Last data update: Nov 04, 2024. (Total: 48056 publications since 2009)
Records 1-8 (of 8 Records) |
Query Trace: Malden DE[original query] |
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A texting- and internet-based self-reporting system for enhanced vaccine safety surveillance with insights from a large integrated health care system in the United States: Prospective cohort study
Malden DE , Gee J , Glenn S , Li Z , Ryan DS , Gu Z , Bezi C , Kim S , Jazwa A , McNeil MM , Weintraub ES , Tartof SY . JMIR Mhealth Uhealth 2024 12 e58991 BACKGROUND: SMS text messaging- and internet-based self-reporting systems can supplement existing vaccine safety surveillance systems, but real-world participation patterns have not been assessed at scale. OBJECTIVE: This study aimed to describe the participation rates of a new SMS text messaging- and internet-based self-reporting system called the Kaiser Permanente Side Effect Monitor (KPSEM) within a large integrated health care system. METHODS: We conducted a prospective cohort study of Kaiser Permanente Southern California (KPSC) patients receiving a COVID-19 vaccination from April 23, 2021, to July 31, 2023. Patients received invitations through flyers, SMS text messages, emails, or patient health care portals. After consenting, patients received regular surveys to assess adverse events up to 5 weeks after each dose. Linkage with medical records provided demographic and clinical data. In this study, we describe KPSEM participation rates, defined as providing consent and completing at least 1 survey within 35 days of COVID-19 vaccination. RESULTS: Approximately, 8% (164,636/2,091,975) of all vaccinated patients provided consent and completed at least 1 survey within 35 days. The lowest participation rates were observed for parents of children aged 12-17 years (1349/152,928, 0.9% participation rate), and the highest participation was observed among older adults aged 61-70 years (39,844/329,487, 12.1%). Persons of non-Hispanic White race were more likely to participate compared with other races and ethnicities (13.1% vs 3.9%-7.5%, respectively; P<.001). In addition, patients residing in areas with a higher neighborhood deprivation index were less likely to participate (5.1%, 16,503/323,122 vs 10.8%, 38,084/352,939 in the highest vs lowest deprivation quintiles, respectively; P<.001). Invitations through the individual's Kaiser Permanente health care portal account and by SMS text message were associated with the highest participation rate (19.2%, 70,248/366,377 and 10.5%, 96,169/914,793, respectively), followed by email (19,464/396,912, 4.9%) and then QR codes on flyers (25,882/2,091,975, 1.2%). SMS text messaging-based surveys demonstrated the highest sustained daily response rates compared with internet-based surveys. CONCLUSIONS: This real-world prospective study demonstrated that a novel digital vaccine safety self-reporting system implemented through an integrated health care system can achieve high participation rates. Linkage with participants' electronic health records is another unique benefit of this surveillance system. We also identified lower participation among selected vulnerable populations, which may have implications when interpreting data collected from similar digital systems. |
Post-COVID conditions following COVID-19 vaccination: a retrospective matched cohort study of patients with SARS-CoV-2 infection
Malden DE , Liu IA , Qian L , Sy LS , Lewin BJ , Asamura DT , Ryan DS , Bezi C , Williams JTB , Kaiser R , Daley MF , Nelson JC , McClure DL , Zerbo O , Henninger ML , Fuller CC , Weintraub ES , Saydah S , Tartof SY . Nat Commun 2024 15 (1) 4101 COVID-19 vaccinations protect against severe illness and death, but associations with post-COVID conditions (PCC) are less clear. We aimed to evaluate the association between prior COVID-19 vaccination and new-onset PCC among individuals with SARS-CoV-2 infection across eight large healthcare systems in the United States. This retrospective matched cohort study used electronic health records (EHR) from patients with SARS-CoV-2 positive tests during March 2021-February 2022. Vaccinated and unvaccinated COVID-19 cases were matched on location, test date, severity of acute infection, age, and sex. Vaccination status was ascertained using EHR and integrated data on externally administered vaccines. Adjusted relative risks (RRs) were obtained from Poisson regression. PCC was defined as a new diagnosis in one of 13 PCC categories 30 days to 6 months following a positive SARS-CoV-2 test. The study included 161,531 vaccinated COVID-19 cases and 161,531 matched unvaccinated cases. Compared to unvaccinated cases, vaccinated cases had a similar or lower risk of all PCC categories except mental health disorders (RR: 1.06, 95% CI: 1.02-1.10). Vaccination was associated with ≥10% lower risk of sensory (RR: 0.90, 0.86-0.95), circulatory (RR: 0.88, 0.83-0.94), blood and hematologic (RR: 0.79, 0.71-0.89), skin and subcutaneous (RR: 0.69, 0.66-0.72), and non-specific COVID-19 related disorders (RR: 0.53, 0.51-0.56). In general, associations were stronger at younger ages but mostly persisted regardless of SARS-CoV-2 variant period, receipt of ≥3 vs. 1-2 vaccine doses, or time since vaccination. Pre-infection vaccination was associated with reduced risk of several PCC outcomes and hence may decrease the long-term consequences of COVID-19. |
Natural Language Processing for Improved Characterization of COVID-19 Symptoms: An Observational Study of 350,000 Patients in a Large Integrated Healthcare System.
Malden DE , Tartof SY , Ackerson BK , Hong V , Skarbinski J , Yau V , Qian L , Fischer H , Shaw S , Caparosa S , Xie F . JMIR Public Health Surveill 2022 8 (12) e41529 BACKGROUND: Natural language processing (NLP) of unstructured text from Electronic Medical Records (EMR) can improve characterization of COVID-19 signs and symptoms, but large-scale studies demonstrating the real-world application and validation of NLP for this purpose are limited. OBJECTIVE: To assess the contribution of NLP when identifying COVID-19 signs and symptoms from EMR. METHODS: This study was conducted in Kaiser Permanente Southern California, a large integrated healthcare system using data from all patients with positive SARS-CoV-2 laboratory tests from March 2020 to May 2021. An NLP algorithm was developed to extract free text from EMR on 12 established signs and symptoms of COVID-19, including fever, cough, headache, fatigue, dyspnea, chills, sore throat, myalgia, anosmia, diarrhea, vomiting/nausea and abdominal pain. The proportion of patients reporting each symptom and the corresponding onset dates were described before and after supplementing structured EMR data with NLP-extracted signs and symptoms. A random sample of 100 chart-reviewed and adjudicated SARS-CoV-2 positive cases were used to validate the algorithm performance. RESULTS: A total of 359,938 patients (mean age: 40.4 years; 53% female) with confirmed SARS-CoV-2 infection were identified over the study period. The most common signs and symptoms identified through NLP-supplemented analyses were cough (61%), fever (52%), myalgia (43%), and headache (40%). The NLP algorithm identified an additional 55,568 (15%) symptomatic cases that were previously defined as asymptomatic using structured data alone. The proportion of additional cases with each selected symptom identified in NLP-supplemented analysis varied across the selected symptoms, from 29% of all records for cough, to 61% of all records with nausea or vomiting. Of 295,305 symptomatic patients, the median time from symptom onset to testing was 3 days using structured data alone, whereas the NLP-algorithm identified signs or symptoms approximately one day earlier. When validated against chart-reviewed cases, the NLP algorithm successfully identified most signs and symptoms with consistently high sensitivity (ranging from 87% to 100%) and specificity (94% to 100%). CONCLUSIONS: These findings demonstrate that NLP can identify and characterize a broad set of COVID-19 signs and symptoms from unstructured data within the EMR, with enhanced detail and timeliness compared with structured data alone. |
Reactions following Pfizer-BioNTech COVID-19 mRNA vaccination and related healthcare encounters among 7,077 children aged 5-11 years within an integrated healthcare system.
Malden DE , Gee J , Glenn S , Li Z , Mercado C , Ogun OA , Kim S , Lewin BJ , Ackerson BK , Jazwa A , Weintraub ES , McNeil MM , Tartof SY . Vaccine 2022 41 (2) 315-322 BACKGROUND: Studies combining data from digital surveys and electronic health records (EHR) can be used to conduct comprehensive assessments on COVID-19 vaccine safety. METHODS: We conducted an observational study using data from a digital survey and EHR of children aged 5-11 years vaccinated with Pfizer-BioNTech COVID-19 mRNA vaccine across Kaiser Permanente Southern California during November 4, 2021-February 28, 2022. Parents/guardians who enrolled their children were sent a 14-day survey on reactions. Survey results were combined with EHR, and medical encounters were described for children whose parents or guardians indicated seeking medical care for vaccine-related symptoms. This study describes self-reported reactions (local and systemic) and additional symptoms (chest pain, tachycardia, and pre-syncope). RESULTS: The study recruited 7,077 participants aged 5-11 years who received the Pfizer-BioNTech COVID-19 mRNA vaccine. Of 6,247 participants with survey responses after dose 1, 2,176 (35 %) reported at least one systemic reaction, and 1,076 (32 %) of 3,401 respondents following dose 2 reported at least one systemic reaction. Local reactions were reported less frequently following dose 2 (1,113, 33 %) than dose 1 (3,140, 50 %). The most frequently reported reactions after dose 1 were pain at the injection site (48 %), fatigue (20 %), headache (12 %), myalgia (9 %) and fever (5 %). The most frequently reported symptoms after dose 2 were also pain at the injection site (30 %), fatigue (19 %), headache (13 %), myalgia (10 %) and fever (9 %). Post-vaccination reactions occurred most frequently-one day following vaccination. Chest pain or tachycardia were reported infrequently (1 %). EHR demonstrated that parents rarely sought care for post-vaccination symptoms, and among those seeking care, the most common symptoms documented in EHR were fever and nausea, comprising<0.5 % of children. No encounters were related to myocarditis. CONCLUSION: While post-vaccination reactions to the Pfizer-BioNTech COVID-19 mRNA vaccine were common in children aged 5-11 years, our data showed that in most cases they were transient and did not require medical care. |
Health Care Utilization in the 6 Months Following SARS-CoV-2 Infection.
Tartof SY , Malden DE , Liu IA , Sy LS , Lewin BJ , Williams JTB , Hambidge SJ , Alpern JD , Daley MF , Nelson JC , McClure D , Zerbo O , Henninger ML , Fuller C , Weintraub E , Saydah S , Qian L . JAMA Netw Open 2022 5 (8) e2225657 IMPORTANCE: After SARS-CoV-2 infection, many patients present with persistent symptoms for at least 6 months, collectively termed post-COVID conditions (PCC). However, the impact of PCC on health care utilization has not been well described. OBJECTIVES: To estimate COVID-19-associated excess health care utilization following acute SARS-CoV-2 infection and describe utilization for select PCCs among patients who had positive SARS-CoV-2 test results (including reverse transcription-polymerase chain reaction and antigen tests) compared with control patients whose results were negative. DESIGN, SETTING, AND PARTICIPANTS: This matched retrospective cohort study included patients of all ages from 8 large integrated health care systems across the United States who completed a SARS-CoV-2 diagnostic test during March 1 to November 1, 2020. Patients were matched on age, sex, race and ethnicity, site, and date of SARS-CoV-2 test and were followed-up for 6 months. Data were analyzed from March 18, 2021, to June 8, 2022. EXPOSURE: SARS-CoV-2 infection. MAIN OUTCOMES AND MEASURES: Ratios of rate ratios (RRRs) for COVID-19-associated health care utilization were calculated with a difference-in-difference analysis using Poisson regression models. RRRs were estimated overall, by health care setting, by select population characteristics, and by 44 PCCs. COVID-19-associated excess health care utilization was estimated by health care setting. RESULTS: The final matched cohort included 127 859 patients with test results positive for SARS-CoV-2 and 127 859 patients with test results negative for SARS-CoV-2. The mean (SD) age of the study population was 41.2 (18.6) years, 68 696 patients in each group (53.7%) were female, and each group included 66 211 Hispanic patients (51.8%), 9122 non-Hispanic Asian patients (7.1%), 7983 non-Hispanic Black patients (6.2%), and 34 326 non-Hispanic White patients (26.9%). Overall, SARS-CoV-2 infection was associated with a 4% increase in health care utilization over 6 months (RRR, 1.04 [95% CI, 1.03-1.05]), predominantly for virtual encounters (RRR, 1.14 [95% CI, 1.12-1.16]), followed by emergency department visits (RRR, 1.08 [95% CI, 1.04-1.12]). COVID-19-associated utilization for 18 PCCs remained elevated 6 months from the acute stage of infection, with the largest increase in COVID-19-associated utilization observed for infectious disease sequelae (RRR, 86.00 [95% CI, 5.07-1458.33]), COVID-19 (RRR, 19.47 [95% CI, 10.47-36.22]), alopecia (RRR, 2.52 [95% CI, 2.17-2.92]), bronchitis (RRR, 1.85 [95% CI, 1.62-2.12]), pulmonary embolism or deep vein thrombosis (RRR, 1.74 [95% CI, 1.36-2.23]), and dyspnea (RRR, 1.73 [95% CI, 1.61-1.86]). In total, COVID-19-associated excess health care utilization amounted to an estimated 27 217 additional medical encounters over 6 months (212.9 [95% CI, 146.5-278.4] visits per 1000 patients). CONCLUSIONS AND RELEVANCE: This cohort study documented an excess health care burden of PCC in the 6 months after the acute stage of infection. As health care systems evolve during a highly dynamic and ongoing global pandemic, these data provide valuable evidence to inform long-term strategic resource allocation for patients previously infected with SARS-CoV-2. |
Hospitalization and Emergency Department Encounters for COVID-19 After Paxlovid Treatment - California, December 2021-May 2022.
Malden DE , Hong V , Lewin BJ , Ackerson BK , Lipsitch M , Lewnard JA , Tartof SY . MMWR Morb Mortal Wkly Rep 2022 71 (25) 830-833 Nirmatrelvir/ritonavir (Paxlovid) is a combination protease inhibitor that blocks replication of SARS-CoV-2 (the virus that causes COVID-19) and has been shown to reduce the risk for hospitalization and death among patients with mild to moderate COVID-19 who are at risk for progression to severe disease* (1). In December 2021, the Food and Drug Administration (FDA) issued an Emergency Use Authorization (EUA) for early treatment with Paxlovid among persons with mild to moderate cases of COVID-19 who are at high risk for progression to severe disease (2). FDA and a small number of published case reports have documented recurrence of COVID-19 symptoms or a positive viral test result (COVID-19 rebound) 2-8 days after recovery or a negative SARS-CoV-2 test result among patients treated with Paxlovid (3-7); however, large-scale studies investigating severe illness after Paxlovid treatment are limited. This study used electronic health record (EHR) data from a large integrated health care system in California (Kaiser Permanente Southern California [KPSC]) to describe hospital admissions and emergency department (ED) encounters related to SARS-CoV-2 infections during the 5-15 days after pharmacy dispensation of a 5-day treatment course of Paxlovid. Among 5,287 persons aged ≥12 years who received Paxlovid during December 31, 2021-May 26, 2022, 73% had received ≥3 doses of COVID-19 vaccine(†), and 8% were unvaccinated. During the 5-15 days after Paxlovid treatment was dispensed, six hospitalizations and 39 ED encounters considered to be related to SARS-CoV-2 infection were identified, representing <1% of all patients to whom Paxlovid treatment was dispensed during the study period. Among these 45 persons, 21 (47%) were aged ≥65 years, and 35 (78%) had at least one underlying medical condition(§) (8). This study found that hospitalization or ED encounters for COVID-19 during the 5-15 days after Paxlovid treatment was dispensed for mild to moderate COVID-19 illness were rarely identified. When administered as an early-stage treatment, Paxlovid might prevent COVID-19-related hospitalization among persons with mild to moderate cases of COVID-19 who are at risk for progression to severe disease. |
Distribution of SARS-CoV-2 Variants in a Large Integrated Health Care System - California, March-July 2021.
Malden DE , Bruxvoort KJ , Tseng HF , Ackerson B , Choi SK , Florea A , Tubert J , Takhar H , Aragones M , Hong V , Talarico CA , McLaughlin JM , Qian L , Tartof SY . MMWR Morb Mortal Wkly Rep 2021 70 (40) 1415-1419 Data from observational studies demonstrate that variants of SARS-CoV-2, the virus that causes COVID-19, have evolved rapidly across many countries (1,2). The SARS-CoV-2 B.1.617.2 (Delta) variant of concern is more transmissible than previously identified variants,* and as of September 2021, is the predominant variant in the United States.(†) Studies characterizing the distribution and severity of illness caused by SARS-CoV-2 variants, particularly the Delta variant, are limited in the United States (3), and are subject to limitations related to study setting, specimen collection, study population, or study period (4-7). This study used whole genome sequencing (WGS) data on SARS-CoV-2-positive specimens collected across Kaiser Permanente Southern California (KPSC), a large integrated health care system, to describe the distribution and risk of hospitalization associated with SARS-CoV-2 variants during March 4-July 21, 2021, by patient vaccination status. Among 13,039 SARS-CoV-2-positive specimens identified from KPSC patients during this period, 6,798 (52%) were sequenced and included in this report. Of these, 5,994 (88%) were collected from unvaccinated persons, 648 (10%) from fully vaccinated persons, and 156 (2%) from partially vaccinated persons. Among all sequenced specimens, the weekly percentage of B.1.1.7 (Alpha) variant infections increased from 20% to 67% during March 4-May 19, 2021. During April 15-July 21, 2021, the weekly percentage of Delta variant infections increased from 0% to 95%. During March 4-July 21, 2021, the weekly percentage of variants was similar among fully vaccinated and unvaccinated persons, but the Delta variant was more commonly identified among vaccinated persons then unvaccinated persons overall, relative to other variants. The Delta variant was more prevalent among younger persons, with the highest percentage (55%) identified among persons aged 18-44 years. Infections attributed to the Delta variant were also more commonly identified among non-Hispanic Black persons, relative to other variants. These findings reinforce the importance of continued monitoring of SARS-CoV-2 variants and implementing multiple COVID-19 prevention strategies, particularly during the current period in which Delta is the predominant variant circulating in the United States. |
Obesity and Mortality Among Patients Diagnosed With COVID-19.
Tartof SY , Murali SB , Malden DE . Ann Intern Med 2021 174 (6) 887-888 IN RESPONSE: We thank all respondents for their expertise in identifying potential mediating factors underlying the observed association between BMI and COVID-19 severity described in our study. | | Dr. Kollias and colleagues describe how COVID-19 may exacerbate the known association between BMI and VTE. We did not directly examine the association between VTE and COVID-19 mortality. However, we clinically observed a slight (although nonsignificant) increased risk for death among patients with underlying peripheral vascular disease, a condition that likely shares similar pathophysiologic mechanisms with VTE (1). Because of the association between a high BMI and risk for VTE, as well as the biological plausibility for COVID-19 to potentiate VTE risk, physicians should consider the possibility of enhanced VTE risk among obese patients with COVID-19. |
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