Intraoperative cardiac arrests in adults undergoing noncardiac surgery: incidence, risk factors, and survival outcome.

BACKGROUND: Intraoperative cardiac arrest (ICA) is a rare but potentially catastrophic event. There is a paucity of recent epidemiological data on the incidence and risk factors for ICA. The objective of this study was to assess the incidence, risk factors, and survival outcome of ICAs in adults undergoing noncardiac surgery. METHODS: The authors analyzed prospectively collected data for all noncardiac cases in the American College of Surgeons National Surgical Quality Improvement Program database from the years 2005 to 2007 (n = 362,767). RESULTS: The incidence of ICA was 7.22 per 10,000 surgeries. After adjustment for American Society of Anesthesiologists physical status and other covariates, the odds of ICA increased progressively with the amount of transfusion (adjusted odds ratios = 2.51, 7.59, 11.40, and 29.68 for those receiving 1-3, 4-6, 7-9, and ≥ 10 units of erythrocytes, respectively). Other significant risk factors for ICA were emergency surgery (adjusted odds ratio = 2.04, 95% CI = 1.45-2.86) and being functionally dependent presurgery (adjusted odds ratio = 2.33, 95% CI = 1.69-3.22). Of the 262 patients with ICA, 116 (44.3%) died within 24 h, and 164 (62.6%) died within 30 days. CONCLUSIONS: Intraoperative blood loss as indicated by the amount of transfusion was the most important predictor of ICA. The urgency of surgery and the preoperative composite indicators of health such as American Society of Anesthesiologists status and functional status were other important risk factors. The high case fatality suggests that primary prevention might be the key to reducing mortality from ICA.

Mortality and renal outcomes of patients with severe COVID-19 treated in a provisional intensive care unit.

COVID-19 has created an enormous health crisis and this spring New York City had a severe outbreak that pushed health and critical care resources to the limit. A lack of adequate space for mechanically ventilated patients induced our hospital to convert operating rooms into critical care areas (OR-ICU). A large number of COVID-19 will develop acute kidney injury that requires renal replacement therapy (RRT). We included 116 patients with COVID-19 who required mechanical ventilation and were cared for in our OR-ICU. At 90 days and at discharge 35 patients died (30.2%). RRT was required by 45 of the 116 patients (38.8%) and 18 of these 45 patients (40%) compared to 17 with no RRT (23.9%, ns) died during hospitalization and after 90 days. Only two of the 27 patients who required RRT and survived required RRT at discharge and 90 days. When defining renal recovery as a discharge serum creatinine within 150% of baseline, 68 of 78 survivors showed renal recovery (87.2%). Survival was similar to previous reports of patients with severe COVID-19 for patients cared for in provisional ICUs compared to standard ICUs. Most patients with severe COVID-19 and AKI are likely to recover full renal function.

Predicting Poor Outcome of COVID-19 Patients on the Day of Admission with the COVID-19 Score.

BACKGROUND: COVID-19 may result in multiorgan failure and death. Early detection of patients at risk may allow triage and more intense monitoring. The aim of this study was to develop a simple, objective admission score, based on laboratory tests, that identifies patients who are likely going to deteriorate. METHODS: This is a retrospective cohort study of all COVID-19 patients admitted to a tertiary academic medical center in New York City during the COVID-19 crisis in spring 2020. The primary combined endpoint included intubation, stage 3 acute kidney injury (AKI), or death. Laboratory tests available on admission in at least 70% of patients (and age) were included for univariate analysis. Tests that were statistically or clinically significant were then included in a multivariate binary logistic regression model using stepwise exclusion. 70% of all patients were used to train the model, and 30% were used as an internal validation cohort. The aim of this study was to develop and validate a model for COVID-19 severity based on biomarkers. RESULTS: Out of 2545 patients, 833 (32.7%) experienced the primary endpoint. 53 laboratory tests were analyzed, and of these, 47 tests (and age) were significantly different between patients with and without the endpoint. The final multivariate model included age, albumin, creatinine, C-reactive protein, and lactate dehydrogenase. The area under the ROC curve was 0.850 (CI [95%]: 0.813, 0.889), with a sensitivity of 0.800 and specificity of 0.761. The probability of experiencing the primary endpoint can be calculated as p=e (-2.4475+0.02492age - 0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH)/1+e (-2.4475+ 0.02492age - 0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH). CONCLUSIONS: Our study demonstrated that poor outcome in COVID-19 patients can be predicted with good sensitivity and specificity using a few laboratory tests. This is useful for identifying patients at risk during admission.