Diagnostic yield from prenatal exome sequencing for non-immune hydrops fetalis: A systematic review and meta-analysis.

Non-immune hydrops fetalis (NIHF) has multiple genetic etiologies diagnosable by exome sequencing (ES). We evaluated the yield of prenatal ES for NIHF, and the contribution of additional clinical findings and history. Systematic review was performed with PROSPERO tag 232951 using CINAHL, PubMed, and Ovid MEDLINE from January 1, 2000 through December 1, 2021. Selected studies performed ES to augment standard prenatal diagnostic approaches. Cases meeting a strict NIHF phenotype were tabulated with structured data imputed from papers or requested from authors. Genetic variants and diagnostic outcomes were harmonized across studies using current ACMG and ClinGen variant classification guidelines. Thirty-one studies reporting 445 NIHF cases had a 37% (95% CI: 32%-41%) diagnostic rate. There was no significant difference between isolated NIHF and NIHF with fetal malformations or between recurrent and simplex cases. Diagnostic rate was higher for consanguineous than non-consanguineous cases. Disease categories included RASopathies (24%), neuromuscular (21%), metabolic (17%), lymphatic (13%), other syndromes (9%), cardiovascular (5%), hematologic (2%), skeletal (2%), and other categories (7%). Inheritance patterns included recessive (55%), dominant (41%), and X-linked (4%). ES should be considered in the diagnostic workup of NIHF with and without associated ultrasound findings regardless of history of recurrence or consanguinity.

Transmission of Mobile Colistin Resistance (mcr-1) by Duodenoscope.

BACKGROUND: Clinicians increasingly utilize polymyxins for treatment of serious infections caused by multidrug-resistant gram-negative bacteria. Emergence of plasmid-mediated, mobile colistin resistance genes creates potential for rapid spread of polymyxin resistance. We investigated the possible transmission of Klebsiella pneumoniae carrying mcr-1 via duodenoscope and report the first documented healthcare transmission of mcr-1-harboring bacteria in the United States. METHODS: A field investigation, including screening targeted high-risk groups, evaluation of the duodenoscope, and genome sequencing of isolated organisms, was conducted. The study site included a tertiary care academic health center in Boston, Massachusetts, and extended to community locations in New England. RESULTS: Two patients had highly related mcr-1-positive K. pneumoniae isolated from clinical cultures; a duodenoscope was the only identified epidemiological link. Screening tests for mcr-1 in 20 healthcare contacts and 2 household contacts were negative. Klebsiella pneumoniae and Escherichia coli were recovered from the duodenoscope; neither carried mcr-1. Evaluation of the duodenoscope identified intrusion of biomaterial under the sealed distal cap; devices were recalled to repair this defect. CONCLUSIONS: We identified transmission of mcr-1 in a United States acute care hospital that likely occurred via duodenoscope despite no identifiable breaches in reprocessing or infection control practices. Duodenoscope design flaws leading to transmission of multidrug-resistant organsisms persist despite recent initiatives to improve device safety. Reliable detection of colistin resistance is currently challenging for clinical laboratories, particularly given the absence of a US Food and Drug Administration-cleared test; improved clinical laboratory capacity for colistin susceptibility testing is needed to prevent the spread of mcr-carrying bacteria in healthcare settings.

The Impact of a Reported Penicillin Allergy on Surgical Site Infection Risk.

Background: A reported penicillin allergy may compromise receipt of recommended antibiotic prophylaxis intended to prevent surgical site infections (SSIs). Most patients with a reported penicillin allergy are not allergic. We determined the impact of a reported penicillin allergy on the development of SSIs. Methods: In this retrospective cohort study of Massachusetts General Hospital hip arthroplasty, knee arthroplasty, hysterectomy, colon surgery, and coronary artery bypass grafting patients from 2010 to 2014, we compared patients with and without a reported penicillin allergy. The primary outcome was an SSI, as defined by the Centers for Disease Control and Prevention's National Healthcare Safety Network. The secondary outcome was perioperative antibiotic use. Results: Of 8385 patients who underwent 9004 procedures, 922 (11%) reported a penicillin allergy, and 241 (2.7%) had an SSI. In multivariable logistic regression, patients reporting a penicillin allergy had increased odds (adjusted odds ratio, 1.51; 95% confidence interval, 1.02-2.22) of SSI. Penicillin allergy reporters were administered less cefazolin (12% vs 92%; P < .001) and more clindamycin (49% vs 3%; P < .001), vancomycin (35% vs 3%; P < .001), and gentamicin (24% vs 3%; P < .001) compared with those without a reported penicillin allergy. The increased SSI risk was entirely mediated by the patients' receipt of an alternative perioperative antibiotic; between 112 and 124 patients with reported penicillin allergy would need allergy evaluation to prevent 1 SSI. Conclusions: Patients with a reported penicillin allergy had a 50% increased odds of SSI, attributable to the receipt of second-line perioperative antibiotics. Clarification of penicillin allergies as part of routine preoperative care may decrease SSI risk.

A Discrete Event Simulation Model of Patient Flow in a General Hospital Incorporating Infection Control Policy for Methicillin-Resistant Staphylococcus Aureus (MRSA) and Vancomycin-Resistant Enterococcus (VRE).

BACKGROUND: Hospitalized patients are assigned to available staffed beds based on patient acuity and services required. In hospitals with double-occupancy rooms, patients must be additionally matched by gender. Patients with methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant Enterococcus (VRE) must be bedded in single-occupancy rooms or cohorted with other patients with similar MRSA/VRE flags. METHODS: We developed a discrete event simulation (DES) model of patient flow through an acute care hospital. Patients are matched to beds based on acuity, service, gender, and known MRSA/VRE colonization. Outcomes included time to bed arrival, length of stay, patient-bed acuity mismatches, occupancy, idle beds, acuity-related transfers, rooms with discordant MRSA/VRE colonization, and transmission due to discordant colonization. RESULTS: Observed outcomes were well-approximated by model-generated outcomes for time-to-bed arrival (6.7 v. 6.2 to 6.5 h) and length of stay (3.3 v. 2.9 to 3.0 days), with overlapping 90% coverage intervals. Patient-bed acuity mismatches, where patient acuity exceeded bed acuity and where patient acuity was lower than bed acuity, ranged from 0.6 to 0.9 and 8.6 to 11.1 mismatches per h, respectively. Values for observed occupancy, total idle beds, and acuity-related transfers compared favorably to model-predicted values (91% v. 86% to 87% occupancy, 15.1 v. 14.3 to 15.7 total idle beds, and 27.2 v. 22.6 to 23.7 transfers). Rooms with discordant colonization status and transmission due to discordance were modeled without an observed value for comparison. One-way and multi-way sensitivity analyses were performed for idle beds and rooms with discordant colonization. CONCLUSIONS: We developed and validated a DES model of patient flow incorporating MRSA/VRE flags. The model allowed for quantification of the substantial impact of MRSA/VRE flags on hospital efficiency and potentially avoidable nosocomial transmission.

Real-Time, Automated Detection of Ventilator-Associated Events: Avoiding Missed Detections, Misclassifications, and False Detections Due to Human Error.

OBJECTIVETo validate a system to detect ventilator associated events (VAEs) autonomously and in real time.DESIGNRetrospective review of ventilated patients using a secure informatics platform to identify VAEs (ie, automated surveillance) compared to surveillance by infection control (IC) staff (ie, manual surveillance), including development and validation cohorts.SETTINGThe Massachusetts General Hospital, a tertiary-care academic health center, during January-March 2015 (development cohort) and January-March 2016 (validation cohort).PATIENTSVentilated patients in 4 intensive care units.METHODSThe automated process included (1) analysis of physiologic data to detect increases in positive end-expiratory pressure (PEEP) and fraction of inspired oxygen (FiO2); (2) querying the electronic health record (EHR) for leukopenia or leukocytosis and antibiotic initiation data; and (3) retrieval and interpretation of microbiology reports. The cohorts were evaluated as follows: (1) manual surveillance by IC staff with independent chart review; (2) automated surveillance detection of ventilator-associated condition (VAC), infection-related ventilator-associated complication (IVAC), and possible VAP (PVAP); (3) senior IC staff adjudicated manual surveillance-automated surveillance discordance. Outcomes included sensitivity, specificity, positive predictive value (PPV), and manual surveillance detection errors. Errors detected during the development cohort resulted in algorithm updates applied to the validation cohort.RESULTSIn the development cohort, there were 1,325 admissions, 479 ventilated patients, 2,539 ventilator days, and 47 VAEs. In the validation cohort, there were 1,234 admissions, 431 ventilated patients, 2,604 ventilator days, and 56 VAEs. With manual surveillance, in the development cohort, sensitivity was 40%, specificity was 98%, and PPV was 70%. In the validation cohort, sensitivity was 71%, specificity was 98%, and PPV was 87%. With automated surveillance, in the development cohort, sensitivity was 100%, specificity was 100%, and PPV was 100%. In the validation cohort, sensitivity was 85%, specificity was 99%, and PPV was 100%. Manual surveillance detection errors included missed detections, misclassifications, and false detections.CONCLUSIONSManual surveillance is vulnerable to human error. Automated surveillance is more accurate and more efficient for VAE surveillance.Infect Control Hosp Epidemiol 2018;826-833.

A Generalizable, Data-Driven Approach to Predict Daily Risk of Clostridium difficile Infection at Two Large Academic Health Centers.

OBJECTIVE An estimated 293,300 healthcare-associated cases of Clostridium difficile infection (CDI) occur annually in the United States. To date, research has focused on developing risk prediction models for CDI that work well across institutions. However, this one-size-fits-all approach ignores important hospital-specific factors. We focus on a generalizable method for building facility-specific models. We demonstrate the applicability of the approach using electronic health records (EHR) from the University of Michigan Hospitals (UM) and the Massachusetts General Hospital (MGH). METHODS We utilized EHR data from 191,014 adult admissions to UM and 65,718 adult admissions to MGH. We extracted patient demographics, admission details, patient history, and daily hospitalization details, resulting in 4,836 features from patients at UM and 1,837 from patients at MGH. We used L2 regularized logistic regression to learn the models, and we measured the discriminative performance of the models on held-out data from each hospital. RESULTS Using the UM and MGH test data, the models achieved area under the receiver operating characteristic curve (AUROC) values of 0.82 (95% confidence interval [CI], 0.80-0.84) and 0.75 ( 95% CI, 0.73-0.78), respectively. Some predictive factors were shared between the 2 models, but many of the top predictive factors differed between facilities. CONCLUSION A data-driven approach to building models for estimating daily patient risk for CDI was used to build institution-specific models at 2 large hospitals with different patient populations and EHR systems. In contrast to traditional approaches that focus on developing models that apply across hospitals, our generalizable approach yields risk-stratification models tailored to an institution. These hospital-specific models allow for earlier and more accurate identification of high-risk patients and better targeting of infection prevention strategies. Infect Control Hosp Epidemiol 2018;39:425-433.

The Impact of Methicillin-Resistant Staphylococcus aureus (MRSA) and Vancomycin-Resistant Enterococcus (VRE) Flags on Hospital Operations.

OBJECTIVE To determine the impact of methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus (MRSA/VRE) designations, or flags, on selected hospital operational outcomes. DESIGN Retrospective cohort study of inpatients admitted to the Massachusetts General Hospital during 2010-2011. METHODS Operational outcomes were time to bed arrival, acuity-unrelated within-hospital transfers, and length of stay. Covariates considered included demographic and clinical characteristics: age, gender, severity of illness on admission, admit day of week, residence prior to admission, hospitalization within the prior 30 days, clinical service, and discharge destination. RESULTS Overall, 81,288 admissions were included. After adjusting for covariates, patients with a MRSA/VRE flag at the time of admission experienced a mean delay in time to bed arrival of 1.03 hours (9.63 hours [95% CI, 9.39-9.88] vs 8.60 hours [95% CI, 8.47-8.73]). These patients had 1.19 times the odds of experiencing an acuity-unrelated within-hospital transfer [95% CI, 1.13-1.26] and a mean length of stay 1.76 days longer (7.03 days [95% CI, 6.82-7.24] vs 5.27 days [95% CI, 5.15-5.38]) than patients with no MRSA/VRE flag. CONCLUSIONS MRSA/VRE designation was associated with delays in time to bed arrival, increased likelihood of acuity-unrelated within-hospital transfers and extended length of stay. Efforts to identify patients who have cleared MRSA/VRE colonization are critically important to mitigate inefficient use of resources and to improve inpatient flow. Infect Control Hosp Epidemiol 2016;37:782-790.