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      Trisomy 21 and COVID-19 in Pediatric Patients

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          Abstract

          We present 4 pediatric patients with trisomy 21 (T21) and associated comorbidities who developed COVID-19 requiring hospitalization. A review of the literature revealed that co-morbidities associated with T21 may predispose patients to severe disease. Children with T21 should be considered high risk and monitored carefully if infected with SARS-CoV-2. Children with underlying health conditions, including those with respiratory conditions or who are immunocompromised, continue to be at risk of severe COVID-19. We present 4 cases of SARS-CoV-2 confirmed by PCR in patients of another possible at-risk group: children with trisomy 21 (T21) and associated co-morbidities (Table ). All four patients had COVID-19 disease requiring hospitalization, and one patient had severe disease. None has been reported previously. Of note, Cases 1, 2, and 4 are part of a COVID-19 registry managed by St. Jude Children's Research Hospital, TN. However, at the time of this submission, no data have been published from this registry. Table 1 Characteristics of patients with trisomy 21 and COVID-19 Test / Case 1 2 3 4 Co-Morbidities OSA, Obesity, CHD CHD, OSA, Dysphagia OSA, CHD, dysphagia, epilepsy, hypothyroid, recurrent aspiration pneumonia OSA, CHD, obesity Type of CHD Ventricular septal defect s/p repair Tetralogy of Fallot, s/p repair Atrial septal defect s/p repair Atrial septal defect s/p repair Pulmonary Hypertension No Yes No No Symptomatic System Respiratory, ENT Respiratory Respiratory, GI GI WB x 103 cells/μL 4.15 9.14 4.3 1.46 CRP mg/dL 1.3 1.3 6.2 1.2 Procalcitonin ng/mL 0.10 1.08 - <0.10 Ferritin ng/mL 527 - - 117 D-Dimer mcg/mL 2.26 - 3.97 - Symptomatic Days PTA 8 1 3 1 Days Hospitalized 23 7 4 2 Max Resp Support Mechanical Vent HFNC NC Baseline Support BMI 35.38 15.6 22.2 28.3 Therapy HcQ (3 days only), Toci, Rem Key OSA obstructive sleep apnea; CHD congenital heart disease; PHTN pulmonary hypertension; HFNC high flow nasal cannula; NC nasal cannula; HcQ hydroxychloroquine; Rem remdesivir; Toci tocilizumab Case 1 A 17-year-old male with T21, congenital heart disease (CHD), and obesity presented to our emergency department (ED) after five days of severe throat pain, non-productive cough, and poor oral intake secondary to pharyngitis, but without breathing difficulty. He was febrile but had a normal respiratory examination, including normal work of breathing. A rapid strep test and SARS-CoV-2 PCR were sent; both were positive. Due to overall mild symptoms, he was discharged home to receive amoxicillin for streptococcal pharyngitis. Three days later, he returned to the ED because of dehydration, fever, and concern for increasingly difficult breathing with mild supraclavicular retractions. His chest radiograph showed bilateral lower lobe reticulonodular opacities with focal airspace opacities in the left-mid-to-lower lobe and he was hospitalized for further care. On hospital day of admission (D)1, he had intermittent oxygen desaturation to 85% while asleep which resolved with re-positioning. On D2, he required 2L oxygen by nasal cannula for labored work of breathing, tachypnea, accessory muscle use, and persistent hypoxemia. Hydroxychloroquine was initiated while awaiting approval of emergency use of investigational new drug for remdesivir. On D4, he was transferred to the intensive care unit due to increasing tachypnea and need for supplemental oxygen and was started on IV remdesivir (200 mg IV loading dose on day 1, then 100 mg IV daily on days 2-10). Hydroxychloroquine was discontinued. Intubation was required on D5. On D10, he had an increase in CRP from 3.2 mg/dL at admission to 7 mg/dL and procalcitonin from 0.14 at admission to 2.43, as well as new onset of hypotension to 60s/40s mm Hg. To combat his hyperinflammatory state, tocilizumab was started. His CRP and procalcitonin decreased after a single dose to 2.7 mg/dL and 1.25, respectively. On D14, he was extubated, maintained on high-flow oxygen by nasal cannula and was no longer febrile. After extubation, he required continuous positive airway pressure (CPAP) at night time for probable obstructive sleep apnea (OSA). He was discharged to home on D23 after requiring no oxygen supplementation during the daytime Case 2 A 10-month-old male with T21, CHD, pulmonary hypertension, OSA, and dysphagia was brought to medical attention with a one day history of fever to 38.1 oC, productive cough, and increased work of breathing. On examination he was afebrile, without increased work of breathing; auscultation of his chest revealed clear breath sounds bilaterally. A chest radiograph revealed bilateral perihilar opacities with left retrocardiac opacity. Ceftriaxone was begun IV and he was admitted to the inpatient medical unit. Oxygen requirement increased from his baseline 0.75L O2 via nasal cannula at home (required overnight) to 2L due to intermittent oxygen desaturation to 85%. Symptoms progressively worsened, including increased work of breathing and decreased oxygen saturation, requiring escalation of support by high flow oxygen by nasal cannula. Vancomycin was initiated when he developed fever. On D2, positive SARS-CoV-2 was known and his antibiotics were discontinued. On D4, he was weaned to oxygen by regular flow nasal cannula in the morning and placed back on home O2 of 0.75L overnight. He tolerated being on absence of daytime supplemental O2 on D5 and was discharged tohome. Case 3 A 15-year-old male with T21, OSA, CHD, dysphagia, and recurrent aspiration pneumonia was brought to the ED after two days of cough, one day of fever, and recurrent non-bilious, non-bloody emesis following G-tube feeding. Examination revealed temperature of 38.8 oC and tachycardia, initially with normal oxygen saturation and no increased work of breathing. Oxygen desaturation to 86% ensued and requiring supplementation via nasal cannula; his chest radiograph showed no focal consolidation. During hospital D1 he required escalation of flow to a maximum of 2.5L. On D2, he was re-started on continuous G-tube feedings and subsequently was weaned to room air. On D4, feeding regimen was resumed to home bolus, and he was discharged to home. Case 4 A 14-year-old male with T21, obesity, CHD, and OSA had the acute onset of refusal to eat, abdominal pain, dry cough, and fatigue. He did not have emesis, diarrhea, increased work of breathing or fever, and remained stable on his home settings of CPAP without supplementary oxygen. Per home testing, his blood glucose was 53, and his father brought him to an outside hospital ED for further care. He was given fluids and an anti-emetic and underwent an abdominal CT for continued abdominal pain. Although the abdomen appeared normal on CT, the bases of the lungs showed ill-defined mixed airspace opacities in the lower lobes and inferior aspect of the lingula. SARS-CoV-2 PCR was sent and was positive. He was transferred to our institution for care and monitoring during which time he remained stable without fever, increased work of breathing, or need for supplementary oxygen. He was discharged after one day of hospitalization. Discussion Children with intellectual and developmental disability (IDD), including those with T21, had increased mortality rates from COVID-19 compared with peers without IDD (1). The anatomic, immunologic, and metabolic comorbidities associated with T21, as present in our cases, may increase their risk for severe COVID-19 disease. Children with T21 have abnormal upper airway phenotypic features including macroglossia, midface hypoplasia, choanal stenosis, narrow nasopharynx, enlarged tonsils and adenoids, lingual tonsils, and shortening of the palate, all of which can exacerbate patency of airways during respiratory infections (2). These abnormalities plus generalized hypotonia and increased likelihood of obesity, increase the prevalence of sleep-disordered breathing among this population, with estimated rates varying from 31-79% in children with T21 (3, 4). The onset of sleep-disordered breathing in children with T21 typically occurs at a younger age, after the second to third year of life, compared with children without T21 (3, 4). Children with T21 also have a high rate of congenital heart disease (2). Structural cardiac defects are found in about 40% of children with T21, most commonly seen are atrioventricular septal defects (5). Children with T21 and AVSD more frequently develop pulmonary vascular hypertension compared with those without trisomy (6). For children with T21, the interplay between complicated respiratory and cardiovascular anatomy and pathophysiology likely lead to increased severity and mortality of respiratory infections. Krishnan et al highlighted the interplay between congenital heart disease, pulmonary hypertension, and T21 as it relates to SARS-CoV-2 infection; 60% of patients with pulmonary hypertension and SARS-CoV-2 infection requiring hospitalization also had T21 and AVSD (7). Among our four cases, all patients had repaired congenital heart disease, though only one had pulmonary hypertension. Children with T21 may have abnormal immune function that predisposes them to more severe infections, prolonged lower respiratory tract infections, and increased incidence of acute lung injury (8, 9). Studies have found variations in immune functions in children with T21 including: mild to moderate T- and B-cell lymphopenia, with marked decrease of naive lymphocytes; impaired mitogen-induced T-cell proliferation; reduced specific antibody responses to immunizations; and defects of neutrophil chemotaxis (10). Additionally, the number of CD14/16+ pro-inflammatory monocytes is higher in patients with T21 relative to a low absolute monocyte count (11), exacerbating inflammatory morbidity during infection. Obesity has emerged as a primary risk factor for severe COVID-19 (12). Previous studies estimate an increased prevalence of obesity among children with T21 (13). A meta-analysis by Bertapelli et al found the worldwide prevalence of overweight children with T21 to be 23-70%, with obesity ranging from 0-63% (13). Current studies propose the following hypotheses: increased leptin level thought to be related to leptin resistance and decreased satiety, lower resting energy expenditure and lower physical activity compared with non-T21 youth (14, 15, 16). Increased weight can lead to upper airway obstruction and obstructive sleep apnea, which is compounded by anatomic differences in children with T21. Obesity also can lead to immune dysregulation, increasing the severity of viral disease. Obesity can result in a state of chronic meta-inflammation, which can blunt host’s antiviral response (17). During the 2009 H1N1 pandemic, obesity was associated with increased hospitalization and mortality (17). Children with T21 have hyperactivation of their interferon signaling, ultimately resulting in a hyperinflammatory state (18). For SARS-CoV-2 infection, there is increasing evidence that a hyper-inflammatory response to the virus leads to increased morbidity and mortality (18). Children with T21 may be at increased risk for further up-regulation of pro-inflammatory cytokines during COVID-19. The unique risks of upper and lower respiratory abnormalities, immune defects, increased rates of obesity and sleep disordered breathing all place those with T21 at higher risk for severe disease from respiratory pathogens. It seems prudent to take caution with children and adults with T21 infected with SARS-CoV-2.

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          Hospitalization Rates and Characteristics of Patients Hospitalized with Laboratory-Confirmed Coronavirus Disease 2019 — COVID-NET, 14 States, March 1–30, 2020

          Since SARS-CoV-2, the novel coronavirus that causes coronavirus disease 2019 (COVID-19), was first detected in December 2019 ( 1 ), approximately 1.3 million cases have been reported worldwide ( 2 ), including approximately 330,000 in the United States ( 3 ). To conduct population-based surveillance for laboratory-confirmed COVID-19–associated hospitalizations in the United States, the COVID-19–Associated Hospitalization Surveillance Network (COVID-NET) was created using the existing infrastructure of the Influenza Hospitalization Surveillance Network (FluSurv-NET) ( 4 ) and the Respiratory Syncytial Virus Hospitalization Surveillance Network (RSV-NET). This report presents age-stratified COVID-19–associated hospitalization rates for patients admitted during March 1–28, 2020, and clinical data on patients admitted during March 1–30, 2020, the first month of U.S. surveillance. Among 1,482 patients hospitalized with COVID-19, 74.5% were aged ≥50 years, and 54.4% were male. The hospitalization rate among patients identified through COVID-NET during this 4-week period was 4.6 per 100,000 population. Rates were highest (13.8) among adults aged ≥65 years. Among 178 (12%) adult patients with data on underlying conditions as of March 30, 2020, 89.3% had one or more underlying conditions; the most common were hypertension (49.7%), obesity (48.3%), chronic lung disease (34.6%), diabetes mellitus (28.3%), and cardiovascular disease (27.8%). These findings suggest that older adults have elevated rates of COVID-19–associated hospitalization and the majority of persons hospitalized with COVID-19 have underlying medical conditions. These findings underscore the importance of preventive measures (e.g., social distancing, respiratory hygiene, and wearing face coverings in public settings where social distancing measures are difficult to maintain) † to protect older adults and persons with underlying medical conditions, as well as the general public. In addition, older adults and persons with serious underlying medical conditions should avoid contact with persons who are ill and immediately contact their health care provider(s) if they have symptoms consistent with COVID-19 (https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html) ( 5 ). Ongoing monitoring of hospitalization rates, clinical characteristics, and outcomes of hospitalized patients will be important to better understand the evolving epidemiology of COVID-19 in the United States and the clinical spectrum of disease, and to help guide planning and prioritization of health care system resources. COVID-NET conducts population-based surveillance for laboratory-confirmed COVID-19–associated hospitalizations among persons of all ages in 99 counties in 14 states (California, Colorado, Connecticut, Georgia, Iowa, Maryland, Michigan, Minnesota, New Mexico, New York, Ohio, Oregon, Tennessee, and Utah), distributed across all 10 U.S Department of Health and Human Services regions. § The catchment area represents approximately 10% of the U.S. population. Patients must be residents of a designated COVID-NET catchment area and hospitalized within 14 days of a positive SARS-CoV-2 test to meet the surveillance case definition. Testing is requested at the discretion of treating health care providers. Laboratory-confirmed SARS-CoV-2 is defined as a positive result by any test that has received Emergency Use Authorization for SARS-CoV-2 testing. ¶ COVID-NET surveillance officers in each state identify cases through active review of notifiable disease and laboratory databases and hospital admission and infection control practitioner logs. Weekly age-stratified hospitalization rates are estimated using the number of catchment area residents hospitalized with laboratory-confirmed COVID-19 as the numerator and National Center for Health Statistics vintage 2018 bridged-race postcensal population estimates for the denominator.** As of April 3, 2020, COVID-NET hospitalization rates are being published each week at https://gis.cdc.gov/grasp/covidnet/COVID19_3.html. For each case, trained surveillance officers conduct medical chart abstractions using a standard case report form to collect data on patient characteristics, underlying medical conditions, clinical course, and outcomes. Chart reviews are finalized once patients have a discharge disposition. COVID-NET surveillance was initiated on March 23, 2020, with retrospective case identification of patients admitted during March 1–22, 2020, and prospective case identification during March 23–30, 2020. Clinical data on underlying conditions and symptoms at admission are presented through March 30; hospitalization rates are updated weekly and, therefore, are presented through March 28 (epidemiologic week 13). The COVID-19–associated hospitalization rate among patients identified through COVID-NET for the 4-week period ending March 28, 2020, was 4.6 per 100,000 population (Figure 1). Hospitalization rates increased with age, with a rate of 0.3 in persons aged 0–4 years, 0.1 in those aged 5–17 years, 2.5 in those aged 18–49 years, 7.4 in those aged 50–64 years, and 13.8 in those aged ≥65 years. Rates were highest among persons aged ≥65 years, ranging from 12.2 in those aged 65–74 years to 17.2 in those aged ≥85 years. More than half (805; 54.4%) of hospitalizations occurred among men; COVID-19-associated hospitalization rates were higher among males than among females (5.1 versus 4.1 per 100,000 population). Among the 1,482 laboratory-confirmed COVID-19–associated hospitalizations reported through COVID-NET, six (0.4%) each were patients aged 0–4 years and 5–17 years, 366 (24.7%) were aged 18–49 years, 461 (31.1%) were aged 50–64 years, and 643 (43.4%) were aged ≥65 years. Among patients with race/ethnicity data (580), 261 (45.0%) were non-Hispanic white (white), 192 (33.1%) were non-Hispanic black (black), 47 (8.1%) were Hispanic, 32 (5.5%) were Asian, two (0.3%) were American Indian/Alaskan Native, and 46 (7.9%) were of other or unknown race. Rates varied widely by COVID-NET surveillance site (Figure 2). FIGURE 1 Laboratory-confirmed coronavirus disease 2019 (COVID-19)–associated hospitalization rates,* by age group — COVID-NET, 14 states, † March 1–28, 2020 Abbreviation: COVID-NET = Coronavirus Disease 2019–Associated Hospitalization Surveillance Network. * Number of patients hospitalized with COVID-19 per 100,000 population. † Counties included in COVID-NET surveillance: California (Alameda, Contra Costa, and San Francisco counties); Colorado (Adams, Arapahoe, Denver, Douglas, and Jefferson counties); Connecticut (New Haven and Middlesex counties); Georgia (Clayton, Cobb, DeKalb, Douglas, Fulton, Gwinnett, Newton, and Rockdale counties); Iowa (one county represented); Maryland (Allegany, Anne Arundel, Baltimore, Baltimore City, Calvert, Caroline, Carroll, Cecil, Charles, Dorchester, Frederick, Garrett, Harford, Howard, Kent, Montgomery, Prince George’s, Queen Anne’s, St. Mary’s, Somerset, Talbot, Washington, Wicomico, and Worcester counties); Michigan (Clinton, Eaton, Genesee, Ingham, and Washtenaw counties); Minnesota (Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington counties); New Mexico (Bernalillo, Chaves, Dona Ana, Grant, Luna, San Juan, and Santa Fe counties); New York (Albany, Columbia, Genesee, Greene, Livingston, Monroe, Montgomery, Ontario, Orleans, Rensselaer, Saratoga, Schenectady, Schoharie, Wayne, and Yates counties); Ohio (Delaware, Fairfield, Franklin, Hocking, Licking, Madison, Morrow, Perry, Pickaway and Union counties); Oregon (Clackamas, Multnomah, and Washington counties); Tennessee (Cheatham, Davidson, Dickson, Robertson, Rutherford, Sumner, Williamson, and Wilson counties); and Utah (Salt Lake County). The figure is a bar chart showing laboratory-confirmed COVID-19–associated hospitalization rates, by age group, in 14 states during March 1–28, 2020 according to the Coronavirus Disease 2019–Associated Hospitalization Surveillance Network. FIGURE 2 Laboratory-confirmed coronavirus disease 2019 (COVID-19)–associated hospitalization rates,* by surveillance site † — COVID-NET, 14 states, March 1–28, 2020 Abbreviation: COVID-NET = Coronavirus Disease 2019–Associated Hospitalization Surveillance Network. * Number of patients hospitalized with COVID-19 per 100,000 population. † Counties included in COVID-NET surveillance: California (Alameda, Contra Costa, and San Francisco counties); Colorado (Adams, Arapahoe, Denver, Douglas, and Jefferson counties); Connecticut (New Haven and Middlesex counties); Georgia (Clayton, Cobb, DeKalb, Douglas, Fulton, Gwinnett, Newton, and Rockdale counties); Iowa (one county represented); Maryland (Allegany, Anne Arundel, Baltimore, Baltimore City, Calvert, Caroline, Carroll, Cecil, Charles, Dorchester, Frederick, Garrett, Harford, Howard, Kent, Montgomery, Prince George’s, Queen Anne’s, St. Mary’s, Somerset, Talbot, Washington, Wicomico, and Worcester counties); Michigan (Clinton, Eaton, Genesee, Ingham, and Washtenaw counties); Minnesota (Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington counties); New Mexico (Bernalillo, Chaves, Dona Ana, Grant, Luna, San Juan, and Santa Fe counties); New York (Albany, Columbia, Genesee, Greene, Livingston, Monroe, Montgomery, Ontario, Orleans, Rensselaer, Saratoga, Schenectady, Schoharie, Wayne, and Yates counties); Ohio (Delaware, Fairfield, Franklin, Hocking, Licking, Madison, Morrow, Perry, Pickaway and Union counties); Oregon (Clackamas, Multnomah, and Washington counties); Tennessee (Cheatham, Davidson, Dickson, Robertson, Rutherford, Sumner, Williamson, and Wilson counties); and Utah (Salt Lake County). The figure is a bar chart showing laboratory-confirmed COVID-19–associated hospitalization rates, by surveillance site, in 14 states during March 1–28, 2020 according to the Coronavirus Disease 2019–Associated Hospitalization Surveillance Network. During March 1–30, underlying medical conditions and symptoms at admission were reported through COVID-NET for approximately 180 (12.1%) hospitalized adults (Table); 89.3% had one or more underlying conditions. The most commonly reported were hypertension (49.7%), obesity (48.3%), chronic lung disease (34.6%), diabetes mellitus (28.3%), and cardiovascular disease (27.8%). Among patients aged 18–49 years, obesity was the most prevalent underlying condition, followed by chronic lung disease (primarily asthma) and diabetes mellitus. Among patients aged 50–64 years, obesity was most prevalent, followed by hypertension and diabetes mellitus; and among those aged ≥65 years, hypertension was most prevalent, followed by cardiovascular disease and diabetes mellitus. Among 33 females aged 15–49 years hospitalized with COVID-19, three (9.1%) were pregnant. Among 167 patients with available data, the median interval from symptom onset to admission was 7 days (interquartile range [IQR] = 3–9 days). The most common signs and symptoms at admission included cough (86.1%), fever or chills (85.0%), and shortness of breath (80.0%). Gastrointestinal symptoms were also common; 26.7% had diarrhea, and 24.4% had nausea or vomiting. TABLE Underlying conditions and symptoms among adults aged ≥18 years with coronavirus disease 2019 (COVID-19)–associated hospitalizations — COVID-NET, 14 states,* March 1–30, 2020† Underlying condition Age group (yrs), no./total no. (%) Overall 18–49 50–64 ≥65 years Any underlying condition 159/178 (89.3) 41/48 (85.4) 51/59 (86.4) 67/71 (94.4) Hypertension 79/159 (49.7) 7/40 (17.5) 27/57 (47.4) 45/62 (72.6) Obesity§ 73/151 (48.3) 23/39 (59.0) 25/51 (49.0) 25/61 (41.0) Chronic metabolic disease¶ 60/166 (36.1) 10/46 (21.7) 21/56 (37.5) 29/64 (45.3)    Diabetes mellitus 47/166 (28.3) 9/46 (19.6) 18/56 (32.1) 20/64 (31.3) Chronic lung disease 55/159 (34.6) 16/44 (36.4) 15/53 (28.3) 24/62 (38.7)    Asthma 27/159 (17.0) 12/44 (27.3) 7/53 (13.2) 8/62 (12.9)    Chronic obstructive pulmonary disease 17/159 (10.7) 0/44 (0.0) 3/53 (5.7) 14/62 (22.6) Cardiovascular disease** 45/162 (27.8) 2/43 (4.7) 11/56 (19.6) 32/63 (50.8)    Coronary artery disease 23/162 (14.2) 0/43 (0.0) 7/56 (12.5) 16/63 (25.4)    Congestive heart failure 11/162 (6.8) 2/43 (4.7) 3/56 (5.4) 6/63 (9.5) Neurologic disease 22/157 (14.0) 4/42 (9.5) 4/55 (7.3) 14/60 (23.3) Renal disease 20/153 (13.1) 3/41 (7.3) 2/53 (3.8) 15/59 (25.4) Immunosuppressive condition 15/156 (9.6) 5/43 (11.6) 4/54 (7.4) 6/59 (10.2) Gastrointestinal/Liver disease 10/152 (6.6) 4/42 (9.5) 0/54 (0.0) 6/56 (10.7) Blood disorder 9/156 (5.8) 1/43 (2.3) 1/55 (1.8) 7/58 (12.1) Rheumatologic/Autoimmune disease 3/154 (1.9) 1/42 (2.4) 0/54 (0.0) 2/58 (3.4) Pregnancy†† 3/33 (9.1) 3/33 (9.1) N/A N/A Symptom §§ Cough 155/180 (86.1) 43/47 (91.5) 54/60 (90.0) 58/73 (79.5) Fever/Chills 153/180 (85.0) 38/47 (80.9) 53/60 (88.3) 62/73 (84.9) Shortness of breath 144/180 (80.0) 40/47 (85.1) 50/60 (83.3) 54/73 (74.0) Myalgia 62/180 (34.4) 20/47 (42.6) 23/60 (38.3) 19/73 (26.0) Diarrhea 48/180 (26.7) 10/47 (21.3) 17/60 (28.3) 21/73 (28.8) Nausea/Vomiting 44/180 (24.4) 12/47 (25.5) 17/60 (28.3) 15/73 (20.5) Sore throat 32/180 (17.8) 8/47 (17.0) 13/60 (21.7) 11/73 (15.1) Headache 29/180 (16.1) 10/47 (21.3) 12/60 (20.0) 7/73 (9.6) Nasal congestion/Rhinorrhea 29/180 (16.1) 8/47 (17.0) 13/60 (21.7) 8/73 (11.0) Chest pain 27/180 (15.0) 9/47 (19.1) 13/60 (21.7) 5/73 (6.8) Abdominal pain 15/180 (8.3) 6/47 (12.8) 6/60 (10.0) 3/73 (4.1) Wheezing 12/180 (6.7) 3/47 (6.4) 2/60 (3.3) 7/73 (9.6) Altered mental status/Confusion 11/180 (6.1) 3/47 (6.4) 2/60 (3.3) 6/73 (8.2) Abbreviations: COVID-NET = Coronavirus Disease 2019–Associated Hospitalization Surveillance Network; N/A = not applicable. * Counties included in COVID-NET surveillance: California (Alameda, Contra Costa, and San Francisco counties); Colorado (Adams, Arapahoe, Denver, Douglas, and Jefferson counties); Connecticut (New Haven and Middlesex counties); Georgia (Clayton, Cobb, DeKalb, Douglas, Fulton, Gwinnett, Newton, and Rockdale counties); Iowa (one county represented); Maryland (Allegany, Anne Arundel, Baltimore, Baltimore City, Calvert, Caroline, Carroll, Cecil, Charles, Dorchester, Frederick, Garrett, Harford, Howard, Kent, Montgomery, Prince George’s, Queen Anne’s, St. Mary’s, Somerset, Talbot, Washington, Wicomico, and Worcester counties); Michigan (Clinton, Eaton, Genesee, Ingham, and Washtenaw counties); Minnesota (Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington counties); New Mexico (Bernalillo, Chaves, Dona Ana, Grant, Luna, San Juan, and Santa Fe counties); New York (Albany, Columbia, Genesee, Greene, Livingston, Monroe, Montgomery, Ontario, Orleans, Rensselaer, Saratoga, Schenectady, Schoharie, Wayne, and Yates counties); Ohio (Delaware, Fairfield, Franklin, Hocking, Licking, Madison, Morrow, Perry, Pickaway and Union counties); Oregon (Clackamas, Multnomah, and Washington counties); Tennessee (Cheatham, Davidson, Dickson, Robertson, Rutherford, Sumner, Williamson, and Wilson counties); and Utah (Salt Lake County). † COVID-NET included data for one child aged 5–17 years with underlying medical conditions and symptoms at admission; data for this child are not included in this table. This child was reported to have chronic lung disease (asthma). Symptoms included fever, cough, gastrointestinal symptoms, shortness of breath, chest pain, and a sore throat on admission. § Obesity is defined as calculated body mass index (BMI) ≥30 kg/m2, and if BMI is missing, by International Classification of Diseases discharge diagnosis codes. Among 73 patients with obesity, 51 (69.9%) had obesity defined as BMI 30–<40 kg/m2, and 22 (30.1%) had severe obesity defined as BMI ≥40 kg/m2. ¶ Among the 60 patients with chronic metabolic disease, 45 had diabetes mellitus only, 13 had thyroid dysfunction only, and two had diabetes mellitus and thyroid dysfunction. ** Cardiovascular disease excludes hypertension. †† Restricted to women aged 15–49 years. §§ Symptoms were collected through review of admission history and physical exam notes in the medical record and might be determined by subjective or objective findings. In addition to the symptoms in the table, the following less commonly reported symptoms were also noted for adults with information on symptoms (180): hemoptysis/bloody sputum (2.2%), rash (1.1%), conjunctivitis (0.6%), and seizure (0.6%). Discussion During March 1–28, 2020, the overall laboratory-confirmed COVID-19–associated hospitalization rate was 4.6 per 100,000 population; rates increased with age, with the highest rates among adults aged ≥65 years. Approximately 90% of hospitalized patients identified through COVID-NET had one or more underlying conditions, the most common being obesity, hypertension, chronic lung disease, diabetes mellitus, and cardiovascular disease. Using the existing infrastructure of two respiratory virus surveillance platforms, COVID-NET was implemented to produce robust, weekly, age-stratified hospitalization rates using standardized data collection methods. These data are being used, along with data from other surveillance platforms (https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview.html), to monitor COVID-19 disease activity and severity in the United States. During the first month of surveillance, COVID-NET hospitalization rates ranged from 0.1 per 100,000 population in persons aged 5–17 years to 17.2 per 100,000 population in adults aged ≥85 years, whereas cumulative influenza hospitalization rates during the first 4 weeks of each influenza season (epidemiologic weeks 40–43) over the past 5 seasons have ranged from 0.1 in persons aged 5–17 years to 2.2–5.4 in adults aged ≥85 years ( 6 ). COVID-NET rates during this first 4-week period of surveillance are preliminary and should be interpreted with caution; given the rapidly evolving nature of the COVID-19 pandemic, rates are expected to increase as additional cases are identified and as SARS-CoV-2 testing capacity in the United States increases. In the COVID-NET catchment population, approximately 49% of residents are male and 51% of residents are female, whereas 54% of COVID-19-associated hospitalizations occurred in males and 46% occurred in females. These data suggest that males may be disproportionately affected by COVID-19 compared with females. Similarly, in the COVID-NET catchment population, approximately 59% of residents are white, 18% are black, and 14% are Hispanic; however, among 580 hospitalized COVID-19 patients with race/ethnicity data, approximately 45% were white, 33% were black, and 8% were Hispanic, suggesting that black populations might be disproportionately affected by COVID-19. These findings, including the potential impact of both sex and race on COVID-19-associated hospitalization rates, need to be confirmed with additional data. Most of the hospitalized patients had underlying conditions, some of which are recognized to be associated with severe COVID-19 disease, including chronic lung disease, cardiovascular disease, diabetes mellitus ( 5 ). COVID-NET does not collect data on nonhospitalized patients; thus, it was not possible to compare the prevalence of underlying conditions in hospitalized versus nonhospitalized patients. Many of the documented underlying conditions among hospitalized COVID-19 patients are highly prevalent in the United States. According to data from the National Health and Nutrition Examination Survey, hypertension prevalence among U.S. adults is 29% overall, ranging from 7.5%–63% across age groups ( 7 ), and age-adjusted obesity prevalence is 42% (range across age groups = 40%–43%) ( 8 ). Among hospitalized COVID-19 patients, hypertension prevalence was 50% (range across age groups = 18%–73%), and obesity prevalence was 48% (range across age groups = 41%–59%). In addition, the prevalences of several underlying conditions identified through COVID-NET were similar to those for hospitalized influenza patients identified through FluSurv-NET during influenza seasons 2014–15 through 2018–19: 41%–51% of patients had cardiovascular disease (excluding hypertension), 39%–45% had chronic metabolic disease, 33%–40% had obesity, and 29%–31% had chronic lung disease ( 6 ). Data on hypertension are not collected by FluSurv-NET. Among women aged 15–49 years hospitalized with COVID-19 and identified through COVID-NET, 9% were pregnant, which is similar to an estimated 9.9% of the general population of women aged 15–44 years who are pregnant at any given time based on 2010 data. †† Similar to other reports from the United States ( 9 ) and China ( 1 ), these findings indicate that a high proportion of U.S. patients hospitalized with COVID-19 are older and have underlying medical conditions. The findings in this report are subject to at least three limitations. First, hospitalization rates by age and COVID-NET site are preliminary and might change as additional cases are identified from this surveillance period. Second, whereas minimum case data to produce weekly age-stratified hospitalization rates are usually available within 7 days of case identification, availability of detailed clinical data are delayed because of the need for medical chart abstractions. As of March 30, chart abstractions had been conducted for approximately 200 COVID-19 patients; the frequency and distribution of underlying conditions during this time might change as additional data become available. Clinical course and outcomes will be presented once the number of cases with complete medical chart abstractions are sufficient; many patients are still hospitalized at the time of this report. Finally, testing for SARS-CoV-2 among patients identified through COVID-NET is performed at the discretion of treating health care providers, and testing practices and capabilities might vary widely across providers and facilities. As a result, underascertainment of cases in COVID-NET is likely. Additional data on testing practices related to SARS-CoV-2 will be collected in the future to account for underascertainment using described methods ( 10 ). Early data from COVID-NET suggest that COVID-19–associated hospitalizations in the United States are highest among older adults, and nearly 90% of persons hospitalized have one or more underlying medical conditions. These findings underscore the importance of preventive measures (e.g., social distancing, respiratory hygiene, and wearing face coverings in public settings where social distancing measures are difficult to maintain) to protect older adults and persons with underlying medical conditions. Ongoing monitoring of hospitalization rates, clinical characteristics, and outcomes of hospitalized patients will be important to better understand the evolving epidemiology of COVID-19 in the United States and the clinical spectrum of disease, and to help guide planning and prioritization of health care system resources. Summary What is already known about this topic? Population-based rates of laboratory-confirmed coronavirus disease 2019 (COVID-19)–associated hospitalizations are lacking in the United States. What is added by this report? COVID-NET was implemented to produce robust, weekly, age-stratified COVID-19–associated hospitalization rates. Hospitalization rates increase with age and are highest among older adults; the majority of hospitalized patients have underlying conditions. What are the implications for public health practice? Strategies to prevent COVID-19, including social distancing, respiratory hygiene, and face coverings in public settings where social distancing measures are difficult to maintain, are particularly important to protect older adults and those with underlying conditions. Ongoing monitoring of hospitalization rates is critical to understanding the evolving epidemiology of COVID-19 in the United States and to guide planning and prioritization of health care resources.
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            Intellectual and Developmental Disability and COVID-19 Case-Fatality Trends: TriNetX Analysis

            Background Despite possibly higher risk of severe outcomes from COVID-19 among people with intellectual and developmental disabilities (IDD), there has been limited reporting of COVID-19 trends for this population. Objective To compare COVID-19 trends among people with and without IDD, overall and stratified by age. Methods Data from the TriNetX COVID-19 Research Network platform was used to identify COVID-19 patients. Analysis focused on trends in comorbidities, number of cases, number of deaths, and case-fatality rate among patients with and without IDD who had a positive diagnosis for COVID-19 through May 14, 2020. Results People with IDD had higher prevalence of specific comorbidities associated with poorer COVID-19 outcomes. Distinct age-related differences in COVID-19 trends were present among those with IDD, with a higher concentration of COVID-19 cases at younger ages. In addition, while the overall case-fatality rate was similar for those with IDD (5.1%) and without IDD (5.4%), these rates differed by age: ages 75– IDD 21.1%, without IDD, 20.7%. Conclusions Though of concern for all individuals, COVID-19 appears to present a greater risk to people with IDD, especially at younger ages. Future research should seek to document COVID-19 trends among people with IDD, with particular attention to age related trends.
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              Infections and immunodeficiency in Down syndrome.

              Down syndrome (DS) is the most common genetic disease and presents with cognitive impairment, cardiac and gastrointestinal abnormalities, in addition to other miscellaneous clinical conditions. DS individuals may have a high frequency of infections, usually of the upper respiratory tract, characterized by increased severity and prolonged course of disease, which are partially attributed to defects of the immune system. The abnormalities of the immune system associated with DS include: mild to moderate T and B cell lymphopenia, with marked decrease of naive lymphocytes, impaired mitogen-induced T cell proliferation, reduced specific antibody responses to immunizations and defects of neutrophil chemotaxis. Limited evidence of genetic abnormalities secondary to trisomy of chromosome 21 and affecting the immune system is available, such as the potential consequences of gene over-expression, most significantly SOD1 and RCAN1. Secondary immunodeficiency due to metabolic or nutritional factors in DS, particularly zinc deficiency, has been postulated. Non-immunological factors, including abnormal anatomical structures (e.g. small ear canal, tracheomalacia) and gastro-oesophageal reflux, may play a role in the increased frequency of respiratory tract infections. The molecular mechanisms leading to the immune defects observed in DS individuals and the contribution of these immunological abnormalities to the increased risk of infections require further investigation. Addressing immunological and non-immunological factors involved in the pathogenesis of infectious diseases may reduce the susceptibility to infections in DS subjects. © 2011 The Authors. Clinical and Experimental Immunology © 2011 British Society for Immunology.
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                Author and article information

                Contributors
                Journal
                J Pediatr
                J. Pediatr
                The Journal of Pediatrics
                Elsevier Inc.
                0022-3476
                1097-6833
                27 August 2020
                27 August 2020
                Affiliations
                [1 ]Ann & Robert H. Lurie Children’s Hospital, Chicago, IL, USA
                [2 ]Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
                Author notes
                []Corresponding Author anewman@ 123456luriechildrens.org
                Article
                S0022-3476(20)31103-3
                10.1016/j.jpeds.2020.08.067
                7451004
                32861693
                f528b631-66cd-4f43-982e-e53dc2e39bb8
                © 2020 Elsevier Inc. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 5 July 2020
                : 20 August 2020
                : 24 August 2020
                Categories
                Article

                Pediatrics
                trisomy 21,down syndrome,covid-19
                Pediatrics
                trisomy 21, down syndrome, covid-19

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