Transition matrices model as a way to better understand and predict intra-hospital pathways of covid-19 patients.

Since January 2020, the SARS-CoV-2 pandemic has severely affected hospital systems worldwide. In Europe, the first 3 epidemic waves (periods) have been the most severe in terms of number of infected and hospitalized patients. There are several descriptions of the demographic and clinical profiles of patients with COVID-19, but few studies of their hospital pathways. We used transition matrices, constructed from Markov chains, to illustrate the transition probabilities between different hospital wards for 90,834 patients between March 2020 and July 2021 managed in Paris area. We identified 3 epidemic periods (waves) during which the number of hospitalized patients was significantly high. Between the 3 periods, the main differences observed were: direct admission to ICU, from 14 to 18%, mortality from ICU, from 28 to 24%, length of stay (alive patients), from 9 to 7 days from CH and from 18 to 10 days from ICU. The proportion of patients transferred from CH to ICU remained stable. Understanding hospital pathways of patients is crucial to better monitor and anticipate the impact of SARS-CoV-2 pandemic on health system.

Impact of the SARS-COV-2 outbreak on epidemiology and management of major traumain France: a registry-based study (the COVITRAUMA study).

BACKGROUND: Emerging evidence suggests that the reallocation of health care resources during the COVID-19 pandemic negatively impacts health care system. This study describes the epidemiology and the outcome of major trauma patients admitted to centers in France during the first wave of the COVID-19 outbreak. METHODS: This retrospective observational study included all consecutive trauma patients aged 15 years and older admitted into 15 centers contributing to the TraumaBase® registry during the first wave of the SARS-CoV-2 pandemic in France. This COVID-19 trauma cohort was compared to historical cohorts (2017-2019). RESULTS: Over a 4 years-study period, 5762 patients were admitted between the first week of February and mid-June. This cohort was split between patients admitted during the first 2020 pandemic wave in France (pandemic period, 1314 patients) and those admitted during the corresponding period in the three previous years (2017-2019, 4448 patients). Trauma patient demographics changed substantially during the pandemic especially during the lockdown period, with an observed reduction in both the absolute numbers and proportion exposed to road traffic accidents and subsequently admitted to traumacenters (348 annually 2017-2019 [55.4% of trauma admissions] vs 143 [36.8%] in 2020 p < 0.005). The in-hospital observed mortality and predicted mortality during the pandemic period were not different compared to the non-pandemic years. CONCLUSIONS: During this first wave of COVID-19 in France, and more specifically during lockdown there was a significant reduction of patients admitted to designated trauma centers. Despite the reallocation and reorganization of medical resources this reduction prevented the saturation of the trauma rescue chain and has allowed maintaining a high quality of care for trauma patients.

A nomogram to predict the risk of unfavourable outcome in COVID-19: a retrospective cohort of 279 hospitalized patients in Paris area.

OBJECTIVE: To identify predictive factors of unfavourable outcome among patients hospitalized for COVID-19. METHODS: We conducted a monocentric retrospective cohort study of COVID-19 patients hospitalized in Paris area. An unfavourable outcome was defined as the need for artificial ventilation and/or death. Characteristics at admission were analysed to identify factors predictive of unfavourable outcome using multivariable Cox proportional hazard models. Based on the results, a nomogram to predict 14-day probability of poor outcome was proposed. RESULTS: Between March 15th and April 14th, 2020, 279 COVID-19 patients were hospitalized after a median of 7 days after the first symptoms. Among them, 88 (31.5%) patients had an unfavourable outcome: 48 were admitted to the ICU for artificial ventilation, and 40 patients died without being admitted to ICU. Multivariable analyses retained age, overweight, polypnoea, fever, high C-reactive protein, elevated us troponin-I, and lymphopenia as risk factors of an unfavourable outcome. A nomogram was established with sufficient discriminatory power (C-index 0.75), and proper consistence between the prediction and the observation. CONCLUSION: We identified seven easily available prognostic factors and proposed a simple nomogram for early detection of patients at risk of aggravation, in order to optimize clinical care and initiate specific therapies. KEY MESSAGES Since novel coronavirus disease 2019 pandemic, a minority of patients develops severe respiratory distress syndrome, leading to death despite intensive care. Tools to identify patients at risk in European populations are lacking. In our series, age, respiratory rate, overweight, temperature, C-reactive protein, troponin and lymphocyte counts were risk factors of an unfavourable outcome in hospitalized adult patients. We propose an easy-to-use nomogram to predict unfavourable outcome for hospitalized adult patients to optimize clinical care and initiate specific therapies.

Preliminary pragmatic lessons from the SARS-CoV-2 pandemic in France.

The first wave of the SARS-CoV-2 pandemic required an unprecedented and historic increase in critical care capacity on a global scale in France. Authors and members from the ACUTE and REANIMATION committees of the French Society of Anaesthesia and Intensive Care (SFAR) wished to share experience and insights gained during the first weeks of this pandemic. These were summarised following the World Health Organization Response Checklist and detailed according to the subsequent subheadings: 1. Command and Control, 2. Communication, 3. Safety and Security, 4. Triage, 5. Surge Capacity, 6. Continuity of essential services, 7. Human resources, 8. Logistics and supply management, 9. Training/Preparation, 10. Psychological comfort for patients and next of kin, 11. Learning and 12. Post disaster recovery. These experience-based recommendations, consensual across all members from both committees of our national society, establish a practical framework for medical teams, either spared by the first wave of severe COVID patients or preparing for the second one.