Low Positive Predictive Value Research Articles

Perioperative Risk Assessment of Patients Using the MyRISK Digital Score Completed Before the Preanesthetic Consultation: Prospective Observational Study

The ongoing COVID-19 pandemic has highlighted the potential of digital health solutions to adapt the organization of care in a crisis context. Our aim was to describe the relationship between the MyRISK score, derived from self-reported data collected by a chatbot before the preanesthetic consultation, and the occurrence of postoperative complications. This was a single-center prospective observational study that included 401 patients. The 16 items composing the MyRISK score were selected using the Delphi method. An algorithm was used to stratify patients with low (green), intermediate (orange), and high (red) risk. The primary end point concerned postoperative complications occurring in the first 6 months after surgery (composite criterion), collected by telephone and by consulting the electronic medical database. A logistic regression analysis was carried out to identify the explanatory variables associated with the complications. A machine learning model was trained to predict the MyRISK score using a larger data set of 1823 patients classified as green or red to reclassify individuals classified as orange as either modified green or modified red. User satisfaction and usability were assessed. Of the 389 patients analyzed for the primary end point, 16 (4.1%) experienced a postoperative complication. A red score was independently associated with postoperative complications (odds ratio 5.9, 95% CI 1.5-22.3; P=.009). A modified red score was strongly correlated with postoperative complications (odds ratio 21.8, 95% CI 2.8-171.5; P=.003) and predicted postoperative complications with high sensitivity (94%) and high negative predictive value (99%) but with low specificity (49%) and very low positive predictive value (7%; area under the receiver operating characteristic curve=0.71). Patient satisfaction numeric rating scale and system usability scale median scores were 8.0 (IQR 7.0-9.0) out of 10 and 90.0 (IQR 82.5-95.0) out of 100, respectively. The MyRISK digital perioperative risk score established before the preanesthetic consultation was independently associated with the occurrence of postoperative complications. Its negative predictive strength was increased using a machine learning model to reclassify patients identified as being at intermediate risk. This reliable numerical categorization could be used to objectively refer patients with low risk to teleconsultation.

Potential surrogate outcomes in individuals at high risk for incident knee osteoarthritis

To study potential surrogate outcomes for osteoarthritis (OA) incidence by evaluating the association of short-term changes in clinical and imaging biomarkers with long-term clinical knee OA incidence. Middle-aged women with overweight/obesity, but free of knee symptoms were recruited through their general practitioners. At baseline, after 2.5 years, and after 6.5 years, questionnaires, physical examination, radiographs, and Magnetic resonance imaging (MRI) scans were obtained. The percentage of knees with a minimal clinically important difference for knee pain severity, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain/stiffness/function, and joint space narrowing, and of those with progression/regression of medial knee alignment, chronic knee pain, radiographic osteophytes, and cartilage defects, bone marrow lesions, osteophytes, and effusion/synovitis on MRI were determined. For each of these potential surrogate outcomes with ≥10% improvement or progression in the population over 2.5 years, the association with incident clinical knee OA, defined using the combined ACR-criteria, after 6.5 years was determined. Most pre-defined potential surrogate outcomes showed ≥10% change in the population over 2.5 years, but only worsening of TF cartilage defects, worsening of TF osteophytes on MRI, and an increase in pain severity were significantly associated with greater clinical knee OA incidence after 6.5 years. These potential surrogate outcomes had high specificity and negative predictive value (89-91%) and low sensitivity and positive predictive value (20-28%) CONCLUSIONS: Worsening of TF cartilage defects and TF osteophytes on MRI, and increased pain severity could be seen as surrogate outcomes for long-term OA incidence. However, higher positive predictive values seem warranted for the applicability of these factors in future preventive trials.

Integrating Palliative Care into Burn Care: A Retrospective Application of Criteria for Appropriate Referral.

Burn injuries often require complex interdisciplinary care. Despite potential benefits, consultation with specialist palliative care typically occurs in 2% of burn admissions, due largely to lack of availability and misconceptions concerning palliative care. Criteria to guide consultation with specialist palliative care have been developed at this institution. The purpose of this study was to quantify the sensitivity and specificity of these criteria, and then optimize them. Retrospective examination of 388 admissions over 15 months at this adult and pediatric Burn Center were conducted. Chi-square or Fisher's exact test for categorical variables and Wilcoxon Rank Sum test for continuous variables were used to test for between-group differences in demographic and clinical characteristics. Logistic regression model was built to determine modified Baux cut-off score using Youden index (J) value. Criteria were sensitive (0.96) and specific (0.90), though with a low positive predictive value (0.43). Persons with lengths of stay greater than one week, advanced directives, Allow Natural Death orders, and/or deterioration events were significantly more likely to have had palliative care consulted. There were significant between-group differences (with/without palliative care consultation) based on burn surface area, modified Baux score, and mortality risk. Potential criteria revisions are proposed. Prospective adherence to revised criteria could provide useful guidance to providers and benefit to patients and families.

Letter to the editor: Association between birth weight, preterm birth, and nonalcoholic fatty liver disease in a community-based cohort.

To the editor, While we commend Amadou et al.1 for their fine study reporting a U-shaped association between birth weight and risk of NAFLD, we have some concerns. NAFLD was defined using the fatty liver index. This index was, however, developed as a risk stratification tool (not as a diagnostic instrument) and has a rather low positive predictive value for the diagnosis of NAFLD (67%).2 Furthermore, the fatty liver index may perform poorly in young individuals with normal body mass index,3 as in the current French study population (mean age 38 y, normal body mass index).1 Given that the fatty liver index formula is largely driven by body mass index and waist circumference, the question arises whether the found associations rather explain a higher risk of obesity and would especially miss individuals with lean NAFLD. While in women, there was a positive association between high birth weight and risk of NAFLD, the mediation analysis revealed that in men high birth weight did neither have a direct nor a total effect on the later risk of NAFLD—in contrast the indirect effect seemed even protective. Against this background, how do the authors explain the contradictive results on high birth weight and NAFLD risk in men andwomen? The authors found a slight negative association between birth weight and the Forns index, which was used as proxy for liver fibrosis. Here, we see two limitations that make the interpretation of these results challenging: first, the Forns index was originally developed to noninvasively rule-out significant fibrosis and has not been validated to be used as a continuous variable. Second, it was derived in high-risk cohorts of patients with chronic hepatitis C infection,4 while the current study applied it in a general population setting. Hence, we are eager to know if the authors could confirm these results using FIB-4 instead, which is recommended by international guidelines.5

Correlation of Qualitative Alpha1-microglobulin, Values of Interleukin 6, Cervicometry and Cervical Infection in Pregnant Women with Symptoms of Preterm Birth.

One of the problems in modern obstetrics is how to identify and select pregnant women who are most likely to give premature birth. In the last ten years, due to false-positive test results, i.e., tests with low positive predictive values, there is an increase in unnecessary hospitalization days as well as unnecessary therapy. The probability of preterm birth is 25% in a population of pregnant women with symptoms of preterm birth. The aim was to analyze diagnostic accuracy of tests for the purpose of predicting premature births in< 37th and <34th week of pregnancy.Incidence of preterm births in < 37th week of pregnancy was 28%, while the incidence of preterm births up until 34th week of pregnancy, was < 8%. We included two groups of pregnant women in a prospective study; one group with the symptoms of threatening preterm birth between 22nd and 37th week of pregnancyand the other one of the same gestation period with no symptoms. Each pregnant woman underwent test for placental alphamicroglobulin-1, cervical length screening, cervical sampling for microbiological analysis, blood sampling for IL6 and CRP analysis. There were 16% of preterm births, up until 7 days from hospitalization, and they were all PAMG-1 positive; There is 75% of preterm births if PAMG-1 is positive with cervical length under 25mm. Combining tests, we reached the best predictive accuracy with positive PAMG-1 test, cervical length under 15mm along with the increase of CRP values above 15.96%. Total number of hospitalization days was 29% with preterm births up to 71% with full term births regardless the symptomatology, which justifies further studies towards releasing the pressure from the health care system and from doctors as well in the process of reaching a decision on treatment of pregnant women with the signs of preterm birth.

Interpatient Heartbeat Classification Using Modified Residual Attention Network With Two-Phase Training and Assistant Decision

State-of-the-art studies on automatic heartbeat classification have made efforts to improve supraventricular ectopic beat (SVEB) detection, but resulted in a low positive predictive value (PPV) of SVEB and poor performance of other categories under the interpatient paradigm. This article proposes a novel algorithm for heartbeat classification by the means of deep learning combined with feature extraction, which enhances the performance and can be applied to an automatic electrocardiogram (ECG) analysis. It is an improved residual attention network (IraNet) that combines attention module, residual inception block, and bidirectional long short-term memory (BiLSTM) layer to process single heartbeat segments directly. A two-phase training method is presented to change the weights in a planned way to deal with the imbalance of distinguishable features. An assistant decision for the deep learning-based model enhances the PPV of SVEB effectively. Under the interpatient paradigm on the Massachusetts Institute of Technology and Beth Israel Hosipital (MIT-BIH) arrhythmia database, the overall accuracy (Acc) of four classes achieves 0.9548. For SVEB class, the PPV is significantly improved to 0.7557 with the sensitivity (Sen) and an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F1$ </tex-math></inline-formula> score of 0.7392 and 0.7474, respectively. For ventricular ectopic beat (VEB) class, the Sen, PPV, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F1$ </tex-math></inline-formula> score achieve 0.9575, 0.8500, and 0.9005, respectively, and the numbers are 0.9663, 0.9873, and 0.9767 for normal beat class. For fusion beat class, the numbers are 0.7964, 0.3597, and 0.4954, respectively. The proposed algorithm gets competitive results with the state-of-the-art studies, and there is a notable improvement in the detection of SVEB

Value of Breast MRI and Nomogram After Negative Axillary Ultrasound for Predicting Axillary Lymph Node Metastasis in Patients With Clinically T1-2 N0 Breast Cancer.

There are increasing concerns about that sentinel lymph node biopsy (SLNB) could be omitted in patients with clinically T1-2 N0 breast cancers who has negative axillary ultrasound (AUS). This study aims to assess the false negative result (FNR) of AUS, the rate of high nodal burden (HNB) in clinically T1-2 N0 breast cancer patients, and the diagnostic performance of breast magnetic resonance imaging (MRI) and nomogram. We identified 948 consecutive patients with clinically T1-2 N0 cancers who had negative AUS, subsequent MRI, and breast conserving therapy between 2013 and 2020 from two tertiary medical centers. Patients from two centers were assigned to development and validation sets, respectively. Among 948 patients, 402 (mean age ± standard deviation, 57.61 ± 11.58) were within development cohort and 546 (54.43 ± 10.02) within validation cohort. Using logistic regression analyses, clinical-imaging factors associated with lymph node (LN) metastasis were analyzed in the development set from which nomogram was created. The performance of MRI and nomogram was assessed. HNB was defined as ≥ 3 positive LNs. The FNR of AUS was 20.1% (81 of 402) and 19.2% (105 of 546) and the rates of HNB were 1.2% (5/402) and 2.2% (12/546), respectively. Clinical and imaging features associated with LN metastasis were progesterone receptor positivity, outer tumor location on mammography, breast imaging reporting and data system category 5 assessment of cancer on ultrasound, and positive axilla on MRI. In validation cohorts, the positive predictive value (PPV) and negative predictive value (NPV) of MRI and clinical-imaging nomogram was 58.5% and 86.5%, and 56.0% and 82.0%, respectively. The FNR of AUS was approximately 20% but the rate of HNB was low. The diagnostic performance of MRI was not satisfactory with low PPV but MRI had merit in reaffirming negative AUS with high NPV. Patients who had low probability scores from our clinical-imaging nomogram might be possible candidates for the omission of SLNB.

The accuracy of magnetic resonance cholangiopancreatography in the diagnosis of biliary atresia in preterm infants with cholestasis.

Magnetic resonance cholangiopancreatography (MRCP) is a useful and non-invasive method to diagnose biliary atresia (BA) in term infants, however few studies have investigated its use in preterm infants. This study aimed to evaluate the accuracy of MRCP in the diagnosis of BA in preterm infants with cholestasis. Infants aged less than 6 months who received MRCP for cholestasis at a tertiary medical center were enrolled from 2011 to 2020. Demographic and laboratory data were retrospectively obtained. One pediatric radiologist reviewed the MRCP images. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of MRCP to diagnose BA based on surgical proof or at least 6 months of follow-up were assessed. A total of 80 infants (36 preterm and 44 term) were analyzed. The mean post-chronological age was 1.8 months, and the female-to-male ratio was 0.78. Six (16.7%) preterm and 16 (36.4%) term infants were confirmed to have BA. BA was obscured by a choledochal cyst preoperatively in two term infants. In the preterm infants, the sensitivity, specificity, PPV, NPV, and accuracy of MRCP to diagnose BA were 100%, 77%, 46%, 100%, and 81%, respectively, compared to 81%, 86%, 76%, 89%, and 84% in the term infants. Using MRCP to differentiate BA from other cholestasis in the preterm infants had superior sensitivity (100% vs. 81%) and NPV (100% vs. 89%), and lower specificity (77% vs. 86%) and PPV (46% vs. 76%) than in the term infants. Negative MRCP findings can be used to exclude BA in preterm infants with cholestasis based on a favorable NPV.

2D Measurements of the Angle of the Vestibular Aqueduct Using CT Imaging.

Recently, Bächinger et al. developed a software that measures the angle between the vestibular aqueduct proximal to the vestibule and the distal vestibular aqueduct on computed tomography (CT) scans and found differences in the vestibular aqueduct angle between the hypoplastic and degenerative categories of Meniere's disease (MD). Hypoplastic radiological findings were associated with the development of bilateral MD and hypoplastic changes were not found outside of fetal temporal bones and individuals with MD. The purpose of this study is to examine how the software developed by Bächinger et al. performs when applied to a large dataset of adult patients with varied otologic diagnoses. Adult patients who underwent high resolution flat panel CT scans without intravenous contrast (n = 301) were retrospectively reviewed. Measurements of the angle of the vestibular aqueduct were made using the previously developed software tool. The tool could be applied to measure the vestibular aqueduct angle in most CT scans of the temporal bones (n = 572 ears, 95%). While the majority of ears fell within the normal range of &lt;120 degrees (n = 462, 80%), fourteen ears (2.3%) in 13 patients were found to have vestibular aqueduct angles that meet criteria for hypoplastic MD (&gt;140 degrees). Only one of the 13 patients had a diagnosis of MD and not in the ear in the hypoplastic category. An inconsistent pattern of other otologic diagnoses were found among the 13 individuals meeting criteria for hypoplastic MD. Although prior reports indicate the software has prognostic value in individuals with MD, these results suggest that the software may have lower positive predictive value when applied to a large population of individuals with varied otologic diagnoses.

Creatinine and cystatin C-based estimated glomerular filtration rate estimates of kidney function in Black people with HIV on antiretroviral therapy.

To reduce health inequalities, the creatinine-based chronic kidney disease epidemiology collaboration 2021 formula for estimated glomerular filtration rate (eGFR) is replacing the 2009 formula, which required adjustment specifically for Black individuals. We compared the 2021 and 2009 creatinine-based formulae with cystatin C-based eGFR in Black people on antiretroviral therapy (ART) with HIV RNA <200 c/ml. Cross-sectional analysis of paired serum creatinine and cystatin C measurements. Bias, imprecision, accuracy, and performance for identifying individuals with eGFR cystatin C <60 (units: ml/min per 1.73 m 2 ) were determined. The effects of ART with no, mild-moderate, or marked effect on tubular creatinine secretion on the performance of the 2021 formula was assessed. We included 362 individuals (mean age 51 years, 56% female, mean eGFR-cystatin C 88.3). Overall, the 2021 (vs. the 2009 race-adjusted) formula was less biased and had improved imprecision and accuracy compared with eGFR-cystatin C but underestimated eGFR-cystatin C in those with eGFR ≥90 and overestimated eGFR-cystatin C in those with eGFR <60. The 2021 (vs. the 2009) formula had high specificity (95% vs. 97%) and negative predictive value (97% vs. 96%), but low sensitivity (56% vs. 52%) and positive predictive value (44% vs. 54%) for identifying individuals with eGFR-cystatin C <60 ( P > 0.25). Performance at the eGFR <60 cut-off was minimally affected by ART exposure group. The CKD-EPI 2021 creatinine-based formula was better aligned with eGFR-cystatin C than the 2009 formula. eGFR-cystatin C may provide clinically useful information in Black people with eGFR <60 irrespective of ART regimen.

Severe Maternal Morbidity in Twins.

While twin gestations are at increased risk of severe maternal morbidity (SMM), there is limited information about timing and causes of SMM in twins. Furthermore, existing data rely on screening definitions of SMM because a gold standard approach requires chart review. We sought to determine the timing and cause of SMM in twins using a gold standard definition outlined by the American College of Obstetricians and Gynecologists (ACOG). We used a perinatal database to identify all twin deliveries from 1998 to 2013 at a single academic medical center (n = 2,367). Deliveries were classified as screen positive for SMM if they met any of the following criteria: (1) one of the Centers for Disease Control and Prevention (CDC) International Classification of Diseases Ninth Revision diagnosis and procedure codes for SMM; (2) a prolonged postpartum length of stay (>3 standard deviations beyond mean length of stay by mode of delivery); or (3) maternal intensive care unit admission. We identified true cases of SMM through medical record review of all screen-positive deliveries using the definition of SMM outlined in the ACOG Obstetric Care Consensus. We also determined cause and timing of SMM. A total of 165 (7%) of twin deliveries screened positive for SMM. After chart review of all screen-positive cases, 2.4% (n = 56) were classified as a true case of SMM using the ACOG definition for a positive predictive value of 34%. The majority of SMM occurred postpartum (65%). Hemorrhage was the most common cause of SMM, followed by hypertensive and pulmonary etiologies. Commonly used approaches to screen for SMM perform poorly in twins. This has important implications for quality initiatives and epidemiologic studies that rely on screening definitions of maternal morbidity. Our study demonstrates that the immediate postpartum period is a critical time for maternal health among women with twin pregnancies. · Screening approaches for SMM have low positive predictive value in twins.. · Hemorrhage, hypertensive, and pulmonary complications were the most common morbidities.. · SMM was most common postpartum..

1033: AN EVALUATION OF MEWS, NEWS, AND A WIDELY AVAILABLE PROPRIETARY DETERIORATION INDEX

Introduction: Hospitalized patients who experience clinical deterioration often display signs of clinical instability in the preceding hours. Many healthcare institutions have adopted processes to proactively identify and intervene on patients likely to experience a deterioration event. The extent to which these processes can intervene in patient care depends on the ability of the health system to accurately detect patients at risk of deterioration. We conducted a retrospective evaluation of three widely adopted early warning scores as a critical first step to ensuring that we can meaningfully intervene in care for patients likely to experience a deterioration event. Methods: We extracted MEWS variables, NEWS variables, and Epic Deterioration Index (EDI) scores for adult (>18 years) inpatient encounters between July 1, 2020 and January 1, 2022 from Vanderbilt University Medical Center’s (VUMC) Epic electronic health record. For each encounter, we calculated MEWS and NEWS scores each time a new variable was recorded. EDI scores are automatically calculated at 15-minute intervals. We defined a clinical deterioration event as an in-hospital cardiac arrest (IHCA), unanticipated transfer to intensive care, or Rapid Response activation. We retrospectively evaluated the performance of each score in predicting a clinical deterioration event at predefined time intervals. Results: Among 68,127 hospitalizations in our study, there were 3,500 (5.1%) that included a deterioration event. The EDI score correctly identified 904 encounters within 24 hours of an event with an area under the receiver operating curve (AUROC) of 0.67, sensitivity of 0.28, specificity of 0.86, and positive predictive value (PPV) of 0.09. Compared to the EDI score, MEWS and NEWS yielded higher sensitivity (0.35 and 0.54) but lower AUROC (0.58 and 0.63), lower specificity (0.78 and 0.65), and lower PPV (0.08 and 0.08). Conclusions: While MEWS and NEWS have been widely evaluated clinical deterioration, the EDI score is a novel proprietary score with less available performance evaluation data. Our analysis compares the EDI against other validated scores to evaluate its use as an early warning score for common clinical deterioration events, and our data supports the use of the EDI score as a mechanism for identify patients at risk for deterioration.

376. Testing for Cytomegalovirus Viremia in People with HIV/AIDS- An Opportunity for Diagnostic Stewardship

Abstract Background Guidelines recommend against testing for cytomegalovirus (CMV) viremia as a screening tool for CMV end-organ disease (EOD) in people with HIV/AIDS (PWHA) due to low positive predictive value. Additionally, a negative result does not exclude EOD. In this study, we aim to assess the clinical utility of plasma CMV quantitative PCR (qPCR) for the diagnosis of CMV EOD and to determine if positive results lead to further testing for EOD or earlier initiation of anti-CMV therapy. Methods We retrospectively identified PWHA who had a plasma CMV qPCR result or who were diagnosed with CMV EOD between 2014-2021. qPCR results that were undetectable or less than the minimum quantifiable value (300 IU/mL) were considered negative and results &amp;gt;300 IU/mL were considered positive. EOD was confirmed via tissue biopsy, ophthalmic exam, or cerebrospinal fluid analysis. We compared CMV qPCR results for participants with proven EOD and those without proven EOD. For participants diagnosed with CMV EOD, we evaluated if a positive qPCR prompted further workup for EOD diagnosis or triggered anti-CMV therapy. Results We identified 138 PWHA with a CMV qPCR result and 17 PWHA with CMV EOD. Participant characteristics are shown in Table 1. Among participants with a qPCR result, 27 (19.6%) were positive; 13 (9.42%) of those with a qPCR results had EOD. 4 participants with EOD did not have qPCR. Participants with a positive qPCR were 4.55 (95% CI 2.63-7.90) times more likely to have EOD than those with a negative result. Table 2 shows qPCR results among participants with and without EOD. Table 3 shows the performance of qPCR for the diagnosis of EOD. 9 (69.2%) of 13 participants with EOD had a positive qPCR. 7 of them were diagnosed with EOD and started on treatment before the qPCR resulted. In 1 case, the qPCR resulted as positive on the same day ophthalmology diagnosed CMV retinitis. In only 1 case did a positive qPCR result and initiation of therapy precede the diagnosis of EOD. Conclusion Contrary to guidelines, clinicians often order plasma CMV qPCR on PWHA. Although PWHA who have CMV EOD are more likely to a have a positive qPCR than those without EOD, our data confirm CMV qPCR should not be used as a screening tool for EOD. Instead, clinical assessment should guide diagnostic investigation. Disclosures All Authors: No reported disclosures.

Assessment of the Accuracy of Firearm Injury Intent Coding at 3 US Hospitals

The absence of reliable hospital discharge data regarding the intent of firearm injuries (ie, whether caused by assault, accident, self-harm, legal intervention, or an act of unknown intent) has been characterized as a glaring gap in the US firearms data infrastructure. To use incident-level information to assess the accuracy of intent coding in hospital data used for firearm injury surveillance. This cross-sectional retrospective medical review study was conducted using case-level data from 3 level I US trauma centers (for 2008-2019) for patients presenting to the emergency department with an incident firearm injury of any severity. Classification of firearm injury intent. Researchers reviewed electronic health records for all firearm injuries and compared intent adjudicated by team members (the gold standard) with International Classification of Diseases, Ninth and Tenth Revision, Clinical Modification (ICD-9-CM and ICD-10-CM) codes for firearm injury intent assigned by medical records coders (in discharge data) and by trauma registrars. Accuracy was assessed using intent-specific sensitivity and positive predictive value (PPV). Of the 1227 cases of firearm injury incidents seen during the ICD-10-CM study period (October 1, 2015, to December 31, 2019), the majority of patients (1090 [88.8%]) were male and 547 (44.6%) were White. The research team adjudicated 837 (68.2%) to be assaults. Of these assault incidents, 234 (28.0%) were ICD coded as unintentional injuries in hospital discharge data. These miscoded patient cases largely accounted for why discharge data had low sensitivity for assaults (66.3%) and low PPV for unintentional injuries (34.3%). Misclassification was substantial even for patient cases described explicitly as assaults in clinical notes (sensitivity of 74.3%), as well as in the ICD-9-CM study period (sensitivity of 77.0% for assaults and PPV of 38.0% for unintentional firearm injuries). By contrast, intent coded by trauma registrars differed minimally from researcher-adjudicated intent (eg, sensitivity for assault of 96.0% and PPV for unintentional firearm injury of 93.0%). The findings of this cross-sectional study underscore questions raised by prior work using aggregate count data regarding the accuracy of ICD-coded discharge data as a source of firearm injury intent. Based on our observations, researchers and policy makers should be aware that databases drawn from hospital discharge data (most notably, the Nationwide Emergency Department Sample) cannot be used to reliably count or characterize intent-specific firearm injuries.

Prevalence of post-traumatic stress disorder and common mental disorders in health-care workers in England during the COVID-19 pandemic: a two-phase cross-sectional study

Previous studies on the impact of the COVID-19 pandemic on the mental health of health-care workers have relied on self-reported screening measures to estimate the point prevalence of common mental disorders. Screening measures, which are designed to be sensitive, have low positive predictive value and often overestimate prevalence. We aimed to estimate prevalence of common mental disorders and post-traumatic stress disorder (PTSD) among health-care workers in England using diagnostic interviews. We did a two-phase, cross-sectional study comprising diagnostic interviews within a larger multisite longitudinal cohort of health-care workers (National Health Service [NHS] CHECK; n=23 462) during the COVID-19 pandemic. In the first phase, health-care workers across 18 NHS England Trusts were recruited. Baseline assessments were done using online surveys between April 24, 2020, and Jan 15, 2021. In the second phase, we selected a proportion of participants who had responded to the surveys and conducted diagnostic interviews to establish the prevalence of mental disorders. The recruitment period for the diagnostic interviews was between March 1, 2021 and Aug 27, 2021. Participants were screened with the 12-item General Health Questionnaire (GHQ-12) and assessed with the Clinical Interview Schedule-Revised (CIS-R) for common mental disorders or were screened with the 6-item Post-Traumatic Stress Disorder Checklist (PCL-6) and assessed with the Clinician Administered PTSD Scale for DSM-5 (CAPS-5) for PTSD. The screening sample contained 23 462 participants: 2079 participants were excluded due to missing values on the GHQ-12 and 11 147 participants due to missing values on the PCL-6. 243 individuals participated in diagnostic interviews for common mental disorders (CIS-R; mean age 42 years [range 21-70]; 185 [76%] women and 58 [24%] men) and 94 individuals participated in diagnostic interviews for PTSD (CAPS-5; mean age 44 years [23-62]; 79 [84%] women and 15 [16%] men). 202 (83%) of 243 individuals in the common mental disorders sample and 83 (88%) of 94 individuals in the PTSD sample were White. GHQ-12 screening caseness for common mental disorders was 52·8% (95% CI 51·7-53·8). Using CIS-R diagnostic interviews, the estimated population prevalence of generalised anxiety disorder was 14·3% (10·4-19·2), population prevalence of depression was 13·7% (10·1-18·3), and combined population prevalence of generalised anxiety disorder and depression was 21·5% (16·9-26·8). PCL-6 screening caseness for PTSD was 25·4% (24·3-26·5). Using CAPS-5 diagnostic interviews, the estimated population prevalence of PTSD was 7·9% (4·0-15·1). The prevalence estimates of common mental disorders and PTSD in health-care workers were considerably lower when assessed using diagnostic interviews compared with screening tools. 21·5% of health-care workers met the threshold for diagnosable mental disorders, and thus might benefit from clinical intervention. UK Medical Research Council; UCL/Wellcome; Rosetrees Trust; NHS England and Improvement; Economic and Social Research Council; National Institute for Health and Care Research (NIHR) Biomedical Research Centre at the Maudsley and King's College London (KCL); NIHR Protection Research Unit in Emergency Preparedness and Response at KCL.

Development of a risk prediction model for bloodstream infection in patients with fever of unknown origin

Bloodstream infection (BSI) is a significant cause of mortality among patients with fever of unknown origin (FUO). Inappropriate empiric antimicrobial therapy increases difficulty in BSI diagnosis and treatment. Knowing the risk of BSI at early stage may help improve clinical outcomes and reduce antibiotic overuse. We constructed a multivariate prediction model based on clinical features and serum inflammatory markers using a cohort of FUO patients over a 5-year period by Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression. Among 712 FUO patients, BSI was confirmed in 55 patients. Five independent predictors available within 24 h after admission for BSI were identified: presence of diabetes mellitus, chills, C-reactive protein level of 50-100 mg/L, procalcitonin > 0.3 ng/mL, neutrophil percentage > 75%. A predictive score incorporating these 5 variables has adequate concordance with an area under the curve of 0.85. The model showed low positive predictive value (22.6%), but excellent negative predictive value (97.4%) for predicting the risk of BSI. The risk of BSI reduced to 2.0% in FUO patients if score < 1.5. A simple tool based on 5 variables is useful for timely ruling out the individuals at low risk of BSI in FUO population.

HPB P34 Complexity alone is not an indication for resection of liver cysts

Abstract Background Most cystic liver lesions are simple biliary cysts (SBC) and have no malignant potential. Surgical deroofing may be indicated if symptomatic. Mucinous cystic neoplasms (MCN) represent less than 5% of liver cysts but can progress to mucinous cystadenocarcinoma and therefore require formal liver resection. While an MCN would demonstrate complex features on imaging, SBC may have similar appearances following episodes of infection or bleeding. CT, MR and US scans therefore have low positive predictive value for MCN, and most complex cystic liver lesions represent SBC. As a result, the decision to resect a complex cyst can be difficult for both patients and clinicians. We aimed to review our practice. Methods Patients treated surgically for cystic liver lesions in a tertiary Hepatobiliary (HPB) centre between 2016 and 2019 were identified. Data on preoperative imaging, patient demographics, histology and follow up were obtained retrospectively. Results 18 patients were treated surgically for liver cysts. Cysts were solitary in 3/18 cases. Eight were classified as complex on preoperative radiology. Five (all were complex and one was solitary) underwent formal liver resection and the remaining 13 were deroofing procedures. Patients who underwent liver resection were significantly more likely to have an asymptomatic liver cyst (4/5 vs 0/13, chi Squared, p&amp;lt;0.01). None of the resected specimens represented MCN, and complex characteristics on imaging were attributed to episodes of bleeding or infection. 14/18 patients were followed up for a median of 9 months (range: 2–36) without major adverse events. Conclusions Surgical risks of liver resection must be balanced against likelihood of future malignancy. Cyst complexity alone is not an indication for resection and selected cases can be fenestrated if there are no other features to strongly suggest MCN, such as being solitary or in the absence of history suggesting cyst haemorrhage or infection

Positive predictive values and outcomes for uninformative cell-free DNA tests: An Italian multicentric Cytogenetic and cytogenomic Audit of diagnOstic testing (ICARO study).

To establish the positive predictive values (PPV) of cfDNA testing based on data from a nationwide survey of independent clinical cytogenetics laboratories. Prenatal diagnostic test results obtained by Italian laboratories between 2013 and March 2020 were compiled for women with positive non-invasive prenatal tests (NIPT), without an NIPT result, and cases where there was sex discordancy between the NIPT and ultrasound. PPV and other summary data were reviewed. Diagnostic test results were collected for 1327 women with a positive NIPT. The highest PPVs were for Trisomy (T) 21 (624/671, 93%) and XYY (26/27, 96.3%), while rare autosomal trisomies (9/47, 19.1%) and recurrent microdeletions (8/55, 14.5%) had the lowest PPVs. PPVs for T21, T18, and T13 were significantly higher when diagnostic confirmation was carried out on chorionic villi (97.5%) compared to amniotic fluid (89.5%) (p<0.001). In 19/139 (13.9%), of no result cases, a cytogenetic abnormality was detected. Follow-up genetic testing provided explanations for 3/6 cases with a fetal sex discordancy between NIPT and ultrasound. NIPT PPVs differ across the conditions screened and the tissues studied in diagnostic testing. This variability, issues associated with fetal sex discordancy, and no results, illustrate the importance of pre- and post-test counselling.

Validity of Algorithms to Identify Patients With Glaucoma Using the Japanese Claims Data.

Diagnostic or antiglaucoma drug records in the Japanese claims data showed a high validity in identifying glaucoma patients. Specific subtypes were identified with high specificity and negative predictive values but low sensitivity and positive predictive values. Despite the widespread use of administrative claims data in epidemiological research on glaucoma, only a few studies have investigated the validity of the methods in defining patients with glaucoma using diagnoses and drug records. We aimed to evaluate the validity of these algorithms in identifying patients with glaucoma using the Japanese claims data. Two ophthalmologists independently reviewed the medical charts and administrative claims data of 500 randomly selected patients who visited the Department of Ophthalmology of an academic hospital in 2019. We constructed 12 algorithms to identify patients with any type and specific subtypes of glaucoma using the claims records of diagnosis, antiglaucoma drugs, and visual field tests. We regarded the diagnosis of glaucoma based on the medical charts as the reference standard and calculated the sensitivity, specificity, and positive and negative predictive values of each algorithm based on the claims data. The algorithms of ≥1 diagnostic record per year and ≥1 antiglaucoma drug record per year exhibited sensitivities of 94.6% and 89.2%, respectively, and specificities of 88.9% and 98.3%, respectively. An increase in the frequency of records resulted in a decreased sensitivity and slightly increased specificity. The addition of visual field tests did not improve the validity. The algorithms for specific subtypes of glaucoma exhibited high specificity and relatively low sensitivity. Diagnostic or antiglaucoma drug records in the Japanese claims data were useful for identifying patients with glaucoma. Researchers should select identification algorithms based on the study design.

Risk stratification of patients who present with chest pain and have normal troponins using a machine learning model.

Risk stratification tools exist for patients presenting with chest pain to the emergency room and have achieved the recommended negative predictive value (NPV) of 99%. However, due to low positive predictive value (PPV), current stratification tools result in unwarranted investigations such as serial laboratory tests and cardiac stress tests (CSTs). To create a machine learning model (MLM) for risk stratification of chest pain with a better PPV. This retrospective cohort study used de-identified hospital data from January 2016 until November 2021. Inclusion criteria were patients aged > 21 years who presented to the ER, had at least two serum troponins measured, were subsequently admitted to the hospital, and had a CST within 4 d of presentation. Exclusion criteria were elevated troponin value (> 0.05 ng/mL) and missing values for body mass index. The primary outcome was abnormal CST. Demographics, coronary artery disease (CAD) history, hypertension, hyperlipidemia, diabetes mellitus, chronic kidney disease, obesity, and smoking were evaluated as potential risk factors for abnormal CST. Patients were also categorized into a high-risk group (CAD history or more than two risk factors) and a low-risk group (all other patients) for comparison. Bivariate analysis was performed using a χ 2 test or Fisher's exact test. Age was compared by t test. Binomial regression (BR), random forest, and XGBoost MLMs were used for prediction. Bootstrapping was used for the internal validation of prediction models. BR was also used for inference. Alpha criterion was set at 0.05 for all statistical tests. R software was used for statistical analysis. The final cohort of the study included 2328 patients, of which 245 (10.52%) patients had abnormal CST. When adjusted for covariates in the BR model, male sex [risk ratio (RR) = 1.52, 95% confidence interval (CI): 1.2-1.94, P < 0.001)], CAD history (RR = 4.46, 95%CI: 3.08-6.72, P < 0.001), and hyperlipidemia (RR = 3.87, 95%CI: 2.12-8.12, P < 0.001) remained statistically significant. Incidence of abnormal CST was 12.2% in the high-risk group and 2.3% in the low-risk group (RR = 5.31, 95%CI: 2.75-10.24, P < 0.001). The XGBoost model had the best PPV of 24.33%, with an NPV of 91.34% for abnormal CST. The XGBoost MLM achieved a PPV of 24.33% for an abnormal CST, which is better than current stratification tools (13.00%-17.50%). This highlights the beneficial potential of MLMs in clinical decision-making.