Sudden cardiac arrest during the COVID-19 pandemic: A two-year prospective evaluation in a North American community.

BACKGROUND: Early during the coronavirus disease 2019 (COVID-19) pandemic, higher sudden cardiac arrest (SCA) incidence and lower survival rates were reported. However, ongoing effects on SCA during the evolving pandemic have not been evaluated. OBJECTIVE: The purpose of this study was to assess the impact of COVID-19 on SCA during 2 years of the pandemic. METHODS: In a prospective study of Ventura County, California (2020 population 843,843; 44.1% Hispanic), we compared SCA incidence and outcomes during the first 2 years of the COVID-19 pandemic to the prior 4 years. RESULTS: Of 2222 out-of-hospital SCA cases identified, 907 occurred during the pandemic (March 2020 to February 2022) and 1315 occurred prepandemic (March 2016 to February 2020). Overall age-standardized annual SCA incidence increased from 39 per 100,000 (95% confidence [CI] 37-41) prepandemic to 54 per 100,000 (95% CI 50-57; P <.001) during the pandemic. Among Hispanics, incidence increased by 77%, from 38 per 100,000 (95% CI 34-43) to 68 per 100,000 (95% CI 60-76; P <.001). Among non-Hispanics, incidence increased by 26%, from 39 per 100,000 (95% CI 37-42; P <.001) to 50 per 100,000 (95% CI 46-54). SCA incidence rates closely tracked COVID-19 infection rates. During the pandemic, SCA survival was significantly reduced (15% to 10%; P <.001), and Hispanics were less likely than non-Hispanics to receive bystander cardiopulmonary resuscitation (45% vs 55%; P = .005) and to present with shockable rhythm (15% vs 24%; P = .003). CONCLUSION: Overall SCA rates remained consistently higher and survival outcomes consistently lower, with exaggerated effects during COVID infection peaks. This longer evaluation uncovered higher increases in SCA incidence among Hispanics, with worse resuscitation profiles. Potential ethnicity-specific barriers to acute SCA care warrant urgent evaluation and intervention.

Experience With Hydroxychloroquine and Azithromycin in the Coronavirus Disease 2019 Pandemic: Implications for QT Interval Monitoring.

Background Despite a lack of clinical evidence, hydroxychloroquine and azithromycin are being administered widely to patients with verified or suspected coronavirus disease 2019 (COVID-19). Both drugs may increase risk of lethal arrhythmias associated with QT interval prolongation. Methods and Results We analyzed a case series of COVID-19-positive/suspected patients admitted between February 1, 2020, and April 4, 2020, who were treated with azithromycin, hydroxychloroquine, or a combination of both drugs. We evaluated baseline and postmedication QT interval (corrected QT interval [QTc]; Bazett) using 12-lead ECGs. Critical QTc prolongation was defined as follows: (1) maximum QTc ≥500 ms (if QRS <120 ms) or QTc ≥550 ms (if QRS ≥120 ms) and (2) QTc increase of ≥60 ms. Tisdale score and Elixhauser comorbidity index were calculated. Of 490 COVID-19-positive/suspected patients, 314 (64%) received either/both drugs and 98 (73 COVID-19 positive and 25 suspected) met study criteria (age, 62±17 years; 61% men). Azithromycin was prescribed in 28%, hydroxychloroquine in 10%, and both in 62%. Baseline mean QTc was 448±29 ms and increased to 459±36 ms (P=0.005) with medications. Significant prolongation was observed only in men (18±43 ms versus -0.2±28 ms in women; P=0.02). A total of 12% of patients reached critical QTc prolongation. Changes in QTc were highest with the combination compared with either drug, with much greater prolongation with combination versus azithromycin (17±39 ms versus 0.5±40 ms; P=0.07). No patients manifested torsades de pointes. Conclusions Overall, 12% of patients manifested critical QTc prolongation, and the combination caused greater prolongation than either drug alone. The balance between uncertain benefit and potential risk when treating COVID-19 patients should be carefully assessed.

A Machine Learning Algorithm Predicts Duration of hospitalization in COVID-19 patients.

The COVID-19 pandemic has placed unprecedented strain on the healthcare system, particularly hospital bed capacity in the setting of large variations in patient length of stay (LOS). Using electronic health record data from 966 COVID-19 patients at a large academic medical center, we developed three machine learning algorithms to predict the likelihood of prolonged LOS, defined as >8 days. The models included 353 variables and were trained on 80% of the cohort, with 20% used for model validation. The three models were created on hospital days 1, 2 and 3, each including information available at or before that point in time. The models' predictive capabilities improved sequentially over time, reaching an accuracy of 0.765, with an AUC of 0.819 by day 3. These models, developed using readily available data, may help hospital systems prepare for bed capacity needs, and help clinicians counsel patients on their likelihood of prolonged hospitalization.

Cardiac arrhythmias in hospitalized patients with COVID-19: A prospective observational study in the western United States.

Arrhythmias have been reported frequently in COVID-19 patients, but the incidence and nature have not been well characterized. Patients admitted with COVID-19 and monitored by telemetry were prospectively enrolled in the study. Baseline characteristics, hospital course, treatment and complications were collected from the patients' medical records. Telemetry was monitored to detect the incidence of cardiac arrhythmias. The incidence and types of cardiac arrhythmias were analyzed and compared between survivors and non-survivors. Among 143 patients admitted with telemetry monitoring, overall in-hospital mortality was 25.2% (36/143 patients) during the period of observation (mean follow-up 23.7 days). Survivors were less tachycardic on initial presentation (heart rate 90.6 ± 19.6 vs. 99.3 ± 23.1 bpm, p = 0.030) and had lower troponin (peak troponin 0.03 vs. 0.18 ng/ml. p = 0.004), C-reactive protein (peak C-reactive protein 97 vs. 181 mg/dl, p = 0.029), and interleukin-6 levels (peak interleukin-6 30 vs. 246 pg/ml, p = 0.003). Sinus tachycardia, the most common arrhythmia (detected in 39.9% [57/143] of patients), occurred more frequently in non-survivors (58.3% vs. 33.6% in survivors, p = 0.009). Premature ventricular complexes occurred in 28.7% (41/143), and non-sustained ventricular tachycardia in 15.4% (22/143) of patients, with no difference between survivors and non-survivors. Sustained ventricular tachycardia and ventricular fibrillation were not frequent (seen only in 1.4% and 0.7% of patients, respectively). Contrary to reports from other regions, overall mortality was higher and ventricular arrhythmias were infrequent in this hospitalized and monitored COVID-19 population. Either disease or management-related factors could explain this divergence of clinical outcomes, and should be urgently investigated.

Out-of-Hospital Cardiac Arrest Response and Outcomes During the COVID-19 Pandemic.

OBJECTIVES: The purpose of this study was to evaluate the potential impact of the coronavirus disease-2019 (COVID-19) pandemic on out-of-hospital cardiac arrest (OHCA) responses and outcomes in 2 U.S. communities with relatively low infection rates. BACKGROUND: Studies in areas with high COVID-19 infection rates indicate that the pandemic has had direct and indirect effects on community responses to OHCA and negative impacts on survival. Data from areas with lower infection rates are lacking. METHODS: Cases of OHCA in Multnomah County, Oregon, and Ventura County, California, with attempted resuscitation by emergency medical services (EMS) from March 1 to May 31, 2020, and from March 1 to May 31, 2019, were evaluated. RESULTS: In a comparison of 231 OHCA in 2019 to 278 in 2020, the proportion of cases receiving bystander cardiopulmonary resuscitation (CPR) was lower in 2020 (61% to 51%, respectively; p = 0.02), and bystander use of automated external defibrillators (AEDs) declined (5% to 1%, respectively; p = 0.02). EMS response time increased (6.6 ± 2.0 min to 7.6 ± 3.0 min, respectively; p < 0.001), and fewer OHCA cases survived to hospital discharge (14.7% to 7.9%, respectively; p = 0.02). Incidence rates did not change significantly (p > 0.07), and coronavirus infection rates were low (Multnomah County, 143/100,000; Ventura County, 127/100,000 as of May 31) compared to rates of ∼1,600 to 3,000/100,000 in the New York City region at that time. CONCLUSIONS: The community response to OHCA was altered from March to May 2020, with less bystander CPR, delays in EMS response time, and reduced survival from OHCA. These results highlight the pandemic's indirect negative impact on OHCA, even in communities with relatively low incidence of COVID-19 infection, and point to potential opportunities for countering the impact.

Pre-existing traits associated with Covid-19 illness severity.

IMPORTANCE: Certain individuals, when infected by SARS-CoV-2, tend to develop the more severe forms of Covid-19 illness for reasons that remain unclear. OBJECTIVE: To determine the demographic and clinical characteristics associated with increased severity of Covid-19 infection. DESIGN: Retrospective observational study. We curated data from the electronic health record, and used multivariable logistic regression to examine the association of pre-existing traits with a Covid-19 illness severity defined by level of required care: need for hospital admission, need for intensive care, and need for intubation. SETTING: A large, multihospital healthcare system in Southern California. PARTICIPANTS: All patients with confirmed Covid-19 infection (N = 442). RESULTS: Of all patients studied, 48% required hospitalization, 17% required intensive care, and 12% required intubation. In multivariable-adjusted analyses, patients requiring a higher levels of care were more likely to be older (OR 1.5 per 10 years, P<0.001), male (OR 2.0, P = 0.001), African American (OR 2.1, P = 0.011), obese (OR 2.0, P = 0.021), with diabetes mellitus (OR 1.8, P = 0.037), and with a higher comorbidity index (OR 1.8 per SD, P<0.001). Several clinical associations were more pronounced in younger compared to older patients (Pinteraction<0.05). Of all hospitalized patients, males required higher levels of care (OR 2.5, P = 0.003) irrespective of age, race, or morbidity profile. CONCLUSIONS AND RELEVANCE: In our healthcare system, greater Covid-19 illness severity is seen in patients who are older, male, African American, obese, with diabetes, and with greater overall comorbidity burden. Certain comorbidities paradoxically augment risk to a greater extent in younger patients. In hospitalized patients, male sex is the main determinant of needing more intensive care. Further investigation is needed to understand the mechanisms underlying these findings.