An Easy-To-Use Prehospital Severity Scoring Tool To Triage COVID-19 Positive Adults In A Resource-Limited Setting.

Objectives: To develop an easy-to-use severity scoring tool for prehospital triage of patients infected by the coronavirus disease-2019 in resource-limited settings. METHODS: The cohort study was conducted at a tertiary care hospital in Karachi, from August to September 2020, and comprised adult patients of either gender who tested positive for coronavirus disease-2019 on real-time polymerase chain reaction. The scoring system and categorisation were based on validated scales for the detection of pneumonia and opinions from pulmonologists. Data was analysed using SPSS 19. RESULTS: Of the 206 participants, 100(48.5%) were in-patients and 106(51.5%) were out-patients. There were 144(69.9%) males and 62(30.1%) females with an overall mean age of 48.4±16.2 years. After categorisation based on severity, significantly higher number of in-patients were found to be in categories III and IV (p<0.05). CONCLUSIONS: The severity scoring tool could effectively help classify coronavirus disease-2019 patients into mild, moderate and severe cases.

Injury severity score as a predictor of mortality in patients with abdominal trauma at a tertiary Nigerian hospital.

Background: Abdominal trauma is a major cause of morbidity and mortality in low-and middle-income countries. Typical patients present late and very sick with early recognition key to improving outcome. There is a paucity of trauma data in this environment and trauma scoring systems which have been validated in the developed world are yet to find widespread use here. Aim: This study aimed at evaluating role of injury severity score (ISS) in predicting mortality. Patients and Methods: This is a retrospective observational study of patients with abdominal trauma who presented at the University of Ilorin Teaching Hospital from 2013 to 2019. Records were identified and data were extracted and analyzed using Statistical package for social sciences 23. Results: A total of 87 patients were included in the study. There were 73 males and 14 females. The mean overall ISS in this study was 16.06 ± 7.9. Concerning morbidity, the area under the receiver operating characteristic curve in predicting morbidity was 0.843 (95% confidence interval 0.737-0.928). ISS had a strong sensitivity of 90% and specificity 55% at a cut-off of 14.50. Also, the area under the receiver operating characteristic curve in predicting mortality was 0.746 (95% confidence interval 0.588-0.908) and at a cut-off of 16.50; ISS had a specificity of 80% and sensitivity of 60%. The mean ISS of patients with mortality was 22.60 ± 10.5 while the survivors had a mean ISS of 14.7 ± 6.5 (P <.001). The mean ISS for patients who had morbidity was 22.8 ± 8.1 while those without morbidity had a mean ISS of 13.1 ± 5.7 (P <.05). Conclusion: ISS was a good predictor of morbidity and mortality in abdominal trauma in patients in this study. A prospective study with standardized abdominal imaging would be needed to further validate this scoring tool.

Blunt Trauma Massive Transfusion (B-MaT) Score: A Novel Scoring Tool.

BACKGROUND: Multiple tools predicting massive transfusion (MT) in trauma have been developed but utilize variables that are not immediately available. Additionally, they only differentiate blunt from penetrating trauma and do not account for the large range of blunt mechanisms and their difference in force. We aimed to develop a Blunt trauma Massive Transfusion (B-MaT) score that accounts for high-risk blunt mechanisms and predicts MT needs in blunt trauma patients (BTPs) prior to arrival. MATERIALS AND METHODS: The adult 2017 Trauma Quality Improvement Program database was used to identify BTPs who were divided into 2 sets at random (derivation/validation). First, multiple logistic regression models were created to determine risk factors of MT (≥6 units of PRBCs within 4-hours or ≥10 units within 24-hours). Next, the weighted average and relative impact of each independent predictor was used to derive a B-MaT score. Finally, the area under the receiver-operating curve (AROC) was calculated. RESULTS: Of 172,423 patients in the derivation-set, 1,160 (0.7%) required MT. Heart rate ≥ 120bpm, systolic blood pressure ≤ 90mmHg, and high-risk blunt mechanisms were identified as independent predictors for MT. B-MaT scores were derived ranging from 0 -9, with scores of 6, 7, and 9 yielding a MT rate of 11.7%, 19.4%, and 32.4%, respectively. The AROC was 0.86. The validation-set had an AROC of 0.85. CONCLUSIONS: B-MaT is a novel scoring tool that predicts need for MT in BTPs and can be calculated prior to arrival. B-MaT warrants prospective validation to confirm its accuracy and assess its ability to improve patient outcomes and blood product allocation.

Assessing a New Prescreening Score for the Simplified Evaluation of the Clinical Quality and Relevance of eHealth Apps: Instrument Validation Study.

BACKGROUND: In 2020, more than 250 eHealth solutions were added to app stores each day, or 90,000 in the year; however, the vast majority of these solutions have not undergone clinical validation, their quality is unknown, and the user does not know if they are effective and safe. We sought to develop a simple prescreening scoring method that would assess the quality and clinical relevance of each app. We designed this tool with 3 health care stakeholder groups in mind: eHealth solution designers seeking to evaluate a potential competitor or their own tool, investors considering a fundraising candidate, and a hospital clinician or IT department wishing to evaluate a current or potential eHealth solution. OBJECTIVE: We built and tested a novel prescreening scoring tool (the Medical Digital Solution scoring tool). The tool, which consists of 26 questions that enable the quick assessment and comparison of the clinical relevance and quality of eHealth apps, was tested on 68 eHealth solutions. METHODS: The Medical Digital Solution scoring tool is based on the 2021 evaluation criteria of the French National Health Authority, the 2022 European Society of Medical Oncology recommendations, and other provided scores. We built the scoring tool with patient association and eHealth experts and submitted it to eHealth app creators, who evaluated their apps via the web-based form in January 2022. After completing the evaluation criteria, their apps obtained an overall score and 4 categories of subscores. These criteria evaluated the type of solution and domain, the solution's targeted population size, the level of clinical assessment, and information about the provider. RESULTS: In total, 68 eHealth solutions were evaluated with the scoring tool. Oncology apps (22%, 20/90) and general health solutions (23%, 21/90) were the most represented. Of the 68 apps, 32 (47%) were involved in remote monitoring by health professionals. Regarding clinical outcomes, 5% (9/169) of the apps assessed overall survival. Randomized studies had been conducted for 21% (23/110) of the apps to assess their benefit. Of the 68 providers, 38 (56%) declared the objective of obtaining reimbursement, and 7 (18%) out of the 38 solutions seeking reimbursement were assessed as having a high probability of reimbursement. The median global score was 11.2 (range 4.7-17.4) out of 20 and the distribution of the scores followed a normal distribution pattern (Shapiro-Wilk test: P=.33). CONCLUSIONS: This multidomain prescreening scoring tool is simple, fast, and can be deployed on a large scale to initiate an assessment of the clinical relevance and quality of a clinical eHealth app. This simple tool can help a decision-maker determine which aspects of the app require further analysis and improvement.

Evaluation of a tool to score donor vein suitability for blood donation.

BACKGROUND AND OBJECTIVES: Phlebotomy is a central task for whole blood donation, yet there are no published standards regarding systematic donor vein assessment or the impact of vein quality on successful blood donation. Blood donation failures and related adverse events are highly predictive of donors not returning for future blood donation. A specific blood donation vein scoring tool was assessed to measure donor vein suitability for whole blood collection and investigate the correlation of the donor's veins with donation outcomes. MATERIALS AND METHODS: The vein assessment tool consisted of three questions using a 5-point Likert-type scale to measure responses. Two phlebotomists performed blinded assessments of each donor's veins on each arm using the tool. The individual measures were then aggregated to provide a total vein score out of 12. Inter-rater reliability of the vein score tool was assessed by calculating the intraclass correlation coefficient for absolute agreement. RESULTS: Fifty-seven phlebotomists across four fixed blood donation centres performed paired vein assessments on 553 blood donors. The intraclass correlation coefficient indicated moderate inter-rater reliability was achieved. The median scores for viable donations were 10, for non-viable donations were 6·5 and for failed phlebotomies were 4. Donation histories of donors with lower vein scores indicated lower success during blood donation. CONCLUSION: The vein score tool appears to be predictive of a successful donation outcome, however, since there was not a suitably high correlation between the scores of the two assessors, further refinement of the tool will be required prior to wider use.

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy.

BACKGROUND: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. METHODS: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. RESULTS: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45-85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p < 0.001), with the proportions of operations lasting > 90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. CONCLUSION: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care.

Postanesthesia Scoring Methods: An Integrative Review of the Literature.

PURPOSE: Internationally there is no consensus on the indicators essential for determining safe recovery from anesthesia and patient readiness for discharge from the postanesthesia care unit (PACU). DESIGN: Integrative review. METHODS: Using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) as a search strategy, the literature related to PACU discharge scores were evaluated and organized into themes. FINDINGS: The traditional components of airway support, oxygenation, sedation, and circulation are common within many first stage PACU discharge scores. However, there is strong support from the literature for components such as heart rate, temperature, pain, postoperative nausea and vomiting (PONV), urine output, and surgical site assessment to also be included. The review revealed that there is no standardized time frequency in applying a first stage PACU discharge score to patients within the PACU environment. CONCLUSIONS: There is a need for the development and trial of an evidence based first stage PACU discharge score.

Value of a risk scoring tool to predict respiratory syncytial virus disease severity and need for hospitalization in term infants.

Several environmental and demographic risk factors have been validated and are used to determine the risk of acquiring severe respiratory syncytial virus (RSV) infection and subsequent hospitalization in late preterm infants born at 33-35 weeks gestational age. The applicability of the same composite model of risk factors in the term population has not been fully explored. The primary objective of this pilot study was to establish whether a risk scoring tool (RST), could predict the severity of RSV infection in term, RSV-positive infants who were hospitalized. A retrospective observational study was conducted in a pediatric unit, over 2 RSV seasons (2011-2013). A convenient sample of 72 children was selected out of a total of 111 RSV-positive cases after exclusions. The RST was applied and a score of respiratory disease severity was determined for each patient. Demographic characteristics were analyzed by standard descriptive methods, χ(2) analysis was utilized for categorical data and ANOVA for comparison between the clinical severity groups and the RST score. A P-value <0.05 was considered significant. Sixty per cent (n = 43) of all infants scored in the low-risk category compared to 26% (n = 19) in the moderate and 14% (n = 10) in the high-risk groups. RST scores were also inconsistent with disease severity. Mean (SD) RST scores for those with mild, moderate, and severe illness were 47.8 [16.4], 41.1 [20.39] and, 41.7 [19.8], respectively (P = 0.17). In conclusion, the RST did not predict accurately the clinical severity of RSV bronchiolitis in term infants nor did it correlate with risk for RSV-related hospitalization.

Predictors of new fragility fractures after diagnosis of indolent systemic mastocytosis.

BACKGROUND: Fragility fractures (FFxs) and osteoporosis occur frequently in patients with indolent systemic mastocytosis (ISM), even before 50 years of age. OBJECTIVE: We sought to develop a prediction model to identify individual patients with ISM at risk of new FFxs. METHODS: Data on lifetime fractures and trauma circumstances were collected from vertebral morphometry, patients' records, and questionnaires. Clinical, lifestyle, and bone characteristics were measured. Patients receiving treatment for osteoporosis before ISM diagnosis or with missing bone data were excluded from FFx risk assessment. RESULTS: In total, 389 lifetime fractures occurred in 127 of the 221 patients with ISM (age, 19-77 years), including 90 patients with 264 FFxs. Median follow-up after diagnosis was 5.4 years (range, 0.4-15.3 years), with 5- and 10-year FFx risks of 23% ± 3% and 31% ± 4%, respectively. Male sex, high levels of bone resorption (serum type I collagen C-telopeptide), low hip bone mineral density, absence of urticaria pigmentosa, and alcohol intake at the time of ISM diagnosis were independent predictors of future FFxs. The MastFx score, a prediction model using these 5 characteristics, showed good accuracy (area under the curve, 0.80) to determine the risk of new FFxs. QFracture, a validated risk scoring tool for persons aged 30 to 99 years, was not useful in patients with ISM. CONCLUSION: The MastFx score distinguishes patients with ISM at high, intermediate, and low risk of new FFxs. The included characteristics sex, serum type I collagen C-telopeptide, hip bone mineral density, urticaria pigmentosa, and alcohol intake are easy to collect in clinical practice. The high occurrence of FFxs in patients with ISM underlines the importance of optimizing bone quality and early start of therapeutic prevention in patients at risk.

In utero exposure to Black Bull chewing tobacco and neonatal nicotine withdrawal: a review of the literature.

Among the indigenous people of the Yukon-Kuskokwim Delta area of Alaska, a homemade moist chewing tobacco known as Black Bull or "iq'mik" is widely used. Intake of various tobacco products is reported to be more than 80 percent in pregnant women throughout this area, with up to 60 percent of the pregnant women admitting to regular use of Black Bull. High levels of nicotine, cotinine, heavy metals, and other chemicals are known to pass to the fetus. Neonatal exposure to maternal tobacco use has been studied for the past three decades and has been shown to cause neonatal passive addiction and subsequent withdrawal symptoms. The intensified exposure and withdrawal experienced by infants passively subjected to Black Bull warrant further study.

Immediate Operative Trauma Assessment Score: A Simple and Reliable Predictor of Mortality in Trauma Patients Undergoing Urgent/Emergent Surgery.

Objective: Many current trauma mortality prediction tools are either too intricate or rely on data not readily available during a trauma patient's initial evaluation. Moreover, none are tailored to those necessitating urgent or emergent surgery. Our objective was to design a practical, user-friendly scoring tool using immediately available variables, and then compare its efficacy to the widely-known Revised Trauma Score (RTS). Methods: The adult 2017-2021 Trauma Quality Improvement Program (TQIP) database was queried to identify patients ≥18 years old undergoing any urgent/emergent operation (direct from Emergency Department to operating room). Patients were divided into derivation and validation groups. A three-step methodology was used. First, multiple logistic regression models were created to determine risk of death using only variables available upon arrival. Second, the weighted average and relative impact of each independent predictor was used to derive an easily calculated Immediate Operative Trauma Assessment Score (IOTAS). We then validated IOTAS using AUROC and compared it to RTS. Results: From 249 208 patients in the derivation-set, 14 635 (5.9%) died. Age ≥65, Glasgow Coma Scale score <9, hypotension (SBP <90 mmHg), and tachycardia (>120/min) on arrival were identified as independent predictors for mortality. Using these, the IOTAS was structured, offering scores between 0-8. The AUROC for this was .88. A clear escalation in mortality was observed across scores: from 4.4% at score 1 to 60.5% at score 8. For the validation set (250 182 patients; mortality rate 5.8%), the AUROC remained consistent at .87, surpassing RTS's AUROC of .83. Conclusion: IOTAS is a novel, accurate, and now validated tool that is intuitive and efficient in predicting mortality for trauma patients requiring urgent or emergent surgeries. It outperforms RTS, and thereby may help guide clinicians when determining the best course of action in patient management as well as counseling patients and their families.

Development and assessment of an abbreviated medication regimen complexity index (the A-MRCI).

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: Adaptation of the Medication Regimen Complexity Index (MRCI) for automation in an electronic medical record has the potential to improve medication optimization and patient outcomes. The purpose of this study was to develop and evaluate an abbreviated medication regimen complexity index (A-MRCI) and compare its associations with patient-level factors to those of the MRCI. METHODS: The MRCI was modified via several rounds of review with an expert panel of clinical pharmacists and outcomes researchers. Medication data from 138 electronic health records were abstracted to calculate MRCI and A-MRCI scores for dosage form, dosing frequency, and additional directions. Comparison between indices was performed using inferential statistics for a 1-month sample of patients admitted to a cardiology or advanced heart failure service in 2017. RESULTS: A-MRCI scores were higher than MRCI scores (mean difference of 3.97, P < 0.0005; 95% CI, 2.21-5.71). A significant association was observed between the A-MRCI score and both length of stay (P = 0.0005) and polypharmacy (P < 0.0005), whereas an association between MRCI score and the patient-level factors examined was not demonstrated. CONCLUSION: On average, A-MRCI scores were higher and more likely to be associated with several patient-level factors. Internal analyses show the potential for integration into an electronic health record for automation. However, further exploration of the A-MRCI in a larger external validation sample is warranted.

Scoring big: Aligning inpatient clinical pharmacy services through implementation of an electronic scoring system.

PURPOSE: Data are limited on utilizing a comprehensive scoring system in the electronic health record to help prioritize, align, and standardize clinical pharmacy services across multiple hospitals and practice models within a health system. The purpose of this article is to describe the development and implementation of an electronic scoring system to help inpatient pharmacists prioritize patient care activities and standardize clinical services across a diverse health system. SUMMARY: Inpatient pharmacists from all specialty areas across the health system partnered with health information technology pharmacists to develop a scoring system directly integrated into the electronic health record that would help triage patient care, identify opportunities for pharmacist intervention, and prioritize clinical pharmacy services. Individual variables were built based on documented patient parameters such as use of high-risk medications, pharmacy consults, laboratory values, disease states, and patient acuity. Total overall scores were assigned to patients based on the sum of the scores for the individual variables, which update automatically in real time. The total scores were designed to help inpatient pharmacists prioritize patients with higher scores, thus reducing the need for manual chart review to identify high-risk patients. CONCLUSION: An electronic scoring system with a tiered point system developed for inpatient pharmacists creates a method to prioritize and align clinical pharmacy services across a health system with diverse pharmacy practice models.

FDrisk: development of a validated risk assessment tool for Fabry disease utilizing electronic health record data.

Purpose: Fabry disease (FD) is a rare, X-linked, lysosomal storage disease characterized by great variability in clinical presentation and progressive multisystemic organ damage. Lack of awareness of FD and frequent misdiagnoses cause long diagnostic delays. To address the urgent need for earlier diagnosis, we created an online, risk-assessment scoring tool, the FDrisk, for predicting an individual's risk for FD and prompting diagnostic testing and clinical evaluation. Methods: Utilizing electronic health records, data were collected retrospectively from randomly selected, deidentified patients with FD treated at the Emory Lysosomal Storage Disease Center. Deidentified, negative controls were randomly selected from the Fabry Disease Diagnostic Testing and Education project database, a program within the American Association of Kidney Patients Center for Patient Education and Research. Diagnosis of FD was documented by evidence of a pathogenic variant in GLA and/or an abnormal level of leukocyte α-Gal A. Thirty characteristic clinical features of FD were initially identified and subsequently curated into 16 clinical covariates used as predictors for the risk of FD. An overall prediction model and two sex-specific prediction models were built. Two-hundred and sixty samples (130 cases, 130 controls) were used to train the risk prediction models. One-hundred and ninety-seven independent samples (30 cases, 167 controls) were used for testing model performance. Prediction accuracy was evaluated using a threshold of 0.5 to determine a predicted case vs. control. Results: The overall risk prediction model demonstrated 80% sensitivity, 83.8% specificity, and positive predictive value of 47.1%. The male model demonstrated 75% sensitivity, 95.8% specificity, and positive predictive value of 75%. The female model demonstrated 83.3% sensitivity, 81.3% specificity, and positive predictive value of 45.5%. Patients with risk scores at or above 50% are categorized as "at risk" for FD and should be sent for diagnostic testing. Conclusion: We have developed a statistical risk prediction model, the FDrisk, a validated, clinician-friendly, online, risk-assessment scoring tool for predicting an individual's risk for FD and prompting diagnostic testing and clinical evaluation. As an easily accessible, user-friendly scoring tool, we believe implementing the FDrisk will significantly decrease the time to diagnosis and allow earlier initiation of FD-specific therapy.

Development and validation of a predictive scoring model for risk stratification of tuberculosis treatment interruption.

BACKGROUND: Tuberculosis (TB) treatment interruption poses risks of antimicrobial resistance, potentially leading to treatment failure and mortality. Addressing the risk of early treatment interruption is crucial in tuberculosis care and management to improve treatment outcomes and curb disease transmission. OBJECTIVES: This study aimed to identify risk factors of TB treatment interruption and construct a predictive scoring model that enables objective risk stratification for better prediction of treatment interruption. METHODS: A multicentre retrospective cohort study was conducted at public health clinics in Sarawak, Malaysia over 11 months from March 2022 to January 2023, involving adult patients aged ≥18 years with drug-susceptible TB diagnosed between 2018 and 2021. Cumulative missed doses or discontinuation of TB medications for ≥2 weeks, either consecutive or non-consecutive, was considered as treatment interruption. The model was developed and internally validated using the split-sample method. Multiple logistic regression analysed 18 pre-defined variables to identify the predictors of TB treatment interruption. The Hosmer-Lemeshow test and area under the receiver operating characteristic curve (AUC) were employed to evaluate model performance. RESULTS: Of 2953 cases, two-thirds (1969) were assigned to the derivation cohort, and one-third (984) formed the validation cohort. Positive predictors included smoking, previously treated cases, and adverse drug reactions, while concurrent diabetes was protective. Based on the validation dataset, the model demonstrated good calibration (P = 0.143) with acceptable discriminative ability (AUC = 0.775). A cutoff score of 2.5 out of 11 achieved a sensitivity of 81 % and a specificity of 64.4 %. Risk stratification into low (0-2), medium (3-5), and high-risk (≥6) categories showed ascending interruption rates of 5.3 %, 18.1 %, and 41.3 %, respectively (P < 0.001). CONCLUSION: The predictive scoring model aids in risk assessment for TB treatment interruption, enabling focused monitoring and personalized intervention plans for higher-risk groups in the early treatment phase.

Comprehensive Spinal Tuberculosis Score: A Clinical Guide for the Management of Thoracolumbar Spinal Tuberculosis.

STUDY DESIGN: A newly proposed scoring tool was designed to assist in the clinical management of adult thoracolumbar spinal tuberculosis (TB). PURPOSE: To formulate a comprehensive yet simple scoring tool to guide decision-making in the management of adult thoracolumbar spinal TB. OVERVIEW OF LITERATURE: Spine surgeons have differing consensus in defining the threshold grade for clinico-radiological parameters when deciding between operative or conservative treatment for adult thoracolumbar spinal TB. Currently, the void in decision-making from the lack of well-defined guidelines is compensated by the surgeon's experience in treating these patients. To the best of our knowledge, no scoring system holistically integrates multiple facets of spinal TB to guide clinical decision-making. METHODS: The RAND/University of California, Los Angeles appropriateness method was employed among an expert panel of 10 spine surgeons from four apex tertiary care centers. Vital characteristics that independently influenced treatment decisions in spinal TB were identified, and a scoring tool was formulated. Points were assigned for each component based on their severity. The cutoff scores to guide clinical management were determined from the receiver operating characteristic curve based on the retrospective records of 151 patients treated operatively or non-operatively with improved functional outcomes at the 1-year follow-up. RESULTS: The components of the comprehensive spinal TB score (CSTS) are pain, kyphosis angle, vertebral destruction, and neurological status. A score classification of <5.5, 5.5-6.5, and >6.5 was established to guide the patient toward conservative, conservative/ operative, and operative management, respectively. CONCLUSIONS: The CSTS was designed to reflect the essential indicators of mechanical stability, neurological stability, and disease process stabilization in spinal TB. The scoring tool is devised to be practical and serve as a common language in the spine community to facilitate discussions and decision-making in thoracolumbar spinal TB. The validity, reliability, and reproducibility of this tool must be assessed through multicenter long-term studies.

Unit-Based Nurses' Development of a Couplet Care Acuity Scoring Tool.

OBJECTIVE: To evaluate content validity (CV) and interrater reliability (IRR) of an acuity scoring tool developed for the couplet care/postpartum/nursery patient population and to determine if there was agreement between supervisor or director scoring and staff scoring. DESIGN: A scoring tool to assess the acuity of the couplet care/postpartum/nursery patients was developed. SETTING: Two hospitals: one Level 2 hospital, one Level 3 hospital. Unit-based patient care councils participated in the development, and all couplet care nurses participated in scoring patients for testing. MEASUREMENTS: The final tool was evaluated for CV and IRR using expert review, universal agreement scores, and discriminant content validation. RESULTS: Regarding CV for the Couplet Care Acuity Scoring Tool, the average of the number of experts in agreement divided by the total number of experts across all items was 1.00. Regarding IRR, the intraclass correlation coefficient was 0.85, indicating that the tool is valid and reliable for the study sample. CONCLUSION: The tool was reliable and valid in this study. Future testing is needed with larger samples and different health care facilities.

Intrahospital Handovers before and after the Implementation of ISBAR Communication: A Quality Improvement Study on ICU Nurses' Handovers to General Medical Ward Nurses.

BACKGROUND: Research finds a lack of structure as well as varying and incomplete content in intrahospital handovers. This study aimed to improve intrahospital handovers by implementing structured ISBAR communication (identification, situation, background, assessment and recommendation). METHODS: This quality improvement study was conducted observing 25 handovers given by nurses from the intensive care unit to nurses from general medical wards at baseline and after the implementation of the ISBAR communication tool. The 26-item ISBAR scoring tool was used to audit the handovers. In addition, the structure of the ISBAR communication and time spent on the handovers were observed. RESULTS: There were no significant improvements from baseline to post-intervention regarding adherence to the ISBAR communication scoring tool. The structure of the handovers improved from baseline to post-intervention (p = 0.047). The time spent on handovers declined from baseline to post-intervention, although not significantly. CONCLUSIONS: The items in the ISBAR communication scoring tool can act as a guide for details that need to be reported during intrahospital handovers to strengthen patient safety. Future research calls for studies measuring satisfaction among nurses regarding using different handover tools and studies using multifaceted training interventions.

Neonatal Abstinence Signs during Treatment: Trajectory, Resurgence and Heterogeneity.

Neonatal abstinence syndrome (NAS) presents with a varying severity of withdrawal signs and length of treatment (LOT). We examined the course and relevance of each of the NAS withdrawal signs during treatment in a sample of 182 infants with any prenatal opioid exposure, gestational age ≥ 35 weeks, without other medical conditions, and meeting the criteria for pharmacological treatment. Infants were monitored using the Finnegan Neonatal Abstinence Scoring Tool. Daily mean Finnegan scores were estimated using linear mixed models with random subject effects to account for repeated withdrawal scores from the same subject. Daily item prevalence was estimated using generalized estimating equations with a within-subject exchangeable correlation structure. The median LOT was 12.86 days. The prevalence of withdrawal signs decreased from day one to day three of treatment. However, certain central nervous system (CNS) and gastrointestinal (GI) signs showed sporadic increases in prevalence notable around two weeks of treatment, accounting for increases in Finnegan scores that guided pharmacotherapy. We question whether the resurgence of signs with a prolonged LOT is mainly a consequence of opioid tolerance or withdrawal. Monitoring CNS and GI signs throughout treatment is crucial. Future studies directed to better understand this clinical phenomenon may lead to the refining of NAS pharmacotherapy and perhaps the discovery of treatment alternatives.

Risk factors and risk scoring tool for infection during tissue expansion in tissue expander and implant breast reconstruction.

Tissue expander and implant (TE/I) breast reconstruction has been increasing recently. In TE/I breast reconstruction, infection leads to reconstruction failure and is the most serious complication. The infection rate was reported to be higher during the tissue expander period than the implant period. However, few studies have investigated the risk factors for infection during tissue expansion following TE/I breast reconstruction. The goal of this study was to identify risk factors for infection during tissue expansion in TE/I breast reconstruction and to develop a simple risk scoring tool for infection that can be used for clinical application. In this retrospective cohort study, 981 patients who received TE/I breast reconstruction were surveyed and analyzed at one of the main clinics performing TE/I breast reconstruction in Japan. Numerous potential risk factors were collected from the clinical charts. Multiple logistic regression analyses were used to identify risk factors for infection. To develop a risk scoring tool, we converted the coefficients of the identified predictors estimated in the multiple logistic regression analyses into simplified risk scores. We assessed the tool discrimination by drawing a receiver operating characteristic curve and calculating the area under the curve. Infection was noted in 47 patients (4.79%) during tissue expansion. In multiple logistic regression analyses, diabetes, repeated expander insertions, larger expander size (≥400 cc), postoperative hormone therapy before silicone implant surgery, preoperative chemotherapy, and nipple-sparing mastectomy were identified as risk factors for infection during expansion. The area under the curve of the risk scoring tool for infection was 0.734 (95% CI: 0.662-0.807). We have revealed risk factors and proposed a risk scoring tool for infection during tissue expansion in TE/I breast reconstruction. This study may contribute to the prevention and prediction of infection.