Machine learning and predictive models: 2 years of Sars-CoV-2 pandemic in a single-center retrospective analysis.

BACKGROUND: Since January 2020, coronavirus disease 19 (COVID-19) has rapidly spread all over the world. An early assessment of illness severity is crucial for the stratification of patients in order to address them to the right intensity path of care. We performed an analysis on a large cohort of COVID-19 patients (n=581) hospitalized between March 2020 and May 2021 in our intensive care unit (ICU) at Policlinico Riuniti di Foggia hospital. Through an integration of the scores, demographic data, clinical history, laboratory findings, respiratory parameters, a correlation analysis, and the use of machine learning our study aimed to develop a model to predict the main outcome. METHODS: We deemed eligible for analysis all adult patients (age >18 years old) admitted to our department. We excluded all the patients with an ICU length of stay inferior to 24 h and the ones that declined to participate in our data collection. We collected demographic data, medical history, D-dimers, NEWS2, and MEWS scores on ICU admission and on ED admission, PaO2/FiO2 ratio on ICU admission, and the respiratory support modalities before the orotracheal intubation and the intubation timing (early vs late with a 48-h hospital length of stay cutoff). We further collected the ICU and hospital lengths of stay expressed in days of hospitalization, hospital location (high dependency unit, HDU, ED), and length of stay before and after ICU admission; the in-hospital mortality; and the in-ICU mortality. We performed univariate, bivariate, and multivariate statistical analyses. RESULTS: SARS-CoV-2 mortality was positively correlated to age, length of stay in HDU, MEWS, and NEWS2 on ICU admission, D-dimer value on ICU admission, early orotracheal intubation, and late orotracheal intubation. We found a negative correlation between the PaO2/FiO2 ratio on ICU admission and NIV. No significant correlations with sex, obesity, arterial hypertension, chronic obstructive pulmonary disease, chronic kidney disease, cardiovascular disease, diabetes mellitus, dyslipidemia, and neither MEWS nor NEWS on ED admission were observed. Considering all the pre-ICU variables, none of the machine learning algorithms performed well in developing a prediction model accurate enough to predict the outcome although a secondary multivariate analysis focused on the ventilation modalities and the main outcome confirmed how the choice of the right ventilatory support with the right timing is crucial. CONCLUSION: In our cohort of COVID patients, the choice of the right ventilatory support at the right time has been crucial, severity scores, and clinical judgment gave support in identifying patients at risk of developing a severe disease, comorbidities showed a lower weight than expected considering the main outcome, and machine learning method integration could be a fundamental statistical tool in the comprehensive evaluation of such complex diseases.

Acute Parkinsonism in a Patient with Spinal Cord Injury: A Case Report.

Parkinson's disease (PD) is the most common cause of parkinsonism, a clinical syndrome that includes bradykinesia, tremor, and postural instability. Secondary causes of parkinsonism include chronic traumatic encephalopathy. However, clear physiopathologic association between spinal cord injury (SCI) and PD has not been well described yet. We describe a rare/unusual case of a patient with C7-D1 fracture/listhesis who, 12 days after the trauma, developed a progressive cognitive impairment together with mandibular tremor. Seven days after the onset of symptoms, because of the persistence of mandibular tremor and Glasgow Coma Scale (GCS) score of 4, therapy with L-DOPA/benserazide was started, which resulted in gradual reduction of symptoms and complete recovery of consciousness. This could be the first report of PD appearing only 12 days after an SCI in the acute stage. Early differential diagnosis on the first manifestations of this kind of symptoms should be considered in patients with SCI to set up the right therapy essential for improving the outcome and preventing devastating consequences. This might also provide insights into the potential pathophysiologic responses of the brain after primary (immediate) and secondary (delayed) damages.

Successful Treatment of Klebsiella pneumoniae NDM Sepsis and Intestinal Decolonization with Ceftazidime/Avibactam Plus Aztreonam Combination in a Patient with TTP Complicated by SARSCoV-2 Nosocomial Infection.

Carbapenem-resistant Enterobacteriaceae (CRE) are a serious public health threat. Infections due to these organisms are associated with significant morbidity and mortality. Among them, metallo-ß-lactamases (MBLs)-producing Klebsiella pneumoniae are of global concern today. The ceftazidime/avibactam combination and the ceftazidime/avibactam + aztreonam combination currently represent the most promising antibiotic strategies to stave off these kinds of infections. We describe the case of a patient affected by thrombotic thrombocytopenic purpura (TTP) admitted in our ICU after developing a hospital-acquired SarsCoV2 interstitial pneumonia during his stay in the hematology department. His medical conditions during his ICU stay were further complicated by a K. Pneumoniae NDM sepsis. To our knowledge, the patient had no risk factors for multidrug-resistant bacteria exposure or contamination during his stay in the hematology department. During his stay in the ICU, we treated the sepsis with a combination therapy of ceftazidime/avibactam + aztreonam. The therapy solved his septic state, allowing for a progressive improvement in his general condition. Moreover, we noticed that the negativization of the hemocultures was also associated to a decontamination of his known rectal colonization. The ceftazidime/avibactam + aztreonam treatment could not only be a valid therapeutic option for these kinds of infections, but it could also be considered as a useful tool in selected patients' intestinal decolonizations.

SARS-CoV-2 pneumonia succesfully treated with cpap and cycles of tripod position: a case report.

BACKGROUND: Pneumonia induced by 2019 Coronavirus (COVID-19) is characterized by hypoxemic respiratory failure that may present with a broad spectrum of clinical phenotypes. At the beginning, patients may have normal lung compliance and be responsive to noninvasive ventilatory support, such as CPAP. However, the transition to more severe respiratory failure - Severe Acute Respiratory Syndrome (SARS-CoV-2), necessitating invasive ventilation is often abrupt and characterized by a severe V/Q mismatch that require cycles of prone positioning. The aim of this case is to report the effect on gas exchange, respiratory mechanics and hemodynamics of tripod (or orthopneic sitting position) used as an alternative to prone position in a patient with mild SARS-CoV-2 pneumonia ventilated with helmet CPAP. CASE PRESENTATION: A 77-year-old awake and collaborating male patient with mild SARS-CoV-2 pneumonia and ventilated with Helmet CPAP, showed sudden worsening of gas exchange without dyspnea. After an unsuccessful attempt of prone positioning, we alternated three-hours cycles of semi-recumbent and tripod position, still keeping him in CPAP. Arterial blood gases (PaO2/FiO2, PaO2, SaO2, PaCO2 and A/a gradient), respiratory (VE, VT, RR) and hemodynamic parameters (HR, MAP) were collected in the supine and tripod position. Cycles of tripod position were continued for 3 days. The patient had a clinically important improvement in arterial blood gases and respiratory parameters, with stable hemodynamic and was successfully weaned and discharged to ward 10 days after pneumonia onset. CONCLUSIONS: Tripod position during Helmet CPAP can be applied safely in patients with mild SARS-CoV-2 pneumonia, with improvement of oxygenation and V/Q matching, thus reducing the need for intubation.