compared. Findings The I and Sa codes from the IPASS code set were not observed. Each INURSE code was compared to the corresponding IPASS codes to observe differences between them. Overall the P code was described by 13 INURSE sub codes. The Noise category of IPASS was also described by 5 INURSE codes with few continued instances of Noise. The LIWC software had no misses and 9 false positives. Discussion Overall these findings point towards major differences between nurses and physician’s handover needs. Additionally it points to mixed usefulness of LIWC software for automated analysis. Next steps could include looking into more advanced software for automated analysis, or altering INURSE to train nurses by taking the best of IPASS as well.No embargoAcademic Major: Neuroscienc

Detecting Differences in Communication During Two Types of Patient Handovers: A Linguistic Construct Categorization Approach

Health Professions - Clinical: 4th Place, Honorable Mention (The Ohio State University Denman Undergraduate Research Forum)Patient handovers are a critical point in the patient care process. Software to identify differences in communication content and strategies across different types of patient handovers could be helpful in customizing physician training programs. To determine whether there were differences, Linguistic Inquiry and Word Count (LIWC) software was used. The primary measure was the LIWC output score, which is the frequency of mention of words in a construct category divided by the total number of words in the handover transcript. Two types of constructs were investigated: 1) content, which included name/age, care plan, prognosis, and family, and 2) strategy, which included questioning and collaborative cross-checks. We hypothesized that the Emergency Department (ED) to hospital transfer compared to Intensive Care Unit (ICU) sign-outs would have more discussion of family and less of the patient’s prognosis, as well as more collaborative cross-checks. A two-tailed t-test was used to detect differences. One hypothesis was confirmed, that there was less discussion of prognosis in the ED as compared to the ICU handover. Unexpected findings were less discussion of the care plan and more questioning in the ED as compared to the ICU handover. Findings confirm that both communication content and strategies are different for the two types of patient handovers and that an automated analysis approach can detect differences across a set of handover transcripts.Academic Major: Neuroscienc

Vertebral Tortuosity Is Associated With Increased Rate of Cardiovascular Events in Vascular Ehlers-Danlos Syndrome

Background Arterial tortuosity is associated with adverse events in Marfan and Loeys-Dietz syndromes but remains understudied in Vascular Ehlers-Danlos syndrome. Methods and Results Subjects with a pathogeni

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Cardiopulmonary exercise testing, computed tomography-derived body composition, systemic inflammation and survival after elective abdominal aortic aneurysm repair:A retrospective cohort study

BACKGROUNDCardio-pulmonary exercise testing (CPEX) is selectively used before intervention for abdominal aortic aneurysm (AAA). Sarcopenia, a chronic condition defined by reduced skeletal muscle function and volume, can be assessed radiologically by computed tomography (CT)-derived body composition analysis (CT-BC), and is associated with systemic inflammation.OBJECTIVEThe aim was to describe the association between CT-BC, CPEX, inflammation and survival in patients undergoing elective intervention for AAA.SETTINGPatients were recruited retrospectively from a single, secondary-care centre-operative database. Cases undergoing elective endovascular aneurysm repair (EVAR) and open surgical repair (OSR) between 31 March 2015 and 25 June 2020 were included.PATIENTSThere were 176 patients (130 EVAR, 46 OSR) available for analysis in the final study; median (interquartile range [IQR]) follow-up was 60.5 [27] months, and all completed a minimum of 2 years follow-up.MAIN OUTCOME MEASURESPreoperative CPEX tests were recorded. CT sarcopenia score [CT-SS, range 0 to 2, calculated based on normal/low SMI (0/1) and normal/low SMD (0/1)] assessed radiological sarcopenia. Preoperative modified Glasgow Prognostic score (mGPS) was used to assess systemic inflammation.RESULTSMean [95% confidence interval (CI) survival in the CT-SS 0 vs. CT-SS 1 vs. CT-SS 2 subgroups was 80.1 (73.6 to 86.6) months vs. 70.3 (63.5 to 77.1) months vs. 63.8 (53.4 to 74.2) months] (P = 0.01). CT-SS was not associated with CPEX results (P &gt; 0.05). Elevated CT-SS [hazard ratio (HR) 1.83, 95% CI, 1.16 to 2.89, P &lt; 0.01] was independently associated with increased hazard of long-term mortality; however, CPEX results were not (P &gt; 0.05).CONCLUSIONCPEX test results were not consistently associated with body composition and did not have significant prognostic value in patients undergoing elective treatment for AAA.</p

The Association Between BXO and Obesity in Boys Undergoing Circumcision

This study investigated whether boys with balanitis xerotica obliterans (BXO) have increased rates of obesity compared with boys with no concern for BXO (NCB). Boys ≤18 years old with circumcision pathology–confirmed BXO were compared with an age-matched group who had NCB during circumcision. Boys with BXO were found to have a mean body mass index of 70.64 percentile for age compared with 52.43 percentile in age-matched controls ( P = .0005). The rate of obesity was significantly higher in boys with BXO (42%) compared with 12.4% in boys with NCB (odds ratio = 5.12; 95% CI = 2.6 to 10.06). Given the increasing rates of childhood obesity and the long-term health consequences of both BXO and obesity, special attention should be paid to this population. Further research is needed to determine if BXO in obese children may represent an early indicator of a systemic disease process where intervention may be warranted