Introduction: Since December 2019, more than 925,000 cases of COVID-19 have been reported worldwide, 8,251 cases in Portugal by the end of March. Previous studies related to the SARS pandemic showed a decrease up to 80% in the emergency care episodes. Hence, the objective of this study is to analyze the use of emergency services during the first pandemic month, compared to historical records. Methods: Data from emergency episodes in mainland Portugal, from January 2014 to March 2020, were downloaded from the National Health Service (NHS) Transparency Portal and the NHS monitoring website. The evolution of emergency services from March to September 2020 was forecasted based on historical data from January 2014 to February 2020. Information for March 2020 was forecasted globally, by the Regional Health Administration (RHA) and Manchester Triage System (MTS). Results: Compared with forecasted values, there was a 48% reduction in the number of emergency episodes in March 2020. In the analysis by the RHA, Alentejo had the smallest decrease in the number of episodes; interestingly, Alentejo is also the area with fewer CO-VID-19 cases in mainland Portugal. In the analysis by the MTS, the episodes classified as yellow showed the highest reduction (50%). For episodes classified as urgent, there is a difference of about 144,000 episodes during March 2020. Discussion: The results of this preliminary study are aligned with the evidence produced for previous pandemics. Data about the use of emergency services, demographic and clinical characteristics of the episodes would be relevant to analyze this reduction. Conclusion: There was a significant drop in the number of emergency service use in March 2020, and although the causes of this reduction are not determined, the association between the beginning of the pandemic and the reduction of demand is evident. Understanding this phenomenon is crucial to plan interventions to avoid unnecessary morbidities or deaths, caused by a delayed visit to the emergency department.

Purpose The goal of this systematic review and meta-analysis was to identify the main risk factors for periprosthetic joint infection (PJI) in patients undergoing total hip or knee arthroplasties. Methods A systematic review was conducted of the potential risk factors for PJI in total hip or total knee arthroplasty. Risk factors were compared and grouped according to demographics, comorbidities, behavior, infections, native joint diseases and other patient-related and procedure-related factors. Meta-analysis (random-efects models) was conducted using odds ratio (OR) and mean diference (MD). Risk of bias (ROBBINS-I) and strength of the evidence (GRADE) were assessed. ResultsThe study included 37 studies (2,470,827 patients). Older age was a protective factor (MD = − 1.18). Male gender (OR 1.34), coagulopathy (3.05), congestive heart failure (2.36), diabetes mellitus (1.80), obesity (1.61), systemic neoplasia (1.57), chronic lung disease (1.52), and hypertension (1.21) increased the risk for PJI. Behavioral risk factors comprised alcohol abuse (2.95), immunosuppressive therapy (2.81), steroid therapies (1.88), and tobacco (1.82). Infectious risk factors included surgical site infections (6.14), postoperative urinary tract infections (2.85), and prior joint infections (2.15). Rheumatoid arthritis, posttraumatic native joint disease, high National Nosocomial Infections Surveillance (NNIS) system surgical patient index score, prior joint operation, American Society of Anesthesiologists score ≥ 3 and obesity were also signiicantly associated with higher risk of PJI. Osteoarthritis and blood transfusion were protective factors. Conclusions The main risk factors for PJI in each category were male gender, coagulopathy, alcohol abuse, surgical site infection (highest score) and high NNIS system surgical patient index score. Protective factors were age, female gender in TKA, osteoarthritis and blood transfusion. Optimization of modiiable risk factors for PJI should be attempted in clinical practice. Level of evidence II.

Background:Most people would prefer to die at home as opposed to hospital; therefore, understanding mortality patterns by place of death is essential for health resources allocation.Aim:We examined trends and risk factors for hospital death in conditions needing palliative care in a country without integrated palliative care.Design:This is a death certificate study. We examined factors associated with hospital death using logistic regression.Setting/participants:All adults (1,045,381) who died between 2003 and 2012 in Portugal were included. We identified conditions needing palliative care from main causes of death: cancer, heart/cerebrovascular, renal, liver, respiratory and neurodegenerative diseases, dementia/Alzheimer’s/senility and HIV/AIDS.Results:Conditions needing palliative care were responsible for 70.7% deaths (N = 738,566, median age 80); heart and cerebrovascular diseases (43.9%) and cancer (32.2%) accounted for most. There was a trend towards hospital death (standardised percentage: 56.3% in 2003, 66.7% in 2012; adjusted odds ratio: 1.04, 95% confidence interval: 1.04–1.04). Hospital death risk was higher for those aged 18–39 years (3.46, 3.25–3.69 vs aged 90+), decreasing linearly with age; lower in dementia/Alzheimer’s/senility versus cancer (0.13, 0.13–0.13); and higher for the married and in HIV/AIDS (3.31, 3.00–3.66). Effects of gender, working status, weekday and month of death, hospital beds availability, urbanisation level and deprivation were small.Conclusion:The upward hospital death trend and fact that being married are risk factors for hospital death suggest that a reliance on hospitals may coexist with a tradition of extended family support. The sustainability of this model needs to be assessed within the global transition pattern in where people die.

The length of hospital stay (LOS) is an important measure of efficiency in the use of hospital resources. Acute Myocardial Infarction (AMI), as one of the diseases with higher mortality and LOS variability in the OECD countries, has been studied with predominant use of administrative data, particularly on mortality risk adjustment, failing investigation in the resource planning and specifically in LOS. This paper presents results of a predictive model for extended LOS (LOSE - above 75th percentile of LOS) using both administrative and clinical data, namely laboratory data, in order to develop a decision support system. Laboratory and administrative data of a Portuguese hospital were included, using logistic regression to develop this predictive model. A model with three laboratory data and seven administrative data variables (six comorbidities and age ≥ 69 years), with excellent discriminative ability and a good calibration, was obtained. The model validation shows also good results. Comorbidities were relevant predictors, mainly diabetes with complications, showing the highest odds of LOSE (OR = 37,83; p = 0,001). AMI patients with comorbidities (diabetes with complications, cerebrovascular disease, shock, respiratory infections, pulmonary oedema), with pO2 above level, aged 69 years or older, with cardiac dysrhythmia, neutrophils above level, pO2 below level, and prothrombin time above level, showed increased risk of extended LOS. Our findings are consistent with studies that refer these variables as predictors of increased risk.

IntroductionThere is growing concern about the aggressiveness of cancer care at the end of life (ACCEoL), defined as overly aggressive treatments that compromise the quality of life at its end. Recognising the most affected patients is a cornerstone to improve oncology care. Our aim is to identify factors associated with ACCEoL for patients with cancer dying in hospitals.MethodsAll adult patients with cancer who died in public hospitals in mainland Portugal (January 2010 to December 2015), identified from the hospital morbidity database. This database provided individual clinical and demographic data. We obtained hospital and region-level variables from a survey and National Statistics. The primary outcome is a composite ACCEoL measure of 16 indicators. We used multilevel random effects logistic regression modelling (p<0·05).ResultsWe included 92 155 patients: median age 73 years; 62% male; 53% with metastatic disease. ACCEoL prevalence was 71% (95% CI 70% to 71%). The most prevalent indicators were >14 days in the hospital (43%, 42–43) and surgery (28%, 28–28) in the last 30 days. Older age (p<0·001), breast cancer (OR 0·83; 95% CI 0·76 to 0·91), and metastatic disease (0·54; 95% CI 0·50 to 0·58) were negatively associated with ACCEoL. In contrast, higher Deyo-Charlson Comorbidity Index (p<0·001), gastrointestinal and haematological malignancies (p<0·001), and death at cancer centre (1·31; 95% CI 1·01 to 1·72) or hospital with medical oncology department (1·29; 95% CI 1·02 to 1·63) were positively associated with ACCEoL. There was no association between hospital palliative care services at the hospital of death and ACCEoL.ConclusionClinical factors related to a better understanding of disease course are associated with ACCEoL reduction. Patients with more comorbidities and gastrointestinal malignancies might represent groups with complex needs, and haematological patients may be at increased risk because of unpredictable prognosis. Improvement of hospital palliative care services could help reduce ACCEoL, particularly in cancer centres and hospitals with medical oncology department, as those services are usually under-resourced, thus reaching few.