Did COVID-19 ICU patient mortality risk increase as Colorado hospitals filled? A retrospective cohort study.

OBJECTIVES: To assess whether increasing levels of hospital stress-measured by intensive care unit (ICU) bed occupancy (primary), ventilators in use and emergency department (ED) overflow-were associated with decreasing COVID-19 ICU patient survival in Colorado ICUs during the pre-Delta, Delta and Omicron variant eras. DESIGN: A retrospective cohort study using discrete-time survival models, fit with generalised estimating equations. SETTING: 34 hospital systems in Colorado, USA, with the highest patient volume ICUs during the COVID-19 pandemic. PARTICIPANTS: 9196 non-paediatric SARS-CoV-2 patients in Colorado hospitals admitted once to an ICU between 1 August 2020 and 1 March 2022 and followed for 28 days. OUTCOME MEASURES: Death or discharge to hospice. RESULTS: For Delta-era COVID-19 ICU patients in Colorado, the odds of death were estimated to be 26% greater for patients exposed every day of their ICU admission to a facility experiencing its all-era 75th percentile ICU fullness or above, versus patients exposed for none of their days (OR: 1.26; 95% CI: 1.04 to 1.54; p=0.0102), adjusting for age, sex, length of ICU stay, vaccination status and hospital quality rating. For both Delta-era and Omicron-era patients, we also detected significantly increased mortality hazard associated with high ventilator utilisation rates and (in a subset of facilities) states of ED overflow. For pre-Delta-era patients, we estimated relatively null or even protective effects for the same fullness exposures, something which provides a meaningful contrast to previous studies that found increased hazards but were limited to pre-Delta study windows. CONCLUSIONS: Overall, and especially during the Delta era (when most Colorado facilities were at their fullest), increasing exposure to a fuller hospital was associated with an increasing mortality hazard for COVID-19 ICU patients.

Boletim COVID-19 - 16/05/2023

Boletim semanal COVID-19 no município de São Paulo de 16 de maio de 2023

Boletim Diário - COVID-19 no Município de São Paulo – nº 615

Boletim informativo sobre a situação do novo coronavírus na capital paulista nos hospitais da rede municipal e de campanha, contratualizados e Atenção Básica.

Do subsidized nursing homes and home care teams reduce hospital bed-blocking? Evidence from Portugal.

Excessive length of hospital stay is among the leading sources of inefficiency in healthcare. When a patient is clinically fit to be discharged but requires support outside the hospital, which is not readily available, they remain hospitalized until a safe discharge is possible -a phenomenon called bed-blocking. I study whether the availability of subsidized nursing homes and home care teams reduces hospital bed-blocking. Using individual data on the universe of inpatient admissions at Portuguese hospitals during 2000-2015, I find that the entry of home care teams in a region reduces bed-blocking by 4 days per episode, on average. Nursing home entry only reduces bed-blocking among patients with high care needs or when the intensity of entry is high. Reductions in bed-blocking do not harm patients' health. The beds freed up by reducing bed-blocking are used to admit additional elective patients.

Remdesivir and dexamethasone as tools to relieve hospital care systems stressed by COVID-19: A modelling study on bed resources and budget impact.

Remdesivir and dexamethasone are the only drugs providing reductions in the lengths of hospital stays for COVID-19 patients. We assessed the impacts of remdesivir on hospital-bed resources and budgets affected by the COVID-19 outbreak. A stochastic agent-based model was combined with epidemiological data available on the COVID-19 outbreak in France and data from two randomized control trials. Strategies involving treating with remdesivir only patients with low-flow oxygen and patients with low-flow and high-flow oxygen were examined. Treating all eligible low-flow oxygen patients during the entirety of the second wave would have decreased hospital-bed occupancy in conventional wards by 4% [2%; 7%] and intensive care unit (ICU)-bed occupancy by 9% [6%; 13%]. Extending remdesivir use to high-flow-oxygen patients would have amplified reductions in ICU-bed occupancy by up to 14% [18%; 11%]. A minimum remdesivir uptake of 20% was required to observe decreases in bed occupancy. Dexamethasone had effects of similar amplitude. Depending on the treatment strategy, using remdesivir would, in most cases, generate savings (up to 722€) or at least be cost neutral (an extra cost of 34€). Treating eligible patients could significantly limit the saturation of hospital capacities, particularly in ICUs. The generated savings would exceed the costs of medications.

Early Tracheostomy for Managing ICU Capacity During the COVID-19 Outbreak: A Propensity-Matched Cohort Study.

BACKGROUND: During the first wave of the COVID-19 pandemic, shortages of ventilators and ICU beds overwhelmed health care systems. Whether early tracheostomy reduces the duration of mechanical ventilation and ICU stay is controversial. RESEARCH QUESTION: Can failure-free day outcomes focused on ICU resources help to decide the optimal timing of tracheostomy in overburdened health care systems during viral epidemics? STUDY DESIGN AND METHODS: This retrospective cohort study included consecutive patients with COVID-19 pneumonia who had undergone tracheostomy in 15 Spanish ICUs during the surge, when ICU occupancy modified clinician criteria to perform tracheostomy in Patients with COVID-19. We compared ventilator-free days at 28 and 60 days and ICU- and hospital bed-free days at 28 and 60 days in propensity score-matched cohorts who underwent tracheostomy at different timings (≤ 7 days, 8-10 days, and 11-14 days after intubation). RESULTS: Of 1,939 patients admitted with COVID-19 pneumonia, 682 (35.2%) underwent tracheostomy, 382 (56%) within 14 days. Earlier tracheostomy was associated with more ventilator-free days at 28 days (≤ 7 days vs > 7 days [116 patients included in the analysis]: median, 9 days [interquartile range (IQR), 0-15 days] vs 3 days [IQR, 0-7 days]; difference between groups, 4.5 days; 95% CI, 2.3-6.7 days; 8-10 days vs > 10 days [222 patients analyzed]: 6 days [IQR, 0-10 days] vs 0 days [IQR, 0-6 days]; difference, 3.1 days; 95% CI, 1.7-4.5 days; 11-14 days vs > 14 days [318 patients analyzed]: 4 days [IQR, 0-9 days] vs 0 days [IQR, 0-2 days]; difference, 3 days; 95% CI, 2.1-3.9 days). Except hospital bed-free days at 28 days, all other end points were better with early tracheostomy. INTERPRETATION: Optimal timing of tracheostomy may improve patient outcomes and may alleviate ICU capacity strain during the COVID-19 pandemic without increasing mortality. Tracheostomy within the first work on a ventilator in particular may improve ICU availability.

Hospital Occupancy and its Effect on Emergency Department Evaluation.

STUDY OBJECTIVE: To examine whether hospital occupancy was associated with increased testing and treatment during emergency department (ED) evaluations, resulting in reduced admissions. METHODS: We analyzed the electronic health records of an urban academic ED. We linked data from all ED visits from October 1, 2010, to May 29, 2015, with daily hospital occupancy (inpatients/total staffed beds). Outcome measures included the frequency of laboratory testing, advanced imaging, medication administration, and hospitalizations. We modeled each outcome using multivariable negative binomial or logistic regression, as appropriate, and examined their association with daily hospital occupancy quartiles, controlling for patient and visit characteristics. We calculated the adjusted outcome rates and relative changes at each daily hospital occupancy quartile using marginal estimating methods. RESULTS: We included 270,434 ED visits with a mean patient age of 48.1 (standard deviation 19.8) years; 40.1% were female, 22.8% were non-Hispanic Black, and 51.5% were commercially insured. Hospital occupancy was not associated with differences in laboratory testing, advanced imaging, or medication administration. Compared with the first quartile, the third and fourth quartiles of daily hospital occupancy were associated with decreases of 1.5% (95% confidence interval [CI] -2.9 to -0.2; absolute change -0.6 percentage points [95% CI -1.2 to -0.1]) and 4.6% (95% CI -6.0 to -3.2; absolute change -1.9 percentage points [95% CI -2.5 to -1.3]) in hospitalizations, respectively. CONCLUSION: The lack of association between hospital occupancy and laboratory testing, advanced imaging, and medication administration suggest that changes in ED testing or treatment did not facilitate the decrease in admissions during periods of high hospital occupancy.

Emprego do modelo matemático SEIHDR para auxiliar gestores na estimativa de ocupação de leitos de UTI em uma pandemia: simulação para pacientes com COVID-19 no município de Porto Alegre / Use of the SEIHDR mathematical model to assist health managers in estimating ICU bed occupancy in a pandemic: simulation for patients with COVID-19 in the city of Porto Alegre, Brazil

Introdução: A pandemia de COVID-19, no Brasil, constituiu uma ameaça ao sistema de saúde pelo risco de esgotamento dos leitos de Unidade de Terapia Intensiva (UTI). O objetivo do estudo foi projetar a ocupação de leitos de UTI com casos de COVID-19 no pico em Porto Alegre. Para isso, resolvemos utilizar uma ferramenta matemática com parâmetros da pandemia desta cidade.Métodos:Utilizamos o modelo matemático SEIHDR. Analisamos os casos de hospitalização por COVID-19 em Porto Alegre e RS até 3 de agosto de 2020 a fim de extrair os parâmetros locais para construir uma curva epidemiológica do total de casos prevalentes hospitalizados em UTI. Também analisamos as taxas de reprodução básica (R0) e reprodução efetiva (Re).Resultados: O modelo matemático projetou um pico de 344 casos prevalentes, em UTI, para o dia 22 de agosto de 2020. Calculamos 1,56 para o R0 e 1,08 no dia 3 de agosto para o Re.Conclusão: O modelo matemático simulou uma primeira onda de casos ocupando leitos de UTI muito próxima dos dados reais. Também indicou corretamente uma queda no número de casos nos dois meses subsequentes. Apesar das limitações, as estimativas do modelo matemático forneceram informações sobre as dimensões temporal e numérica de uma pandemia que poderiam ser usadas como auxílio aos gestores de saúde na tomada de decisões para a alocação de recursos frente a calamidades de saúde como o surto de COVID-19 no Brasil.

Introduction: The COVID-19 pandemic in Brazil has been a threat to health services due to the risk of bed shortage in the intensive care unit (ICU). This study aimed to estimate the bed occupancy at the ICU with patients with COVID-19 during the peak of the pandemic in Porto Alegre, capital of Rio Grande do Sul (RS), the southernmost state of Brazil. To this end, we used a mathematical model with pandemic parameters from the city.Methods: We used the SEIHDR mathematical model. We analyzed hospitalizations for COVID-19 in Porto Alegre and RS until August 3, 2020, to extract local parameters to create an epidemiological curve of the total number of prevalent cases in the ICU. We also analyzed the basic reproduction rate (R0) and effective reproduction rate (Re). Results: The mathematical model estimated a peak of 344 prevalent cases in the ICU on August 22, 2020. The model calculated an R0 of 1.56 and Re of 1.08 on August 3, 2020.Conclusion: The mathematical model accurately estimated the first peak of cases in the ICU. Also, it correctly indicated a drop in the number of cases in the following two months. Despite the limitations, the mathematical model estimates provided information on the temporal and numerical dimensions of a pandemic that could be used to assist health managers in making decisions on the allocation of resources in a state of public calamity such as the COVID-19 outbreak in Brazil.

Audit of surgical specialty patients and beds at Pietersburg Hospital, Limpopo Province, South Africa in 2021.

BACKGROUND: While the absolute number of hospital beds is usually discussed, adequate utilisation of beds is a far better instrument to measure departmental efficiency. OBJECTIVE: To measure the number of beds for each surgical specialty in Pietersburg Hospital as well as the average length of stay (LoS) to compare bed utilisation. METHOD: We conducted a 1-day descriptive cross-sectional audit of patients admitted to surgical wards on 21 April 2021 at Pietersburg Hospital. RESULTS: There were huge discrepancies in the number of beds per surgical specialty as well as the LoS. Over one-third of surgical beds were occupied by patients waiting for either a computed tomography scan, surgical procedure, or transfer. CONCLUSION: There is a need to address the functioning of the surgical specialties with regards to the number of beds allocated as well as the ideal average length of stay.

Impact of Hospital Strain on Excess Deaths During the COVID-19 Pandemic - United States, July 2020-July 2021.

Surges in COVID-19 cases have stressed hospital systems, negatively affected health care and public health infrastructures, and degraded national critical functions (1,2). Resource limitations, such as available hospital space, staffing, and supplies led some facilities to adopt crisis standards of care, the most extreme operating condition for hospitals, in which the focus of medical decision-making shifted from achieving the best outcomes for individual patients to addressing the immediate care needs of larger groups of patients (3). When hospitals deviated from conventional standards of care, many preventive and elective procedures were suspended, leading to the progression of serious conditions among some persons who would have benefitted from earlier diagnosis and intervention (4). During March-May 2020, U.S. emergency department visits declined by 23% for heart attacks, 20% for strokes, and 10% for diabetic emergencies (5). The Cybersecurity & Infrastructure Security Agency (CISA) COVID Task Force* examined the relationship between hospital strain and excess deaths during July 4, 2020-July 10, 2021, to assess the impact of COVID-19 surges on hospital system operations and potential effects on other critical infrastructure sectors and national critical functions. The study period included the months during which the highly transmissible SARS-CoV-2 B.1.617.2 (Delta) variant became predominant in the United States.† The negative binomial regression model used to calculate estimated deaths predicted that, if intensive care unit (ICU) bed use nationwide reached 75% capacity an estimated 12,000 additional excess deaths would occur nationally over the next 2 weeks. As hospitals exceed 100% ICU bed capacity, 80,000 excess deaths would be expected in the following 2 weeks. This analysis indicates the importance of controlling case growth and subsequent hospitalizations before severe strain. State, local, tribal, and territorial leaders could evaluate ways to reduce strain on public health and health care infrastructures, including implementing interventions to reduce overall disease prevalence such as vaccination and other prevention strategies, as well as ways to expand or enhance capacity during times of high disease prevalence.

Smart testing and critical care bed sharing for COVID-19 control.

During the early months of the current COVID-19 pandemic, social distancing measures effectively slowed disease transmission in many countries in Europe and Asia, but the same benefits have not been observed in some developing countries such as Brazil. In part, this is due to a failure to organise systematic testing campaigns at nationwide or even regional levels. To gain effective control of the pandemic, decision-makers in developing countries, particularly those with large populations, must overcome difficulties posed by an unequal distribution of wealth combined with low daily testing capacities. The economic infrastructure of these countries, often concentrated in a few cities, forces workers to travel from commuter cities and rural areas, which induces strong nonlinear effects on disease transmission. In the present study, we develop a smart testing strategy to identify geographic regions where COVID-19 testing could most effectively be deployed to limit further disease transmission. By smart testing we mean the testing protocol that is automatically designed by our optimization platform for a given time period, knowing the available number of tests, the current availability of ICU beds and the initial epidemiological situation. The strategy uses readily available anonymised mobility and demographic data integrated with intensive care unit (ICU) occupancy data and city-specific social distancing measures. Taking into account the heterogeneity of ICU bed occupancy in differing regions and the stages of disease evolution, we use a data-driven study of the Brazilian state of Sao Paulo as an example to show that smart testing strategies can rapidly limit transmission while reducing the need for social distancing measures, even when testing capacity is limited.

AFN Acessibilidade - Semana de 09/08 a 13/08

Com o objetivo de ampliar a divulgação de notícias sobre Covid-19 para pessoas com deficiências auditivas, a Coordenação de Comunicação Social (CCS/Fiocruz) lançou um programa semanal que reúne as principais notícias publicadas na Agência Fiocruz de Notícias (AFN) traduzidas para a Língua Brasileira de Sinais (Libras) e com áudio em português.

Association of COVID-19 Hospitalization Volume and Case Growth at US Hospitals with Patient Outcomes.

BACKGROUND: Whether the volume of coronavirus disease 2019 (COVID-19) hospitalizations is associated with outcomes has important implications for the organization of hospital care both during this pandemic and future novel and rapidly evolving high-volume conditions. METHODS: We identified COVID-19 hospitalizations at US hospitals in the American Heart Association COVID-19 Cardiovascular Disease Registry with ≥10 cases between January and August 2020. We evaluated the association of COVID-19 hospitalization volume and weekly case growth indexed to hospital bed capacity, with hospital risk-standardized in-hospital case-fatality rate (rsCFR). RESULTS: There were 85 hospitals with 15,329 COVID-19 hospitalizations, with a median hospital case volume was 118 (interquartile range, 57, 252) and median growth rate of 2 cases per 100 beds per week but varied widely (interquartile range: 0.9 to 4.5). There was no significant association between overall hospital COVID-19 case volume and rsCFR (rho, 0.18, P = .09). However, hospitals with more rapid COVID-19 case-growth had higher rsCFR (rho, 0.22, P = 0.047), increasing across case growth quartiles (P trend = .03). Although there were no differences in medical treatments or intensive care unit therapies (mechanical ventilation, vasopressors), the highest case growth quartile had 4-fold higher odds of above median rsCFR, compared with the lowest quartile (odds ratio, 4.00; 1.15 to 13.8, P = .03). CONCLUSIONS: An accelerated case growth trajectory is a marker of hospitals at risk of poor COVID-19 outcomes, identifying sites that may be targets for influx of additional resources or triage strategies. Early identification of such hospital signatures is essential as our health system prepares for future health challenges.

The association between mechanical ventilator compatible bed occupancy and mortality risk in intensive care patients with COVID-19: a national retrospective cohort study.

BACKGROUND: The literature paints a complex picture of the association between mortality risk and ICU strain. In this study, we sought to determine if there is an association between mortality risk in intensive care units (ICU) and occupancy of beds compatible with mechanical ventilation, as a proxy for strain. METHODS: A national retrospective observational cohort study of 89 English hospital trusts (i.e. groups of hospitals functioning as single operational units). Seven thousand one hundred thirty-three adults admitted to an ICU in England between 2 April and 1 December, 2020 (inclusive), with presumed or confirmed COVID-19, for whom data was submitted to the national surveillance programme and met study inclusion criteria. A Bayesian hierarchical approach was used to model the association between hospital trust level (mechanical ventilation compatible), bed occupancy, and in-hospital all-cause mortality. Results were adjusted for unit characteristics (pre-pandemic size), individual patient-level demographic characteristics (age, sex, ethnicity, deprivation index, time-to-ICU admission), and recorded chronic comorbidities (obesity, diabetes, respiratory disease, liver disease, heart disease, hypertension, immunosuppression, neurological disease, renal disease). RESULTS: One hundred thirty-five thousand six hundred patient days were observed, with a mortality rate of 19.4 per 1000 patient days. Adjusting for patient-level factors, mortality was higher for admissions during periods of high occupancy (> 85% occupancy versus the baseline of 45 to 85%) [OR 1.23 (95% posterior credible interval (PCI): 1.08 to 1.39)]. In contrast, mortality was decreased for admissions during periods of low occupancy (< 45% relative to the baseline) [OR 0.83 (95% PCI 0.75 to 0.94)]. CONCLUSION: Increasing occupancy of beds compatible with mechanical ventilation, a proxy for operational strain, is associated with a higher mortality risk for individuals admitted to ICU. Further research is required to establish if this is a causal relationship or whether it reflects strain on other operational factors such as staff. If causal, the result highlights the importance of strategies to keep ICU occupancy low to mitigate the impact of this type of resource saturation.

Pediatric Emergency Department Challenges and Response to COVID-19.

Severe acute respiratory syndrome coronavirus 2, the virus causing the pandemic illness coronavirus disease 2019, was first detected in the United States in January 2020. As the illness spread across the country, all aspects and venues of health care were significantly impacted. This article explores the challenges and response of one children's emergency medicine division related to surge planning, personal protective equipment, screening, testing, staffing, and other operational challenges, and describes the impact and implications thus far. [Pediatr Ann. 2021;50(4):e172-e177.].

Burden of critically ill patients with influenza in a French catchment population.

Despite the particular focus given to influenza since the 2009 influenza A(H1N1) pandemic, true burden of influenza-associated critical illness remains poorly known. The aim of this study was to identify factors influencing influenza burden imposed on intensive care units (ICUs) in a catchment population during recent influenza seasons. From 2008 to 2013, all adult patients admitted with a laboratory-confirmed influenza infection to one of the ICUs in the catchment area were prospectively included. A total of 201 patients (mean age: 63 ± 16, sex-ratio: 1.1) were included. The influenza-related ICU-bed occupancy rate averaged 4.3% over the five influenza seasons, with the highest mean occupancy rate (16.9%) observed during the 2012 winter. In-hospital mortality for the whole cohort was 26%. Influenza A(H1N1)pdm infections (pdm in the mentioned nomenclature refers to Pandemic Disease Mexico 2009), encountered in 51% of cases, were significantly associated with neither longer length of stay nor higher mortality (ICU and hospital) when compared to infections with other virus subtypes. SOFA score (OR, 1.12; 95% CI, 1.04-1.29) was the only independent factor significantly associated with a prolonged hospitalization. These results highlight both the frequency and the severity of influenza-associated critical illness, leading to a sustained activity in ICUs. Severity of the disease, but not A(H1N1)pdm virus, appears to be a major determinant of ICU burden related to influenza.

Drastic reduction of orthopaedic services at an urban tertiary hospital in South Africa during COVID-19: Lessons for the future response to the pandemic.

BACKGROUND: The COVID-19 pandemic has impacted on the global surgery landscape. OBJECTIVES: To analyse and describe the initial impact of the COVID-19 pandemic on orthopaedic surgery at Groote Schuur Hospital, a tertiary academic hospital in South Africa. METHODS: The number of orthopaedic surgical cases, emergency theatre patient waiting times, and numbers of outpatient clinic visits, ward admissions, bed occupancies and total inpatient days for January - April 2019 (pre-COVID-19) were compared with the same time frame in 2020 (COVID-19). The COVID-19 timeframe included initiation of a national 'hard lockdown' from 26 March 2020, in preparation for an increasing volume of COVID-19 cases. RESULTS: April 2020, the time of the imposed hard lockdown, was the most affected month, although the number of surgical cases had started to decrease slowly during the 3 preceding months. The total number of surgeries, outpatient visits and ward admissions decreased significantly during April 2020 (55.2%, 69.1% and 60.6%, respectively) compared with April 2019 (p<0.05). Trauma cases were reduced by 40% in April 2020. Overall emergency theatre patient waiting time was 30% lower for April 2020 compared with 2019. CONCLUSIONS: COVID-19 and the associated lockdown has heavily impacted on both orthopaedic inpatient and outpatient services. Lockdown led to a larger reduction in the orthopaedic trauma burden than in international centres, but the overall reduction in surgeries, outpatient visits and hospital admissions was less. This lesser reduction was probably due to local factors, but also to a conscious decision to avoid total collapse of our surgical services.