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ABSTRACT Objective: To develop and validate predictive models to estimate the number of COVID-19 patients hospitalized in the intensive care units and general wards of a private not-for-profit hospital in São Paulo, Brazil. Methods: Two main models were developed. The first model calculated hospital occupation as the difference between predicted COVID-19 patient admissions, transfers between departments, and discharges, estimating admissions based on their weekly moving averages, segmented by general wards and intensive care units. Patient discharge predictions were based on a length of stay predictive model, assessing the clinical characteristics of patients hospitalized with COVID-19, including age group and usage of mechanical ventilation devices. The second model estimated hospital occupation based on the correlation with the number of telemedicine visits by patients diagnosed with COVID-19, utilizing correlational analysis to define the lag that maximized the correlation between the studied series. Both models were monitored for 365 days, from May 20th, 2021, to May 20th, 2022. Results: The first model predicted the number of hospitalized patients by department within an interval of up to 14 days. The second model estimated the total number of hospitalized patients for the following 8 days, considering calls attended by Hospital Israelita Albert Einstein’s telemedicine department. Considering the average daily predicted values for the intensive care unit and general ward across a forecast horizon of 8 days, as limited by the second model, the first and second models obtained R² values of 0.900 and 0.996, respectively and mean absolute errors of 8.885 and 2.524 beds, respectively. The performances of both models were monitored using the mean error, mean absolute error, and root mean squared error as a function of the forecast horizon in days. Conclusion: The model based on telemedicine use was the most accurate in the current analysis and was used to estimate COVID-19 hospital occupancy 8 days in advance, validating predictions of this nature in similar clinical contexts. The results encourage the expansion of this method to other pathologies, aiming to guarantee the standards of hospital care and conscious consumption of resources.

ABSTRACT Objective Since the rising of coronavirus disease 2019 (COVID-19) pandemic, there is uncertainty regarding the impact of transmission to cancer patients. Evidence on increased severity for patients undergoing antineoplastic treatment is posed against deferring oncologic treatment. We aimed to evaluate the impact of COVID-19 pandemic on patient volumes in a cancer center in an epicenter of the pandemic. Methods Outpatient and inpatient volumes were extracted from electronic health record database. Two intervals were compared: pre-COVID-19 (March to May 2019) and COVID-19 pandemic (March to May 2020) periods. Results The total number of medical appointments declined by 45% in the COVID-19 period, including a 56.2% decrease in new visits. There was a 27.5% reduction in the number of patients undergoing intravenous systemic treatment and a 57.4% decline in initiation of new treatments. Conversely, there was an increase by 309% in new patients undergoing oral chemotherapy regimens and a 5.9% rise in new patients submitted to radiation therapy in the COVID-19 period. There was a 51.2% decline in length of stay and a 60% reduction in the volume of surgical cases during COVID-19. In the stem cell transplant unit, we observed a reduction by 36.5% in length of stay and a 62.5% drop in stem cell transplants. Conclusion A significant decrease in the number of patients undergoing cancer treatment was observed after COVID-19 pandemic. Although this may be partially overcome by alternative therapeutic options, avoiding timely health care due to fear of getting COVID-19 infection might impact on clinical outcomes. Our findings may help support immediate actions to mitigate this hypothesis.

Objective: The aim of the present study was to obtain information about deaths due to sepsis in São Paulo from 2004 to 2009 and their relationship with geographical distribution. Methods: Causes of death, both main and secondary, were defined according to the codes of the International Classification of Disease version 10 (ICD-10) contained in the database. Sepsis, septic shock, multiple organ failure, pneumonia, urinary tract infection, peritonitis and other intraabdominal infections, skin and soft tissue infections (including surgical wound infection) and meningitis were considered as immediate cause of death or as the condition leading to the immediate cause of death related or associated to sepsis. Results: In the analyzed period, there was a 15.3% increase in the absolute number of deaths from sepsis in São Paulo. The mean number of deaths during this period was 28,472 ± 1566. Most deaths due to sepsis and sepsis-related diseases over the studied period occurred in a hospital or health care facility, showing that most of the patients received medical care during the event that led to death. We observed a significant concentration of deaths in the most populous regions, tending more toward the center of the city. Conclusions: Georeferencing data from death certificates or other sources can be a powerful tool to uncover regional epidemiological differences between populations. Our study revealed an even distribution of sepsis all over the inhabited areas of São Paulo. Keywords: Sepsis, Mortality, Infection, Georeferencing

A few studies have performed to evaluate the temperature variation influences over on the stroke rates in Brazil. METHOD: 176 medical records of inpatients were analyzed after having had a stroke between 2004 and 2006 at Hospital Israelita Albert Einstein. The temperature preceding the occurrence of the symptoms was recorded, as well as the temperature 6, 12 and 24 hours before the symptoms in 6 different weather substations, closest to their houses in São Paulo. RESULTS: Strokes occurred more frequently after a variation of 3ºC between 6 and 24 hours before the symptoms. There were most hospitalizations between 23-24ºC. CONCLUSION: Incidence of stroke on these patients was increased after a variation of 3º Celsius within 24 hours before the ictus. The temperature variations could be an important factor in the occurrence of strokes in this population.Poucos trabalhos têm estudado a variação sazonal e de temperatura em acidente vascular cerebral (AVC) no Brasil. MÉTODO: Foram analisados 176 registros de pacientes com AVC no Hospital Israelita Albert Einstein entre 2004 e 2006. Foram anotadas as temperaturas ambientes do início dos sintomas, bem como as temperaturas de 6, 12 e 24 horas antes dos sintomas, em 6 diferentes subestações metereológicas mais próximas da casa do paciente em São Paulo. RESULTADOS: Houve aumento da incidência do AVC com a variação de 3ºC entre 6 e 24 horas antes do início dos sintomas. Houve um pico de internação entre 23-24ºC. CONCLUSÃO: A variação de temperatura de 3ºC nas 24 horas que antecederam o início dos sintomas pode ter sido um fator importante na ocorrência do AVC.

Objective: Despite the existence of evidence-based guidelines forthe management of patients with severe sepsis and septic shock,there is much variation among individual treatments. Methods: Abefore-after study with prospective data collection was performedat the emergency department and intensive care unit of a 485-bed,private, tertiary, general hospital. A total of 160 patients were enrolled(94 in a “pre-protocol phase” and 66 in a “post-protocol phase”). Aresuscitation bundle for the first six hours and a management bundlefor 24 hours were used. Additional quality indicators were alsoproposed and evaluated. The outcomes analyzed included hospitalmortality, hospital and intensive care unit length of stay, compliancewith bundles and performance related to quality indicators. Results:From the “pre-protocol” to “post-protocol” phase, the diagnosismoved from the intensive care unit (52.0 to 18.2%) to the emergencydepartment (26.6 to 40.9%) and to the wards (17.0 to 36.4%).Number of blood cultures prior to antibiotics, administration ofactivated drotrecogin alfa, use of corticosteroids and compliancewith six-hour and 24-hour sepsis bundles were significantly higherafter protocol implementation. Patients in the “post-protocol” grouphad a statistically lower risk of in-hospital mortality (56.4 versus36.4%, p = 0.01). The greatest decrease in mortality rate occurredamong the most critically ill patients (67.7 to 40.7%, p = 0.004).Conclusions: Adopting an institutional protocol focused on behavioralchanges and using quality improvement tools led to reduced hospitalmortality and generated changes in healthcare team practice. Thisresult adds to the growing evidence that optimized process-of-careby implementing managed protocols for sepsis patients can reducemortality. Therefore, similar strategies should be routinely employed.