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1.
Urology ; 167: 30-35, 2022 09.
Article in English | MEDLINE | ID: covidwho-1821517

ABSTRACT

OBJECTIVE: To analyze Twitter engagement in response to the urology match during the COVID-19 pandemic. METHODS: Tweets containing the hashtags "#uromatch" or "#AUAmatch" during the 2021 and 2022 Match Week were reviewed. Date, author type and number of followers, general content, and engagement with each Tweet was collected. Differences in engagement between author type and content were analyzed using the Kruskal-Wallis H test. Tweet characteristics were compared between the 2021 and 2022 Match Cycles using the Chi-Square test. RESULTS: There were 656 Tweets in total, with 272 (43.5%) from 2021 and 353 (56.5%) from 2022. Medical students' and residency programs' posts received significantly more Tweet engagement than those by residents/fellows, attendings, or the AUA (P <.05). Tweets focusing on announcing a new residency class and personal announcements of match results received significantly more engagements than other content categories (P <.05). In 2022, there was a significantly higher percentage of Tweets about advice for unmatched applicants (2.2 vs 12.5; P <.001), match statistics (0.4 vs 2.9; P = .028) and focus on underrepresented groups in urology (0.7 vs 3.4; P = .029). CONCLUSION: The Twitter response to the urology match between 2021 and 2022 mirrored the increase in competitiveness, with greater participation and an increasing focus on the difficulty of matching. During Match Week, Twitter is a readily available source of information for programs, matched students, and unmatched students alike. As we continue to embrace virtual platforms, we believe that Twitter will remain a major source of match-related information and can be an instrumental tool for broader networking in our field.


Subject(s)
COVID-19 , Internship and Residency , Social Media , Urology , COVID-19/epidemiology , Humans , Pandemics
2.
Am J Emerg Med ; 48: 140-147, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1157085

ABSTRACT

OBJECTIVES: We investigated the impact of anemia based on admission hemoglobin (Hb) level as a prognostic risk factor for severe outcomes in hospitalized patients with coronavirus disease 2019 (COVID-19). METHODS: A single-center, retrospective cohort study was conducted from a random sample of 733 adult patients (age ≥ 18 years) obtained from a total of 4356 laboratory confirmed SARS-CoV-2 cases who presented to the Emergency Department of Montefiore Medical Center between March-June 2020. The primary outcome was a composite endpoint of in-hospital severe outcomes of COVID-19. A secondary outcome was in-hospital all-cause mortality. RESULTS: Among the 733 patients included in our final analysis, 438 patients (59.8%) presented with anemia. 105 patients (14.3%) had mild, and 333 patients (45.5%) had moderate-severe anemia. Overall, 437 patients (59.6%) had a composite endpoint of severe outcomes. On-admission anemia was an independent risk factor for all-cause mortality, (Odds Ratio 1.52, 95% CI [1.01-2.30], p = 0.046) but not for composite severe outcomes. However, moderate-severe anemia (Hb < 11 g/dL) on admission was independently associated with both severe outcomes (OR1.53, 95% CI [1.05-2.23], p = 0.028) and mortality (OR 1.67, 95% CI [1.09-2.56], p = 0.019) during hospitalization. CONCLUSION: Anemia on admission was independently associated with increased odds of all-cause mortality in patients hospitalized with COVID-19. Furthermore, moderate-severe anemia (Hb <11 g/dL) was an independent risk factor for severe COVID-19 outcomes. Moving forward, COVID-19 patient management and risk stratification may benefit from addressing anemia on admission.


Subject(s)
Acute Kidney Injury/epidemiology , Anemia/blood , COVID-19/blood , Hospital Mortality , Hypotension/epidemiology , Respiratory Insufficiency/epidemiology , Shock, Septic/epidemiology , Aged , Aged, 80 and over , Anemia/therapy , Blood Transfusion/statistics & numerical data , COVID-19/mortality , Cause of Death , Cohort Studies , Female , Hemoglobins/metabolism , Hospitalization , Humans , Intensive Care Units , Male , Middle Aged , Respiration, Artificial/statistics & numerical data , Retrospective Studies , SARS-CoV-2 , Severity of Illness Index
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