Israel Medical Association Journal

Background: Prognostication is complex in patients critically ill with coronavirus disease 2019 (COVID-19).

Objectives: To describe the natural history of ventilated critical COVID-19 patients.

Methods: Due to our legal milieu, active withdrawal of care is not permitted, providing an opportunity to examine the natural history of ventilated critical COVID-19 patients. This retrospective cohort included COVID-19 ICU patients who required mechanical ventilation. Respiratory and laboratory parameters were followed from initiation of mechanical ventilation for 14 days or until extubation, death or tracheostomy.

Results: A total of 112 patients were included in the analysis. Surviving patients were younger than non-survivors (62 years [range 54–69] vs. 66 years [range 62–71], P = 0.01). Survivors had a shorter time to intubation, shorter ventilation duration, and longer hospital stay. Respiratory parameters at intubation were not predictive of mortality. Nevertheless, on ventilation day 10, many of the ventilatory parameters were significantly better in survivors. Regarding laboratory parameters, neutrophil counts were significantly higher in non-survivors on day 1 and C-reactive protein levels were significantly lower in survivors on day 10. Modeling using a generalized estimating equation showed small dynamic differences in ventilatory parameters predictive of survival.

Conclusions: In ventilated COVID-19 patients when there is no active care withdrawal, prognostication may be possible after a week; however, differences between survivors and non-survivors remain small.

Background: Frequent readmissions significantly contribute to health care costs as well as work load in internal medicine wards.

Objective: To develop a simple scoring method that includes basic demographic and medical characteristics of  elderly patients in internal medicine wards, which would allow prediction of readmission within 3 months of discharge.

Methods: We conducted a retrospective observational study of 496 hospitalized patients using data collected from discharge letters in the computerized archives. Univariate and multivariate logistic regression analyses were performed and factors that were significantly associated with readmission were selected to construct a scoring tool. Validity was assessed in a cohort of 200 patients.

Results: During a 2 year follow-up 292 patients were readmitted at least once within 3 months of discharge. Age 80 or older, any degree of impaired cognition, nursing home residence, congestive heart failure, and creatinine level > 1.5 mg/dl were found to be strong predictors of readmission. The presence of each variable was scored as 1. A score of 3 or higher in the derivation and validation cohorts corresponded with a positive predictive value of 80% and 67%, respectively, when evaluating the risk of rehospitalization.

Conclusions: We propose a practical, readily available five-item scoring tool that allows prediction of most unplanned readmissions within 3 months. The strength of this scoring tool, as compared with previously published scores, is its simplicity and straightforwardness.