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1. Lead one ratio in left bundle branch block predicts poor cardiac resynchronization therapy response

   https://doi.org/10.1111/pace.13916  

   Loring, Zak ; Friedman, Daniel J. ; Emerek, Kasper ; Graff, Claus ; Sørensen, Peter L. ; Hansen, Steen M. ; Wieslander, Bjorn ; Ugander, Martin ; Søgaard, Peter ; Atwater, Brett D. ( May 2020 , Pacing and Clinical Electrophysiology)

   A low electrocardiogram (ECG) lead one ratio (LOR) of the maximum positive/negative QRS amplitudes is associated with lower left ventricular ejection fraction (LVEF) and worse outcomes in left bundle branch block (LBBB); however, the impact of LOR on cardiac resynchronization therapy (CRT) outcomes is unknown. We compared clinical outcomes and echocardiographic changes after CRT implantation by LOR.

   Consecutive CRT‐defibrillator recipients with LBBB implanted between 2006 and 2015 at Duke University Medical Center were included (N = 496). Time to heart transplant, left ventricular assist device (LVAD) implantation, or death was compared among patients with LOR <12 vs ≥12 using Cox‐proportional hazard models. Changes in LVEF and LV volumes after CRT were compared by LOR.

   Baseline ECG LOR <12 was associated with an adjusted hazard ratio (HR) of 1.69 (95% CI: 1.12‐2.40,P = .01) for heart transplant, LVAD, or death. Patients with LOR <12 had less reduction of LV end diastolic volume (ΔLVEDV −4 ± 21 vs −13 ± 23%,P = .04) and LV end systolic volume (ΔLVESV −9 ± 27 vs −22 ± 26%,P = .03) after CRT. In patients with QRS duration (QRSd) ≥150 ms, LOR <12 was associated with an adjusted HR of 2.01 (95% CI 1.21‐3.35,P = .008) for heart transplant, LVAD, or death, compared with LOR ≥12.

   Baseline ECG LOR <12 portends worse outcomes after CRT implantation in patients with LBBB, specifically among those with QRSd ≥150 ms. This ECG ratio may identify patients with a class I indication for CRT implantation at high risk for poor postimplantation outcomes.

    

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2. The distribution of triatomine (Hemiptera: Reduviidae) vectors of Trypanosoma cruzi (Kinetoplastida: Trypanosomatidae) in Illinois and Missouri: historical records and specimen submissions from community science programs

   https://doi.org/10.1093/jme/tjad124  

   Santos, Ellen M. ; Santanello, Catherine D. ; Curtis-Robles, Rachel ; Killets, Keswick ; Lawrence, Gena ; Sevenshadows, Jet ; Mahoney, Meredith J. ; Baker, Molly ; Hamer, Sarah A. ; Poh, ed., Karen ( December 2023 , Journal of Medical Entomology)

   Triatomine species (kissing bugs) infected with Trypanosoma cruzi are found across the southern United States. The northern limits of Trypanosoma cruzi infected kissing bugs are less understood. The objective of this work was to describe the locations of kissing bugs from Illinois and Missouri based on historical records, submissions to Texas A&M University’s (TAMU) Kissing Bug Community Science Program and the Centers for Disease Control and Prevention (CDC), and records from online platforms (iNaturalist, BugGuide, and GBIF) up to and including 2022. A total of 228 records were discovered, including 186 from historical or observation platforms and 42 specimens submitted to TAMU or CDC. Species included Triatoma sanguisuga (221 total records, 9 nymphs) and Triatoma lecticularia (7 records). Notably, nearly all (24/26) records submitted to TAMU were collected indoors. Twelve of the 30 (40%) specimens tested were positive for the presence of T. cruzi, including parasite discrete taxonomic units TcI and TcIV. One triatomine sample had been found in a bed feeding on the submitter; this bug was positive for T. cruzi and had evidence of human blood in its gut. Records suggest a ubiquitous distribution in Missouri and potentially to the northernmost border in Illinois. Further investigations into triatomine distribution and infection status are needed within states assumed to be northern limits in order to create public health and veterinary health messaging and baseline distributional maps from which to measure future range shifts in relation to a changing climate.

    

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3. Use of machine-learning algorithms to aid in the early detection of leptospirosis in dogs

   https://doi.org/10.1177/10406387221096781  

   Reagan, Krystle L. ; Deng, Shaofeng ; Sheng, Junda ; Sebastian, Jamie ; Wang, Zhe ; Huebner, Sara N. ; Wenke, Louise A. ; Michalak, Sarah R. ; Strohmer, Thomas ; Sykes, Jane E. ( July 2022 , Journal of Veterinary Diagnostic Investigation)

   Leptospirosis is a life-threatening, zoonotic disease with various clinical presentations, including renal injury, hepatic injury, pancreatitis, and pulmonary hemorrhage. With prompt recognition of the disease and treatment, 90% of infected dogs have a positive outcome. Therefore, rapid, early diagnosis of leptospirosis is crucial. Testing for Leptospira-specific serum antibodies using the microscopic agglutination test (MAT) lacks sensitivity early in the disease process, and diagnosis can take >2 wk because of the need to demonstrate a rise in titer. We applied machine-learning algorithms to clinical variables from the first day of hospitalization to create machine-learning prediction models (MLMs). The models incorporated patient signalment, clinicopathologic data (CBC, serum chemistry profile, and urinalysis = blood work [BW] model), with or without a MAT titer obtained at patient intake (=BW + MAT model). The models were trained with data from 91 dogs with confirmed leptospirosis and 322 dogs without leptospirosis. Once trained, the models were tested with a cohort of dogs not included in the model training (9 leptospirosis-positive and 44 leptospirosis-negative dogs), and performance was assessed. Both models predicted leptospirosis in the test set with 100% sensitivity (95% CI: 70.1–100%). Specificity was 90.9% (95% CI: 78.8–96.4%) and 93.2% (95% CI: 81.8–97.7%) for the BW and BW + MAT models, respectively. Our MLMs outperformed traditional acute serologic screening and can provide accurate early screening for the probable diagnosis of leptospirosis in dogs. 

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4. Prevalence and Correlates of Long COVID Symptoms Among US Adults

   https://doi.org/10.1001/jamanetworkopen.2022.38804  

   Perlis, Roy H. ; Santillana, Mauricio ; Ognyanova, Katherine ; Safarpour, Alauna ; Lunz Trujillo, Kristin ; Simonson, Matthew D. ; Green, Jon ; Quintana, Alexi ; Druckman, James ; Baum, Matthew A. ; et al ( October 2022 , JAMA Network Open)

   Persistence of COVID-19 symptoms beyond 2 months, or long COVID, is increasingly recognized as a common sequela of acute infection.

   To estimate the prevalence of and sociodemographic factors associated with long COVID and to identify whether the predominant variant at the time of infection and prior vaccination status are associated with differential risk.

   This cross-sectional study comprised 8 waves of a nonprobability internet survey conducted between February 5, 2021, and July 6, 2022, among individuals aged 18 years or older, inclusive of all 50 states and the District of Columbia.

   Long COVID, defined as reporting continued COVID-19 symptoms beyond 2 months after the initial month of symptoms, among individuals with self-reported positive results of a polymerase chain reaction test or antigen test.

   The 16 091 survey respondents reporting test-confirmed COVID-19 illness at least 2 months prior had a mean age of 40.5 (15.2) years; 10 075 (62.6%) were women, and 6016 (37.4%) were men; 817 (5.1%) were Asian, 1826 (11.3%) were Black, 1546 (9.6%) were Hispanic, and 11 425 (71.0%) were White. From this cohort, 2359 individuals (14.7%) reported continued COVID-19 symptoms more than 2 months after acute illness. Reweighted to reflect national sociodemographic distributions, these individuals represented 13.9% of those who had tested positive for COVID-19, or 1.7% of US adults. In logistic regression models, older age per decade above 40 years (adjusted odds ratio [OR], 1.15; 95% CI, 1.12-1.19) and female gender (adjusted OR, 1.91; 95% CI, 1.73-2.13) were associated with greater risk of persistence of long COVID; individuals with a graduate education vs high school or less (adjusted OR, 0.67; 95% CI, 0.56-0.79) and urban vs rural residence (adjusted OR, 0.74; 95% CI, 0.64-0.86) were less likely to report persistence of long COVID. Compared with ancestral COVID-19, infection during periods when the Epsilon variant (OR, 0.81; 95% CI, 0.69-0.95) or the Omicron variant (OR, 0.77; 95% CI, 0.64-0.92) predominated in the US was associated with diminished likelihood of long COVID. Completion of the primary vaccine series prior to acute illness was associated with diminished risk for long COVID (OR, 0.72; 95% CI, 0.60-0.86).

   This study suggests that long COVID is prevalent and associated with female gender and older age, while risk may be diminished by completion of primary vaccination series prior to infection.

    

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5. Performance evaluation and validation of the Animal Trauma Triage score and modified Glasgow Coma Scale in injured cats: A Veterinary Committee on Trauma registry study

   https://doi.org/10.1111/vec.12885  

   Lapsley, Janis ; Hayes, Galina M. ; Sumner, Julia P. ( August 2019 , Journal of Veterinary Emergency and Critical Care)

   To examine the Animal Trauma Triage (ATT) and modified Glasgow Coma Scale (mGCS) scores as predictors of mortality in injured cats.

   Observational cohort study conducted September 2013 to March 2015.

   Nine Level I and II veterinary trauma centers.

   Consecutive sample of 711 cats reported on the Veterinary Committee on Trauma (VetCOT) case registry.

   None.

   We compared the predictive power (area under receiver operating characteristic curve; AUROC) and calibration of the ATT and mGCS scores to their components. Overall mortality risk was 16.5% (95% confidence interval [CI], 13.9‐19.4). Head trauma prevalence was 11.8% (n = 84). The ATT score showed a linear relationship with mortality risk. Discriminatory performance of the ATT score was excellent (AUROC = 0.87 [95% CI, 0.84‐0.90]). Each ATT score increase of 1 point was associated with an increase in mortality odds of 1.78 (95% CI, 1.61‐1.97,P < 0.001). The eye/muscle/integument category of the ATT showed the lowest discrimination (AUROC = 0.60). When this component, skeletal, and cardiac components were omitted from score calculation, there was no loss in discriminatory capacity compared with the full score (AUROC = 0.86 vs 0.87, respectively,P= 0.66). The mGCS showed fair performance overall for prediction of mortality, but the point estimate of performance improved when restricted to head trauma patients (AUROC = 0.75, 95% CI, 0.70‐0.80 vs AUROC = 0.80, 95% CI, 0.70‐0.90). The motor component of the mGCS showed the best predictive performance (AUROC = 0.71); however, the full score performed better than the motor component alone (P= 0.004). When assessment was restricted to patients with head injury (n = 84), there was no difference in performance between the ATT and mGCS scores (AUROC = 0.82 vs 0.80,P= 0.67).

   On a large, multicenter dataset of feline trauma patients, the ATT score showed excellent discrimination and calibration for predicting mortality; however, an abbreviated score calculated from the perfusion, respiratory, and neurologic categories showed equivalent performance.

    

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