State of the Oral Implantology Practice in Spain during the COVID-19 Pandemic: A Cross-Sectional Survey.

At the beginning of the COVID-19 pandemic, strict measures of confinement and social distancing were taken. Dentists were considered essential personnel and their activity was restricted to emergency treatment. The present observational study aims to determine the situation of oral implantology practice in Spain during the initial period of the COVID-19 pandemic. This is a cross-sectional observational study based on the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines. An electronic survey consisting of three blocks of questions was sent to all members of the Spanish Society of Implants. The data were analyzed using descriptive analysis. A total of 237 participants (14.3%) responded to the questionnaire. The majority of participants (60.8%) only attended emergencies during the first 9 months of the pandemic. Despite this, 77.2% reported having performed dental implant surgeries and 75.5% indicated that they performed non-essential treatments. The activity was fully recovered by 64.1% of the surveyed dentists. The majority of dentists (90.7%) considered that sufficient/adequate preventive measures were carried out at their workplace, which possibly contributed to the fact that 49.3% were not afraid of becoming infected. This concern was significantly and directly proportionally associated with the age of the surveyed dentists. The oral implant practice was affected to a greater extent during the first 9 months of the pandemic, especially in urban areas, with a greater impact on the workload of professionals with less specialised training in oral implantology.

Outcomes of hospitalized patients with COVID-19 during the course of the pandemic in a fully integrated health system.

BACKGROUND: Given the rapid spread of COVID-19 and its associated morbidity and mortality, healthcare providers throughout the world have been forced to constantly update and change their care delivery models. OBJECTIVE: To assess the outcomes of COVID-19 hospitalized patients during the course of the pandemic in a well-integrated health system. METHODS: The study used data from the electronic health medical records to assess trends in clinical profile and outcomes of hospitalized adult COVID-19 patients hospitalized in our 5-hospital health system from March 2020-May 2021 (n = 6865). Integration of the health system began in February 2020 and was fully actualized by March 30, 2020. RESULTS: Mortality decreased from 15% during first peak (March-May 2020; the rate includes 19% in March-April and 10% in May 2020) to 6% in summer-fall 2020, increased to 13% during the second peak (November 2020-January 2021), and dropped to 7% during the decline period (February-May 2021) (p<0.01). Resource utilization followed a similar pattern including a decrease in ICU use from 35% (first peak) to 16% (decline period), mechanical ventilation from 16% (first peak, including 45% in March 2020) to 9-11% in subsequent periods (p<0.01). Independent predictors of inpatient mortality across multiple study periods included older age, male sex, higher multi-morbidity scores, morbid obesity, and indicators of severe illness on admission such as oxygen saturation ≤90% and high qSOFA score (all p<0.05). However, admission during the first peak remained independently associated with increased mortality even after adjustment for patient-related factors: odds ratio = 1.8 (1.4-2.4) (p<0.0001). CONCLUSIONS: The creation of a fully integrated health system allowed us to dynamically respond to the everchanging COVID-19 landscape. In this context, despite the increasing patient acuity, our mortality and resource utilization rates have improved during the pandemic.

Neurological Manifestations in Pediatric Patients Hospitalized for COVID-19: Experiences of the National Medical Center "20 de Noviembre" in Mexico City.

COVID-19 has affected millions of children and, while it was previously considered as a respiratory disease, neurologic involvement has also been documented. The objective of this study was to identify the neurological manifestations (NMs) and the outcomes of children with COVID-19 who attended the National Medical Center "20 de Noviembre". METHODS: A retrospective cohort study of children hospitalized for COVID-19 from April 2020 to March 2021 was conducted. Clinical-demographic data were registered. Neurologic manifestations were defined as any clinical neurological expression of the central and/or peripheral nervous system that occurred during admission or hospitalization. RESULTS: In total, 46 children with a confirmed COVID-19 result, 26 (56.5%) boys and 20 (43.5%) girls with a median age of 8.9 ± 4.6 years, constituted the study population. Half of the children showed some NMs, and this group of patients concomitantly showed acute lymphoblastic leukemia (ALL, 56%), obesity (17.3%), or acute myeloblastic leukemia (AML, 4.3%). The most frequently described NMs were headache (13, 56%), encephalopathy (10, 43.47%), and epilepsy (4, 17.39%). The mortality rate in children with NMs was 21.7% and they had a higher mortality rate when compared to those without NM p ≤ 0.025. CONCLUSIONS: NMs occurred predominantly in male children aged 6 to 12 years; ALL was the most frequent comorbidity. Headache prevailed and hypoxemia, hypocalcemia, elevated ferritin, and C-reactive protein were associated with NM. Finally, NMs were a risk factor for mortality.

Service line care delivery model for COVID-19 patient-centric care.

OBJECTIVES: The COVID-19 pandemic has caused hospitals around the world to quickly develop not only strategies to treat patients but also methods to protect health care and frontline workers. STUDY DESIGN: Descriptive study. METHODS: We outlined the steps and processes that we took to respond to the challenges presented by the COVID-19 pandemic while continuing to provide our routine acute care services to our community. RESULTS: These steps and processes included establishing teams focused on maintaining an adequate supply of personal protection equipment, cross-training staff, developing disaster-based triage for the emergency department, creating quality improvement teams geared toward updating care based on the most current literature, developing COVID-19-based units, creating COVID-19-specific teams of providers, maximizing use of our electronic health record system to allocate beds, and providing adequate practitioner coverage by creating a computer-based dashboard that indicated the need for health care practitioners. These processes led to seamless and integrated care for all patients with COVID-19 across our health system and resulted in a reduction in mortality from a high of 20% during the first peak (March and April 2020) to 6% during the plateau period (June-October 2020) to 12% during the second peak (November and December 2020). CONCLUSIONS: The detailed processes put in place will help hospital systems meet the continuing challenges not only of COVID-19 but also beyond COVID-19 when other unique public health crises may present themselves.

Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset.

Worldwide, COVID-19 coronavirus disease is spreading rapidly in a second and third wave of infections. In this context of increasing infections, it is critical to know the probability of a specific number of cases being reported. We collated data on new daily confirmed cases of COVID-19 breakouts in: Argentina, Brazil, China, Colombia, France, Germany, India, Indonesia, Iran, Italy, Mexico, Poland, Russia, Spain, U.K., and the United States, from the 20th of January, 2020 to 28th of August 2021. A selected sample of almost ten thousand data is used to validate the proposed models. Generalized Extreme-Value Distribution Type 1-Gumbel and Exponential (1, 2 parameters) models were introduced to analyze the probability of new daily confirmed cases. The data presented in this document for each country provide the daily probability of rate incidence. In addition, the frequencies of historical events expressed as a return period in days of the complete data set is provided.