Relationship Between Oral Temperature and Bacteremia in Hospitalized Patients.

BACKGROUND: Early recognition and treatment of bacteremia can be lifesaving. Fever is a well-known marker of bacteremia, but the predictive value of temperature has not been fully explored. OBJECTIVE: To describe temperature as a predictor of bacteremia and other infections. DESIGN: Retrospective review of electronic health record data. SETTING: A single healthcare system comprising 13 hospitals in the United States. PATIENTS: Adult medical patients admitted in 2017 or 2018 without malignancy or immunosuppression. MAIN MEASURES: Maximum temperature, bacteremia, influenza and skin and soft tissue (SSTI) infections based on blood cultures and ICD-10 coding. KEY RESULTS: Of 97,174 patients, 1,518 (1.6%) had bacteremia, 1,392 (1.4%) had influenza, and 3,280 (3.3%) had an SSTI. There was no identifiable temperature threshold that provided adequate sensitivity and specificity for bacteremia. Only 45% of patients with bacteremia had a maximum temperature ≥ 100.4˚F (38˚C). Temperature showed a U-shaped relationship with bacteremia with highest risk above 103˚F (39.4˚C). Positive likelihood ratios for influenza and SSTI also increased with temperature but showed a threshold effect at ≥ 101.0 ˚F (38.3˚C). The effect of temperature was similar but blunted for patients aged ≥ 65 years, who frequently lacked fever despite bacteremia. CONCLUSIONS: The majority of bacteremic patients had maximum temperatures below 100.4 ˚F (38.0˚C) and positive likelihood ratios for bacteremia increased with high temperatures above the traditional definition of fever. Efforts to predict bacteremia should incorporate temperature as a continuous variable.

Patient Perspectives on Self-Monitoring of Blood Glucose When not Using Insulin: a Cross-sectional Survey.

BACKGROUND: Professional societies have recommended against use of self-monitoring blood glucose (SMBG) in non-insulin-treated type 2 diabetes (NITT2D) to control blood sugar levels, but patients are still monitoring. OBJECTIVE: To understand patients' motivation to monitor their blood sugar, and whether they would stop if their physician suggested it. DESIGN: Cross-sectional in-person and electronic survey conducted between 2018 and 2020. PARTICIPANTS: Adults with type 2 diabetes not using insulin who self-monitor their blood sugar. MAIN MEASURES: The survey included questions about frequency and reason for using SMBG, and the impact of SMBG on quality of life and worry. It also asked, "If your doctor said you could stop checking your blood sugar, would you?" We categorized patients based on whether they would stop. To identify the characteristics independently associated with desire to stop SMBG, we performed a logistic regression using backward stepwise selection. KEY RESULTS: We received 458 responses. The common reasons for using SMBG included the doctor wanted the patient to check (67%), desire to see the number (65%), and desire to see if their medications were working (61%). Forty-eight percent of respondents stated that using SMBG reduced their worry about their diabetes and 61% said it increased their quality of life. Fifty percent would stop using SMBG if given permission. In the regression model, respondents who said that they check their blood sugar levels because "I was told to" were more likely to want to stop (AOR: 1.69, 95%CI: 1.11, 2.58). Those that used SMBG due to habit and to understand their diabetes better had lower odds of wanting to stop (AOR: 0.33, 95%CI: 0.18-0.62; AOR: 0.60, 95%CI: 0.39-0.93, respectively). CONCLUSIONS: Primary care physicians should discuss patients' reasons for using SMBG and offer them the option of discontinuing.

Treatment of Patients with Prediabetes in a Primary Care Setting 2011-2018: an Observational Study.

BACKGROUND: Over one third of American adults are at high risk for developing diabetes, which can be delayed or prevented using interventions such as medical nutrition therapy (MNT) or metformin. Physicians' self-reported rates of prediabetes treatment are improving, but patterns of actual referral, prescription, and MNT visits are unknown. OBJECTIVE: To characterize treatment of prediabetes in primary care. DESIGN: We conducted a retrospective cohort study using electronic health record data. We described patterns of treatment and used multivariable logistic regression to evaluate the association of patient factors and PCP-specific treatment rate with patient treatment. PATIENTS: We included overweight or obese outpatients who had a first prediabetes-range hemoglobin A1c (HbA1c) during 2011-2018 and had primary care provider (PCP) follow-up within a year. MAIN MEASURES: We collected patient characteristics and the following treatments: metformin prescription; referral to MNT, diabetes education, endocrinology, or bariatric medicine; and MNT visit. We did not capture within-visit physician counseling. KEY RESULTS: Of 16,713 outpatients with prediabetes, 20.4% received treatment, including metformin prescriptions (7.8%) and MNT referrals (11.3%), but only 7.4% of referred patients completed a MNT visit. The strongest predictor of treatment was the patient's PCP's treatment rate. Some PCPs never treated prediabetes, but two treated more than half of their patients; 62% had no patients complete a MNT visit. Being younger or female and having higher body mass index or HbA1c were also positively associated with treatment. Compared to white patients, black patients were more likely to receive MNT referral and less likely to receive metformin. CONCLUSIONS: Almost 80% of patients with new prediabetes never received treatment, and those who did receive referrals had very poor visit completion. Treatment rates appear to reflect provider rather than patient preferences.

Impact of Embedding a Venous Thromboembolism Risk Assessment Model in the Electronic Health Record Versus Usual Care: A Cluster-Randomized Trial.

BACKGROUND: There are multiple risk assessment models (RAMs) for venous thromboembolism prophylaxis, but it is unknown whether they increase appropriate prophylaxis. METHODS: To determine the impact of a RAM embedded in the electronic health record, we conducted a stepped-wedge hospital-level cluster-randomized trial conducted from October 1, 2017 to February 28, 2019 at 10 Cleveland Clinic hospitals. We included consecutive general medical patients aged 18 years or older. Patients were excluded if they had a contraindication to prophylaxis, including anticoagulation for another condition, acute bleeding, or comfort-only care. A RAM was embedded in the general admission order set and physicians were encouraged to use it. The decisions to use the RAM and act on the results were reserved to the treating physician. The primary outcome was the percentage of patients receiving appropriate prophylaxis (high-risk patients with pharmacological thromboprophylaxis plus low-risk patients without prophylaxis) within 48 hours of hospitalization. Secondary outcomes included total patients receiving prophylaxis, venous thromboembolism among high-risk patients at 14 and 45 days, major bleeding, heparin-induced thrombocytopenia, and length of stay. Mixed-effects models were used to analyze the study outcomes. RESULTS: A total of 26 506 patients (mean age, 61; 52% female; 73% White) were analyzed, including 11 134 before and 15 406 after implementation of the RAM. After implementation, the RAM was used for 24% of patients, and the percentage of patients receiving appropriate prophylaxis increased from 43.1% to 48.8% (adjusted odds ratio, 1.11 [1.00-1.23]), while overall prophylaxis use decreased from 73.5% to 65.2% (adjusted odds ratio, 0.87 [0.78-0.97]). Rates of venous thromboembolism among high-risk patients (adjusted odds ratio, 0.72 [0.38-1.36]), rates of bleeding and heparin-induced thrombocytopenia (adjusted odds ratio, 0.19 [0.02-1.47]), and length of stay were unchanged. CONCLUSIONS: Implementation of a RAM for venous thromboembolism increased appropriate prophylaxis use, but the RAM was used for a minority of patients. REGISTRATION: URL: https://www.clinicaltrials.gov/study/NCT03243708?term=nct03243708&rank=1; Unique identifier: NCT03243708.

Social Behaviors Associated With a Positive COVID-19 Test Result.

Objective To compare the social behaviors of individuals who were tested positive for COVID-19 relative to non-infected individuals.   Methods We sent COVID positive cases and age/gender-matched controls a survey regarding their social behaviors via MyChart (online patient portal). We called cases if they did not complete the electronic survey within two days. Data were collected from May to June 2020. Survey responses for cases without close contact and controls were compared using Pearson chi-square or Fisher's exact tests as appropriate.   Results A total of 339 participants completed the survey (113 cases, 226 controls); 45 (40%) cases had known contact with COVID-19. Cases were more likely to have recently traveled (4% vs. 0%, p = 0.01) or to work outside the home (40% vs. 25%, p = 0.02). There was no difference in the rates of attending private or public gatherings, mask/glove use, hand-washing, cleaning surfaces, and cleaning mail/groceries between cases and controls.   Conclusions Sixty percent of cases had no known contact with COVID-19, indicating ongoing community transmission and underlining the importance of contact tracing. The greater percentage of cases who work outside the home provides further evidence for social distancing and remote telework when possible.

Changes in Social Behavior Over Time During the COVID-19 Pandemic.

Public health recommendations aimed at limiting the spread of SARS-CoV-2 have encouraged social distancing and masks as economies across the United States re-open. Understanding adherence to these guidelines will inform further efforts to reduce transmission. In this repeated cross-sectional survey study, we describe changes in social behavior in Ohio during periods of declining and rising cases. While essential activities remained consistent over time, more individuals attended gatherings of 10 or more people as cases rose, particularly in the 18-29 age group. A majority of individuals wore masks. It appears necessary to continue limiting gatherings and encourage mask-wearing, particularly among younger groups.