Clinical Validation of a Primary Antibody Deficiency Screening Algorithm for Primary Care.

PURPOSE: The diagnostic delay of primary antibody deficiencies (PADs) is associated with increased morbidity, mortality, and healthcare costs. Therefore, a screening algorithm was previously developed for the early detection of patients at risk of PAD in primary care. We aimed to clinically validate and optimize the PAD screening algorithm by applying it to a primary care database in the Netherlands. METHODS: The algorithm was applied to a data set of 61,172 electronic health records (EHRs). Four hundred high-scoring EHRs were screened for exclusion criteria, and remaining patients were invited for serum immunoglobulin analysis and referred if clinically necessary. RESULTS: Of the 104 patients eligible for inclusion, 16 were referred by their general practitioner for suspected PAD, of whom 10 had a PAD diagnosis. In patients selected by the screening algorithm and included for laboratory analysis, prevalence of PAD was ~ 1:10 versus 1:1700-1:25,000 in the general population. To optimize efficiency of the screening process, we refitted the algorithm with the subset of high-risk patients, which improved the area under the curve-receiver operating characteristics curve value to 0.80 (95% confidence interval 0.63-0.97). We propose a two-step screening process, first applying the original algorithm to distinguish high-risk from low-risk patients, then applying the optimized algorithm to select high-risk patients for serum immunoglobulin analysis. CONCLUSION: Using the screening algorithm, we were able to identify 10 new PAD patients from a primary care population, thus reducing diagnostic delay. Future studies should address further validation in other populations and full cost-effectiveness analyses. REGISTRATION: Clinicaltrials.gov record number NCT05310604, first submitted 25 March 2022.

First Discovery of Iodinated Polyfluoroalkyl Acids by Nontarget Mass-Spectrometric Analysis and Iodine-Specific Screening Algorithm.

Per- and polyfluoroalkyl acids (PFAAs) including polyfluoroalkyl carboxylic acids and polyfluoroalkyl sulfonic acids are a large category of crucial environmental pollutants of global concern. Besides known PFAAs, numerous unknown species may exist in the environment, urgently needing discovery and characterization. This study implemented nontarget analysis for a group of novel PFAA pollutants, viz., iodinated PFAAs (I-PFAAs) in wastewater from a fluorochemical manufacturing park by liquid chromatography-high-resolution mass spectrometry in combination with an iodine-specific data-processing algorithm. The algorithm took into account the diagnostic fragment iodine ion (I-) together with carbon and sulfur isotopologue distributions. In total, 18 I-PFAA formulas involving 21 congeners were identified. Semiquantification was conducted, and the total concentrations of I-PFAAs were 1.9-274.7 µg/L, indicating severe pollution of I-PFAAs in the wastewater. The determined concentrations along with predicted environmental behaviors and toxicities demonstrate that I-PFAAs merit further in-depth investigation. The analytical method including the instrumental analysis and data-processing algorithm can be extended to screening and identification of I-PFAAs in other matrices. Furthermore, the analysis results for the first time provide recognition on the occurrence, distribution features, and pollution status of I-PFAAs in the environment.

A Screening Protocol for Exploring Loop Length Requirements for the Formation of a Three Cytosine-Cytosine+ Base-Paired i-Motif.

DNA sequences containing at least four runs of repetitive cytosines can fold into tetra-helical structures called i-Motifs (iMs). The interest in these DNA secondary structures is increasing due to their therapeutical and technological applications. Still, limited knowledge of their folding requirements is currently available. We developed a novel step-by-step pipeline for the systematic screening of putative iM-forming model sequences. Focusing on structures comprising only three cytosine-cytosine+ base pairs, we investigated what the minimal lengths of the loops required for formation of an intra-molecular iM are. Our data indicate that two and three nucleotides are required to connect the strands through the minor and majorgrooves of the iM, respectively. Additionally, they highlight an asymmetric behavior according to the distribution of the cytosines. Specifically, no sequence containing a single cytosine in the first and third run was able to fold into intra-molecular iMs with the same stability of those formed when the first and the third run comprise two cytosines. This knowledge represents a step forward toward the development of prediction tools for the proper identification of biologically functional iMs, as well as for the rational design of these secondary structures as technological devices.

Predictive validity of the Stopping Elderly Accidents, Deaths & Injuries (STEADI) program fall risk screening algorithms among community-dwelling Thai elderly.

BACKGROUND: Fall risk screening using multiple methods was strongly advised as the initial step for preventing fall. Currently, there is only one such tool which was proposed by the U.S. Centers for Disease Control and Prevention (CDC) for use in its Stopping Elderly Accidents, Death & Injuries (STEADI) program. Its predictive validity outside the US context, however, has never been investigated. The purpose of this study was to determine the predictive validity (area under the receiver operating characteristic curve: AUC), sensitivity, and specificity of the two-step sequential fall-risk screening algorithm of the STEADI program for Thai elderly in the community. METHODS: A 1-year prospective cohort study was conducted during October 2018-December 2019. Study population consisted of 480 individuals aged 65 years or older living in Nakhon Ratchasima Province, Thailand. The fall risk screening algorithm composed of two serial steps. Step 1 is a screening by the clinician's 3 key questions or the Thai Stay Independent brochure (Thai-SIB) 12 questions. Step 2 is a screening by 3 physical fitness testing tools including Time Up and Go test (TUG), 30-s Chair Stand, and 4-stage balance test. Participants were then followed for their fall incidents. Statistical analyses were conducted by using Cox proportional hazard model. The AUC, sensitivity, specificity, and other relevant predictive validity indices were then estimated. RESULTS: The average age of the participants was 73.3 ± 6.51 years (range 65-95 years), and 52.5% of them were female. The screening based on the clinician's 3 key questions in Step 1 had a high AUC (0.845), with the sensitivity and specificity of 93.9% (95% CI 88.8, 92.7) and 75.0% (95% CI 70.0, 79.6), respectively. Appropriate risk categorization however differed slightly from the original STEADI program. CONCLUSIONS: With some modification, the fall risk screening algorithm based on the STEADI program was applicable in Thai context.

Cancer surgery during the COVID-19 pandemic: The experience of a comprehensive cancer center performing preoperative screening by RT-PCR and chest CT scan.

BACKGROUND AND OBJECTIVES: During the worldwide pandemic of coronavirus disease 2019 (COVID-19), oncological procedures considered to be urgent could not be delayed, and a specific procedure was required to continue surgical activity. The objective was to assess the efficacy of our preoperative screening algorithm. METHODS: This observational retrospective study was performed between the 25th of March and the 12th of May 2020 in a comprehensive cancer center in France. Patients undergoing elective oncologic surgery were tested by preoperative nasopharyngeal reverse-transcription polymerase chain reaction (RT-PCR) that could be associated with a chest computerized tomography (CT) scan. RESULTS: Of the 510 screening tests (in 477 patients), only 5% (15/477) were positive for COVID-19 in 24 patients (18 RT-PCR+ and 7 CT scan+/RT-PCR-). Four patients were ultimately false positives based on the CT scan. In total, only 4.2% (20/477) of the patients were COVID-19+. The positivity rate decreased with time after the containment measures were implemented (from 7.4% to 0.8%). In the COVID-19+ group, 20% of the patients had postoperative pulmonary complications, whereas this was the case for 5% of the patients in the COVID-19 group. CONCLUSIONS: Maintaining secure surgical activity is achievable and paramount in oncology care, even during the COVID-19 pandemic, with appropriate screening based on preoperative RT-PCR.

COVID-19 and Acute Heart Failure: Screening the Critically Ill - A Position Statement of the Cardiac Society of Australia and New Zealand (CSANZ).

Up to one-third of COVID-19 patients admitted to intensive care develop an acute cardiomyopathy, which may represent myocarditis or stress cardiomyopathy. Further, while mortality in older patients with COVID-19 appears related to multi-organ failure complicating acute respiratory distress syndrome (ARDS), the cause of death in younger patients may be related to acute heart failure. Cardiac involvement needs to be considered early on in critically ill COVID-19 patients, and even after the acute respiratory phase is passing. This Statement presents a screening algorithm to better identify COVID-19 patients at risk for severe heart failure and circulatory collapse, while balancing the need to protect health care workers and preserve personal protective equipment (PPE). The significance of serum troponin levels and the role of telemetry and targeted transthoracic echocardiography (TTE) in patient investigation and management are addressed, as are fundamental considerations in the management of acute heart failure in COVID-19 patients.

Prospective evaluation of a screening algorithm for carbapenemase-producing Enterobacteriaceae.

BACKGROUND: Carbapenemase-producing Enterobacteriaceae (CPE) have become a major public health issue. The objective of the present study was to prospectively assess the analytical performance of a CPE detection algorithm based on phenotypic tests (the screening test) and MALDI-ToF hydrolysis (the confirmatory test). METHODS: Over a 6-month period and based on a disk diffusion method, 74 carbapenem-resistant strains were included in this study. RESULTS: Of the collected isolates, 54 turned out to be negative after phenotypic tests. Hence, 20 strains (including all of the CPEs) were checked with the confirmation test. Seven strains were positive. After molecular biology assessments in a reference center, three of the seven were found to be false positives. The algorithm had a negative predictive value and a sensitivity of 100%, a specificity of 77%, and a positive predictive value of 20%. CONCLUSION: The algorithm has a 24-hour turnaround time and helps to avoid using expensive molecular biology tests; we consider that it can be used on a routine basis for screening clinical strains.

Enhancing recall in automated record screening: A resampling algorithm.

Literature screening is the process of identifying all relevant records from a pool of candidate paper records in systematic review, meta-analysis, and other research synthesis tasks. This process is time consuming, expensive, and prone to human error. Screening prioritization methods attempt to help reviewers identify most relevant records while only screening a proportion of candidate records with high priority. In previous studies, screening prioritization is often referred to as automatic literature screening or automatic literature identification. Numerous screening prioritization methods have been proposed in recent years. However, there is a lack of screening prioritization methods with reliable performance. Our objective is to develop a screening prioritization algorithm with reliable performance for practical use, for example, an algorithm that guarantees an 80% chance of identifying at least 80 % of the relevant records. Based on a target-based method proposed in Cormack and Grossman, we propose a screening prioritization algorithm using sampling with replacement. The algorithm is a wrapper algorithm that can work with any current screening prioritization algorithm to guarantee the performance. We prove, with mathematics and probability theory, that the algorithm guarantees the performance. We also run numeric experiments to test the performance of our algorithm when applied in practice. The numeric experiment results show this algorithm achieve reliable performance under different circumstances. The proposed screening prioritization algorithm can be reliably used in real world research synthesis tasks.

Cystic fibrosis newborn screening in Switzerland - evaluation and scenarios for improvement after 11 years of follow-up.

BACKGROUND: Newborn bloodspot screening (NBS) for cystic fibrosis (CF) is important for early diagnosis and treatment. However, screening can lead to false-positive results leading to unnecessary follow-up tests and distress. This study evaluated the 11-year performance of the Swiss CF-NBS programme, estimated optimal cut-offs for immunoreactive trypsinogen (IRT), and examined how simulated algorithms would change performance. METHODS: The Swiss CF-NBS is based on an IRT-DNA algorithm with a second IRT (IRT-2) as safety net. We analysed data from 2011 to 2021, covering 959,006 IRT-1 analyses and 282 children with CF. We studied performance based on European Cystic Fibrosis Society (ECFS) standards including sensitivity, specificity, positive predictive value (PPV), false negative rate, and second heel-prick tests; identified optimal IRT cut-offs using receiver operating characteristics (ROC) curves; and calculated performance for simulated algorithms with different cut-offs for IRT-1, IRT-2, and safety net. RESULTS: The Swiss CF-NBS showed excellent sensitivity (96 %, 10 false negative cases) but moderate PPV (25 %). Optimal IRT-1 and IRT-2 cut-offs were identified at 2.7 (>99th percentile) and 5.9 (>99.8th percentile) z-scores, respectively. Analysis of simulated algorithms showed that removing the safety net from the current algorithm could increase PPV to 30 % and eliminate >200 second heel-prick tests per year, while keeping sensitivity at 95 %. CONCLUSION: The Swiss CF-NBS program performed well over 11 years but did not achieve the ECFS standards for PPV (≥30 %). Modifying or removing the safety net could improve PPV and reduce unnecessary follow-up tests while maintaining the ECFS standards for sensitivity.

Lynch syndrome-associated upper tract urothelial carcinoma frequently occurs in patients older than 60 years: an opportunity to revisit urology clinical guidelines.

Upper tract urothelial carcinoma (UTUC) is the third most common malignancy associated with Lynch syndrome (LS). The current European urology guidelines recommend screening for LS in patients with UTUC up to the age of 60 years. In this study, we examined a cohort of patients with UTUC for potential association with LS in order to establish the sensitivity of current guidelines in detecting LS. A total of 180 patients with confirmed diagnosis of UTUC were enrolled in the study during a 12-year period (2010-2022). Loss of DNA-mismatch repair proteins (MMRp) expression was identified in 15/180 patients (8.3%). Germline analysis was eventually performed in 8 patients confirming LS in 5 patients (2.8%), including 4 germline mutations in MSH6 and 1 germline mutation in MSH2. LS-related UTUC included 3 females and 2 males, with a mean age of 66.2 years (median 71 years, range 46-75 years). Four of five LS patients (all with MSH6 mutation) were older than 65 years (mean age 71.3, median 72 years). Our findings indicate that LS-associated UTUCs can occur in patients with LS older than 60 years. In contrast to previous studies which used mainly highly pre-selected populations with already diagnosed LS, the most frequent mutation in our cohort involved MSH6 gene. All MSH6 mutation carriers were > 65 years, and UTUC was the first LS manifestation in 2/4 patients. Using current screening guidelines, a significant proportion of patients with LS-associated UTUC may be missed. We suggest universal immunohistochemical MMRp screening for all UTUCs, regardless of age and clinical history.

PCR combined with serologic testing improves the yield and efficiency of SARS-CoV-2 infection hunting: A study in 40,689 consecutive overseas arrivals.

Background: The global epidemiological situation of COVID-19 remains serious. The rapid hunting of SARS-CoV-2 infection is the key means for preventing transmission. Methods: A total of 40,689 consecutive overseas arrivals were screened for SARS-CoV-2 infection based on PCR and serologic testing. The yield and efficiency of different screening algorithms were evaluated. Result: Among the 40,689 consecutive overseas arrivals, 56 (0.14%) subjects were confirmed to have SARS-CoV-2 infection. The asymptomatic rate was 76.8%. When the algorithm based on PCR alone was used, the identification yield of a single round of PCR (PCR1) was only 39.3% (95% CI: 26.1-52.5%). It took at least four rounds of PCR to achieve a yield of 92.9% (95% CI: 85.9-99.8%). Fortunately, an algorithm based on a single round of PCR combined with a single round of serologic testing (PCR1+ Ab1) greatly improved the screening yield to 98.2% (95% CI: 94.6-100.0%) and required 42,299 PCR and 40,689 serologic tests that cost 6,052,855 yuan. By achieving a similar yield, the cost of PCR1+ Ab1 was 39.2% of that of four rounds of PCR. For hunting one case in PCR1+ Ab1, 769 PCR and 740 serologic tests were required, costing 110,052 yuan, which was 63.0% of that of the PCR1 algorithm. Conclusion: Comparing an algorithm based on PCR alone, PCR combined with a serologic testing algorithm greatly improved the yield and efficiency of the identification of SARS-CoV-2 infection.

ADscreen: A speech processing-based screening system for automatic identification of patients with Alzheimer's disease and related dementia.

Alzheimer's disease and related dementias (ADRD) present a looming public health crisis, affecting roughly 5 million people and 11 % of older adults in the United States. Despite nationwide efforts for timely diagnosis of patients with ADRD, >50 % of them are not diagnosed and unaware of their disease. To address this challenge, we developed ADscreen, an innovative speech-processing based ADRD screening algorithm for the protective identification of patients with ADRD. ADscreen consists of five major components: (i) noise reduction for reducing background noises from the audio-recorded patient speech, (ii) modeling the patient's ability in phonetic motor planning using acoustic parameters of the patient's voice, (iii) modeling the patient's ability in semantic and syntactic levels of language organization using linguistic parameters of the patient speech, (iv) extracting vocal and semantic psycholinguistic cues from the patient speech, and (v) building and evaluating the screening algorithm. To identify important speech parameters (features) associated with ADRD, we used the Joint Mutual Information Maximization (JMIM), an effective feature selection method for high dimensional, small sample size datasets. Modeling the relationship between speech parameters and the outcome variable (presence/absence of ADRD) was conducted using three different machine learning (ML) architectures with the capability of joining informative acoustic and linguistic with contextual word embedding vectors obtained from the DistilBERT (Bidirectional Encoder Representations from Transformers). We evaluated the performance of the ADscreen on an audio-recorded patients' speech (verbal description) for the Cookie-Theft picture description task, which is publicly available in the dementia databank. The joint fusion of acoustic and linguistic parameters with contextual word embedding vectors of DistilBERT achieved F1-score = 84.64 (standard deviation [std] = ±3.58) and AUC-ROC = 92.53 (std = ±3.34) for training dataset, and F1-score = 89.55 and AUC-ROC = 93.89 for the test dataset. In summary, ADscreen has a strong potential to be integrated with clinical workflow to address the need for an ADRD screening tool so that patients with cognitive impairment can receive appropriate and timely care.

Use of a beta-lactam graded challenge process for inpatients with self-reported penicillin allergies at an academic medical center.

Background: The Antimicrobial Stewardship Program (ASP) at Nebraska Medicine collaborated with a board-certified allergist to develop a penicillin allergy guidance document for treating inpatients with self-reported allergy. This guidance contains an algorithm for evaluating and safely challenging penicillin-allergic patients with beta-lactams without inpatient allergy consults being available. Methods: Following multi-disciplinary review, an order set for beta-lactam graded challenges (GC) was implemented in 2018. This contains recommended monitoring and detailed medication orders to challenge patients with various beta-lactam agents. Inpatient orders for GC from 3/2018-6/2022 were retrospectively reviewed to evaluate ordering characteristics, outcomes of the challenge, and whether documentation of the allergy history was updated. All beta-lactam challenges administered to inpatients were included, and descriptive statistics were performed. Results: Overall, 157 GC were administered; 13 with oral amoxicillin and 144 with intravenous (IV) beta-lactams. Ceftriaxone accounted for the most challenges (43%). All oral challenges were recommended by an Infectious Diseases consult service, as were a majority of IV challenges (60%). Less than one in five were administered in an ICU (19%). Almost all (n = 150, 96%) were tolerated without any adverse event. There was one reaction (1%) of hives and six (4%) involving a rash, none of which had persistent effects. Allergy information was updated in the electronic health record after 92% of the challenges. Conclusion: Both intravenous and oral beta-lactam graded challenges were implemented successfully in a hospital without a regular inpatient allergy consult service. They were well-tolerated, administered primarily in non-ICU settings, and were often ordered by non-specialist services. In patients with a self-reported penicillin allergy, these results demonstrate the utility and safety of a broadly adopted beta-lactam GC process.

Factors associated with positive predictive value of preliminary screening in a two-step screening strategy for colorectal neoplasms in China.

BACKGROUND: The positive predictive value (PPV) of high risk factor questionnaire (HRFQ) plus fecal immunochemical test (FIT) as preliminary screening strategy for colorectal-related neoplasia is relatively low. We aim to explore independent factors associated with PPVs of HRFQ combined FIT for selecting high risk individuals for colonoscopy. METHODS: A total of 6971 residents were enrolled in a community-based screening program. Participants who had positive results of HRFQ and/or FIT and subsequently received colonoscopy were involved. The associations of socio-demographic factors, lifestyle behaviors, and high risk factors of colorectal cancer with PPVs of HRFQ, FIT, and their combination were evaluated by multivariable logistic regression models. RESULTS: Among 572 involved cases, 249 (43.5%) colorectal neoplasms were detected by colonoscopy, including 71 advanced adenoma (12.4%) and 9 colorectal cancer (CRC) (1.6%). The PPVs of preliminary screening were 43.5% for total colorectal neoplasms, 14.0% for advanced neoplasm, and 1.6% for CRC. Adding positive HRFQ to FIT could improve the PPV from 3.5 to 8.0% for detecting CRC. Preliminarily screened positive individuals who were males [adjusted odds ratio (AOR): 1.95, 95% CI 1.31, 2.90; p < 0.001], elders (> 60 years) (AOR: 1.70, 95% CI 1.17, 2.46; p = 0.005), or ex-/current smokers (AOR: 3.04, 95% CI 1.31, 7.09; p = 0.10) had higher odds of PPVs of detecting colorectal neoplasms. CONCLUSIONS: Combining HRFQ and FIT could largely improve PPVs for screening advanced neoplasm and CRC. Gender and age-specific FIT cut-off values as well as initiating ages for CRC screening might be recommended to improve the accuracy and effectiveness of current screening algorithm.

A conservative screening algorithm to determine candidacy for robotic mitral valve surgery.

OBJECTIVE: Patient selection for robotically assisted mitral valve repair remains controversial. We assessed outcomes of a conservative screening algorithm developed to select patients with degenerative mitral valve disease for robotic surgery. METHODS: From January 2014 to January 2019, a screening algorithm that included transthoracic echocardiography and computed tomography scanning was rigorously applied by 3 surgeons to assess candidacy of 1000 consecutive patients with isolated degenerative mitral valve disease (age 58 ± 11 years, 67% male) for robotic surgery. Screening results and hospital outcomes of those selected for robotic versus sternotomy approaches were compared. RESULTS: With application of the screening algorithm, 605 patients were selected for robotic surgery. Common reasons for sternotomy (n = 395) were aortoiliac atherosclerosis (n = 74/292, 25%), femoral artery diameter <7 mm (n = 60/292, 20%), mitral annular calcification (n = 83/390, 21%), aortic regurgitation (n = 100/391, 26%), and reduced left ventricular function (n = 126/391, 32%). Mitral valve repair was accomplished in 996. Compared with sternotomy, patients undergoing robotic surgery had less new-onset atrial fibrillation (n = 144/582, 25% vs n = 125/373, 34%; P = .002), fewer red blood cell transfusions (n = 61/601, 10% vs 69/395, 17%; P < .001), and shorter hospital stay (5.2 ± 2.9 days vs 5.9 ± 2.1 days; P < .001). No hospital deaths occurred, and occurrence of postoperative stroke in the robotic (n = 3/605, 0.50%) and sternotomy (n = 4/395, 1.0%; P = .3) groups was similar. CONCLUSIONS: This conservative screening algorithm qualified 60% of patients with isolated degenerative mitral valve disease for robotic surgery. Outcomes were comparable with those obtained with sternotomy, validating this as an approach to select patients for robotic mitral valve surgery.

Rapid deployment of an algorithm to triage dental emergencies during COVID-19 pandemic.

COVID-19 quickly immobilized healthcare systems in the United States during the early stages of the outbreak. While much of the ensuing response focused on supporting the medical infrastructure, Columbia University College of Dental Medicine pursued a solution to triage and safely treat patients with dental emergencies amid the pandemic. Considering rapidly changing guidelines from governing bodies, dental infection control protocols, and our clinical faculty's expertise, we modeled, built, and implemented a screening algorithm, which provides decision support as well as insight into COVID-19 status and clinical comorbidities, within a newly integrated electronic health record (EHR). Once operationalized, we analyzed the data and outcomes of its utilization and found that it had effectively guided providers in triaging patient needs in a standardized methodology. This article describes the algorithm's rapid development to assist faculty providers in identifying patients with the most urgent needs, thus prioritizing treatment of dental emergencies during the pandemic.

Optimization of workflow and screening panels for the detection of malignant monoclonal gammopathies.

Objectives: Multiple myeloma (MM) is one of the hematologic malignancies with a greater delay in diagnosis. Laboratories receive numerous MM screening test requests without a specific suspicion, which entails a substantial workload and reduces the efficiency of laboratories. Objective: to increase the efficacy of MM screening protocols. Methods: The results of serum protein electrophoresis (SPEP), serum protein immunofixation electrophoresis (SIFE), urine protein immunofixation electrophoresis, and serum free light chain assays of 75 patients with MM, three with amyloidosis, and a patient with solitary plasmocytoma were collected. The frequency of a set of biochemical alterations in these patients was compared with that in controls (n=120). A validation of the screening algorithm was carried out in 261 consecutive patients with a clinical or analytical suspicion of MM. Results: SPEP+SFLC or SIFE+SFLC (98% sensitivity) were the screening algorithms with the highest sensitivity. Prospectively, the SPEP + SFLC detected 27 of the 28 confirmed cases of MG and saved 15 h of work. Alterations in five of the six parameters studied were more frequent in the study group, with a cumulative value of ≥3 parameters altered (61.1 vs. 1.7%) (positive predictive value: 85%; negative predictive value: 94%). Conclusions: The SPEP+SFLC screening protocol demonstrated the highest sensitivity and was the least time-consuming protocol. In addition, this protocol improves diagnostic sensitivity and laboratory performance.

Diagnosing Post-Cesarean Surgical Site Infections in Rural Rwanda: Development, Validation, and Field Testing of a Screening Algorithm for Use by Community Health Workers.

Background: We aimed to develop and validate a screening algorithm to assist community health workers (CHWs) in identifying surgical site infections (SSIs) after cesarean section (c-section) in rural Africa. Methods: Patients were adult women who underwent c-section at a Rwandan rural district hospital between March and October 2017. A CHW administered a nine-item clinical questionnaire 10 ± 3 days post-operatively. Independently, a general practitioner (GP) administered the same questionnaire and assessed SSI presence by physical examination. The GP's SSI diagnosis was used as the gold standard. Using a simplified Classification and Regression Tree analysis, we identified a subset of screening questions with maximum sensitivity for the GP and CHW and evaluated the subset's sensitivity and specificity in a validation dataset. Then, we compared the subset's results when implemented in the community by CHWs with health center-reported SSI. Results: Of the 596 women enrolled, 525 (88.1%) completed the clinical questionnaire. The combination of questions concerning fever, pain, and discolored drainage maximized sensitivity for both the GPs (sensitivity = 96.8%; specificity = 85.6%) and CHWs (sensitivity = 87.1%; specificity = 73.8%). In the validation dataset, this subset had sensitivity of 95.2% and specificity of 83.3% for the GP-administered questions and sensitivity of 76.2% and specificity of 81.4% for the CHW-administered questions. In the community screening, the overall percent agreement between CHW and health center diagnoses was 81.1% (95% confidence interval: 77.2%-84.6%). Conclusions: We identified a subset of questions that had good predictive features for SSI, but its sensitivity was lower when administered by CHWs in a clinical setting, and it performed poorly in the community. Methods to improve diagnostic ability, including training or telemedicine, must be explored.

Direct Challenges to Penicillin-Based Antibiotics in the Inpatient Setting.

BACKGROUND: Direct challenge (DC) is an emerging safe and effective alternative to penicillin skin testing (PST) in patients reporting a low-risk reaction history, but limited data exist for the inpatient setting. OBJECTIVE: To demonstrate the safety and efficacy of DC of penicillin-based antibiotics in the inpatient setting in patients with low-risk, cutaneous-only reaction histories more than 20 years ago. METHODS: Adult inpatients reporting penicillin allergy and receiving antibiotics were screened by an infectious disease PharmD for appropriateness for penicillin allergy delabeling. Patients with low-risk, cutaneous-only reaction histories (rash, hives, itching) more than 20 years ago were offered a 3-step DC. Patients with a cutaneous reaction history less than 20 years ago, a history of angioedema, or reactions involving multiple body systems underwent PST followed by a 1-time observed dose of amoxicillin. RESULTS: A total of 372 patients were screened during the study period, with 100 of these patients undergoing further evaluation, 52 with histories appropriate for PST and 48 with histories appropriate for DC. In the PST group, 44 of 52 (84.6%) patients were PST negative. In the DC group, 47 of 48 (97.9%) patients initially tolerated the DC, with 2 of 48 (4.2%) experiencing a delayed reaction. The sole patient with an immediate DC reaction was treated with an antihistamine alone. Beta-lactam antibiotics were subsequently used in 56 of the 100 total patients. Total direct antibiotic savings was $23,375.27. DC was less costly than PST, at $206.18/patient versus $419.63/patient. CONCLUSIONS: DC is a safe, effective, and less expensive method for penicillin delabeling in adult inpatients with a low-risk, cutaneous-only reaction history more than 20 years ago.

Methylation-Based Signatures for Gastroesophageal Tumor Classification.

Contention exists within the field of oncology with regards to gastroesophageal junction (GEJ) tumors, as in the past, they have been classified as gastric cancer, esophageal cancer, or a combination of both. Misclassifications of GEJ tumors ultimately influence treatment options, which may be rendered ineffective if treating for the wrong cancer attributes. It has been suggested that misclassification rates were as high as 45%, which is greater than reported for junctional cancer occurrences. Here, we aimed to use the methylation profiles of GEJ tumors to improve classifications of GEJ tumors. Four cohorts of DNA methylation profiles, containing ~27,000 (27k) methylation sites per sample, were collected from the Gene Expression Omnibus and The Cancer Genome Atlas. Tumor samples were assigned into discovery (nEC = 185, nGC = 395; EC, esophageal cancer; GC gastric cancer) and validation (nEC = 179, nGC = 369) sets. The optimized Multi-Survival Screening (MSS) algorithm was used to identify methylation biomarkers capable of distinguishing GEJ tumors. Three methylation signatures were identified: They were associated with protein binding, gene expression, and cellular component organization cellular processes, and achieved precision and recall rates of 94.7% and 99.2%, 97.6% and 96.8%, and 96.8% and 97.6%, respectively, in the validation dataset. Interestingly, the methylation sites of the signatures were very close (i.e., 170-270 base pairs) to their downstream transcription start sites (TSSs), suggesting that the methylations near TSSs play much more important roles in tumorigenesis. Here we presented the first set of methylation signatures with a higher predictive power for characterizing gastroesophageal tumors. Thus, they could improve the diagnosis and treatment of gastroesophageal tumors.