The E-POSSUM is a good tool for predicting mortality, and the only efficient scoring system for predicting morbidity after major colorectal surgery in the elderly.
Cisplatin-based chemotherapy is the standard treatment for patients with resected stage II and IIIA NSCLC. However, such therapy is used quite heterogeneously in daily practice and specific regimens, and the percentage of patients receiving adjuvant chemotherapy vary from standard recommendations. A prospective follow-up of daily practice regarding the use of adjuvant chemotherapy is warranted.
ObjectiveTo explore mortality risk factors for patients hospitalised with COVID-19 in a critical care unit (CCU) or a hospital care unit (HCU).DesignRetrospective cohort analysis using the French national (Programme de médicalisation des systèmes d’information) database.SettingAny public or private hospital in France.Participants98 366 patients admitted with COVID-19 for more than 1 day during the first semester of 2020 were included. The underlying conditions were retrieved for all contiguous stays.Main outcome measuresIn-hospital mortality and associated risk factors were assessed using frailty Cox models.ResultsAmong the 98 366 patients included, 25 765 (26%) were admitted to a CCU. The median age was 66 (IQR: 55–76) years in CCUs and 74 (IQR: 57–85) years in HCUs. Age was the main risk factor of death in both CCUs and HCUs, with adjusted HRs (aHRs) in CCUs increasing from 1.60 (95% CI 1.35 to 1.88) for 46 to 65 years to 8.17 (95% CI 6.86 to 9.72) for ≥85 years. In HCUs, the aHR associated with age was more than two times higher. The gender was not significantly associated with death, aHR 1.03 (95% CI 0.98 to 1.09, p=0.2693) in CCUs. Most of the underlying chronic conditions were risk factors for death, including malignant neoplasm (CCU: 1.34 (95% CI 1.25 to 1.43); HCU: 1.41 (95% CI 1.35 to 1.47)), cirrhosis without transplant (1.41 (95% CI 1.22 to 1.64); 1.27 (95% CI 1.12 to 1.45)) and dementia (1.30 (95% CI 1.16 to 1.46); 1.07 (95% CI 1.03 to 1.12)).ConclusionThis analysis confirms the role of age as the major risk factor of death in patients with COVID-19 irrespective to admission to critical care and therefore supports the current vaccination policies targeting older individuals.
Background The outbreak of a SARS‐CoV‐2 resulted in a massive afflux of patients in hospital and intensive care units with many challenges. Blood transfusion was one of them regarding both blood banks (safety, collection, and stocks) and consumption (usual care and unknown specific demand of COVID‐19 patients). The risk of mismatch was sufficient to plan blood transfusion restrictions if stocks became limited. Study design and methods Analyses of blood transfusion in a tertiary hospital and blood collection in the referring blood bank between February 24 and May 31, 2020. Results Withdrawal of elective surgery and non‐urgent care and admission of 2291 COVID‐19 patients reduced global activity by 33% but transfusion by 17% only. Only 237 (10.3) % of COVID‐19 patients required blood transfusion, including 45 (2.0%) with acute bleeding. Lockdown and cancellation of mobile collection resulted in an 11% reduction in blood donation compared to 2019. The ratio of reduction in blood transfusion to blood donation remained positive and stocks were slightly enhanced. Discussion Reduction of admissions due to SARS‐CoV‐2 pandemic results only in a moderate decrease of blood transfusion. Incompressible blood transfusions concern urgent surgery, acute bleeding (including some patients with COVID‐19, especially under high anticoagulation), or are supportive for chemotherapy‐induced aplasia or chronic anemia. Lockdown results in a decrease of blood donation by cancellation of mobile donation but with little impact on a short period by mobilization of usual donors. No mismatch between demand and donation was evidenced and no planned restriction to blood transfusion was necessary.
BackgroundCOVID-19 infection is less severe among children than among adults; however, some patients require hospitalization and even critical care. Using data from the French national medico-administrative database, we estimated the risk factors for critical care unit (CCU) admissions among pediatric COVID-19 hospitalizations, the number and characteristics of the cases during the successive waves from January 2020 to August 2021 and described death cases.MethodsWe included all children (age < 18) hospitalized with COVID-19 between January 1st, 2020, and August 31st, 2021. Follow-up was until September 30th, 2021 (discharge or death). Contiguous hospital stays were gathered in “care sequences.” Four epidemic waves were considered (cut off dates: August 11th 2020, January 1st 2021, and July 4th 2021). We excluded asymptomatic COVID-19 cases, post-COVID-19 diseases, and 1-day-long sequences (except death cases). Risk factors for CCU admission were assessed with a univariable and a multivariable logistic regression model in the entire sample and stratified by age, whether younger than 2.ResultsWe included 7,485 patients, of whom 1988 (26.6%) were admitted to the CCU. Risk factors for admission to the CCU were being younger than 7 days [OR: 3.71 95% CI (2.56–5.39)], being between 2 and 9 years old [1.19 (1.00–1.41)], pediatric multisystem inflammatory syndrome (PIMS) [7.17 (5.97–8.6)] and respiratory forms [1.26 (1.12–1.41)], and having at least one underlying condition [2.66 (2.36–3.01)]. Among hospitalized children younger than 2 years old, prematurity was a risk factor for CCU admission [1.89 (1.47–2.43)]. The CCU admission rate gradually decreased over the waves (from 31.0 to 17.8%). There were 32 (0.4%) deaths, of which the median age was 6 years (IQR: 177 days–15.5 years).ConclusionSome children need to be more particularly protected from a severe evolution: newborns younger than 7 days old, children aged from 2 to 13 years who are more at risk of PIMS forms and patients with at least one underlying medical condition.
Aim: Since beds are unavailable, we prospectively investigated whether early hospital discharge will be safe and useful in patients hospitalized for COVID-19, regardless of their need for home oxygen therapy. Population and Methods: Extending the initial inclusion criteria, 62 patients were included and 51 benefited from home telemonitoring, mainly assessing clinical parameters (blood pressure, heart rate, respiratory rate, dyspnea, temperature) and peripheral saturation (SpO2) at follow-up. Results: 47% of the patients were older than 65 years; 63% needed home oxygen therapy and/or presented with more than one comorbidity. At home, the mean time to dyspnea and tachypnea resolutions ranged from 21 to 24 days. The mean oxygen-weaning duration was 13.3 ± 10.4 days, and the mean SpO2 was 95.7 ± 1.6%. The nurses and/or doctors managed 1238 alerts. Two re-hospitalizations were required, related to transient chest pain or pulmonary embolism, but no death occurred. Patient satisfaction was good, and 743 potential days of hospitalization were saved for other patients. Conclusion: The remote monitoring of vital parameters and symptoms is safe, allowing for early hospital discharge in patients hospitalized for COVID-19, whether or not home oxygen therapy was required. Oxygen tapering outside the hospital allowed for a greater reduction in hospital stay. Randomized controlled trials are necessary to confirm this beneficial effect.
<b><i>Introduction:</i></b> The coronavirus disease 2019 (COVID-19) pandemic continues to have great impacts on the care of non-COVID-19 patients. This was especially true during the first epidemic peak in France, which coincided with the national lockdown. The aim of this study was to identify whether a decrease in stroke admissions occurred in spring 2020, by analyzing the evolution of all stroke admissions in France from January 2019 to June 2020. <b><i>Methods:</i></b> We conducted a nationwide cohort study using the French national database of hospital admissions (Information Systems Medicalization Program) to extract exhaustive data on all hospitalizations in France with at least one stroke diagnosis between January 1, 2019, and June 30, 2020. The primary endpoint was the difference in the slope gradients of stroke hospitalizations between pre-epidemic, epidemic peak, and post-epidemic peak phases. Modeling was carried out using Bayesian techniques. <b><i>Results:</i></b> Stroke hospitalizations dropped from March 10, 2020 (slope gradient: −11.70), and began to rise again from March 22 (slope gradient: 2.090) to May 7. In total, there were 23,873 stroke admissions during the period March–April 2020, compared to 29,263 at the same period in 2019, representing a decrease of 18.42%. The percentage change was −15.63%, −25.19%, −18.62% for ischemic strokes, transient ischemic attacks, and hemorrhagic strokes, respectively. <b><i>Discussion/Conclusion:</i></b> Stroke hospitalizations in France experienced a decline during the first lockdown period, which cannot be explained by a sudden change in stroke incidence. This decline is therefore likely to be a direct, or indirect, result of the COVID-19 pandemic.
Background and Purpose: The COVID-19 pandemic continues to have great impacts on the care of non-COVID-19 patients. This was especially true during the first epidemic peak in France, which coincided with the national lockdown (17 March 2020 to 10 May 2020). Patients with serious and urgent disease like stroke may have experienced a degradation of care, or may have been hesitant to seek healthcare during this period. The aim of this study was to identify, on a national level, whether a decrease in stroke admissions occurred in spring 2020, by analyzing the evolution of all stroke admissions in France from January 2019 to June 2020. Methods: We conducted a nationwide cohort study using the French national database of hospital admissions (PMSI) to extract exhaustive data on all hospitalizations in France with at least one stroke diagnosis between 1 January 2019 and 30 June 2020. The primary endpoint was the difference in the slope gradients of stroke hospitalizations between pre-epidemic, epidemic peak and post-epidemic periods. Modeling was carried out using Bayesian techniques. Results: Stroke hospitalizations dropped from 10 March 2020 (slope gradient: -11.70), and began to rise again from 22 March (slope gradient: 2.090) to 7 May. In total, there were 23 873 stroke admissions during the period March-April 2020, compared to 29 263 at the same period in 2019, representing a decrease of 18.42%. The percentage change was -15.63%, -25.19%, -18.62% for ischemic strokes, transient ischemic attacks, and hemorrhagic strokes, respectively. In spatial models of French departments, the incidence of COVID-19 explained the ratio of stroke hospitalizations. Conclusions: Stroke hospitalizations in France experienced a decline during the first lockdown period, which cannot be explained by a sudden change in stroke incidence. This decline is therefore likely to be a direct, or indirect, result of the COVID-19 pandemic.
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