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1.
American Journal of Obstetrics and Gynecology ; 226(1):S772-S773, 2022.
Article in English | EMBASE | ID: covidwho-1588399

ABSTRACT

Objective: To evaluate the difference in time from hospital admission to delivery when undergoing inpatient versus outpatient cervical ripening with a transcervical Foley catheter. Study Design: This was a randomized controlled trial of patients with singleton pregnancies, Bishop Score ≤ 6 and at least 37 weeks’ gestation, undergoing labor induction at Sinai Hospital of Baltimore and Thomas Jefferson University Hospital. Patients were randomized to outpatient or inpatient cervical ripening with a Foley catheter. Inpatients received concurrent oxytocin. Outpatients returned 12 hours after Foley placement, and on arrival oxytocin was initiated if the balloon was still in place. Foleys were removed if in place after 12-18 hours, and labor induction initiated with oxytocin as needed. The primary outcome was the difference in time from admission to delivery. A maternal satisfaction survey was also administered. Unpaired t-tests, chi-square tests, and Fisher’s exact test were performed to estimate differences in outcomes between the inpatient and outpatient arms of the study. Results: Enrollment commenced January 2016 and continued until November 2020, after randomizing 30 patients (n=15 per group). The study was terminated prematurely due to low enrollment and temporary suspension during COVID-19. There was no significant difference in time from admission to delivery between outpatient and inpatient groups (14.5 ± 6.1 versus 18.9 ± 8.2 hours, P=.11). The total induction time was shorter for the inpatient group (24.9 ± 6.8 versus 17.3 ± 9.4 hours, P=.02). There were no differences in other maternal or neonatal outcomes (P>.05). Maternal satisfaction was similar between groups on a 1-10 scale (8.6 ± 1.7 versus 8.9 ± 1.0, P=.53), and all patients felt safe. Conclusion: No difference in the primary outcome of time from admission to delivery was noted between inpatient and outpatient cervical ripening with a Foley catheter;however, this may be a result of inadequate power related to early termination. Consistent with past studies, outpatient balloon cervical ripening appears to be safe, and overall satisfaction was high. [Formula presented] [Formula presented]

2.
Journal of the American Society of Nephrology ; 32:60, 2021.
Article in English | EMBASE | ID: covidwho-1489686

ABSTRACT

Background: Patients hospitalized with COVID-19 illness are at high risk for developing acute kidney injury (AKI) and have high mortality rates. Chronic kidney disease (CKD) and end stage renal disease (ESRD) are independent risk factors for COVID-19 disease severity and mortality. Our study compares mortality rates of hospitalized patients with COVID-19 illness who 1) develop AKI with baseline normal renal function, 2) develop AKI with baseline moderate-to-severe CKD stages 3 or 4, and 3) have ESRD. Methods: Consecutive patients admitted with COVID-19 illness referred to Nephrology with AKI or ESRD on dialysis were included. Retrospective data collected included: Demographics, medical history including CKD stage, labs, O2 therapy, AKI diagnosis (KDIGO), and renal replacement therapy (RRT). Chi-square test was used to evaluate the unadjusted association between CKD stage and mortality. Multivariate logistic regression models were constructed to estimate associations between CKD stage and mortality adjusting for potential confounders. Results: 166 patients were analyzed: 87 patients had AKI with baseline normal renal function (GFR > 60 ml/min (AKI-N), 41 patients had AKI on CKD Stage 3 or 4 (AKI-CKD3/4), and 38 patients had ESRD. Mechanical ventilation was used in 33[37.9%] AKI-N, 20[48.8%] AKI-CKD3/4, and 10[26.3%] ERSD patients, p = 0.069. Three [3.5%] AKI-N received iHD, and 9[10.3%] received CRRT/PIRRT. Six [14.6%] AKI-CKD3/4 received iHD and 7[17.1%] received CRRT/PIRRT. Of all AKI patients, 55.5% had Stage 3 AKI. 34[89.5%] ESRD patients received iHD and 2[5.3%] received PD. AKICKD3/ 4 were more likely to receive RRT than AKI-N, p = 0.035. Death occurred in 36[41.4%] AKI-N, 26[63.4%] AKI-CKD3/4, and 9[23.7%] ESRD patients, (p=0.001). Multivariate logistic regression modeling for mortality accounting for age, race, gender, diabetes mellitus, hypertension, obesity, and CHF revealed increased odds of mortality for AKI-CKD3/4 (OR=2.59, p=0.006) and decreased odds of mortality for ESRD patients (OR=0.5, p=0.001), compared to AKI-N. Conclusions: COVID-19 patients with ESRD had less mortality than AKI-N, while AKI-CKD3/4 had higher mortality than both ESRD and AKI-N patients. Prospective studies to determine specific criteria for early initiation of RRT in COVID-19 AKI patients are warranted, as it may decrease mortality especially in those with baseline CKD 3/4.

3.
Chest ; 158(4):A336, 2020.
Article in English | EMBASE | ID: covidwho-871832

ABSTRACT

SESSION TITLE: Chest Infections Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: October 18-21, 2020 PURPOSE: The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in more than 300,000 deaths worldwide as of June 1, 2020. Risk factors associated with mortality have been described in prior studies, however, data is still limited in many clinical settings. The purpose of this study is to identify clinical predictors of mortality in hospitalized adult patients with COVID-19 in an urban hospital in Baltimore. METHODS: Retrospective, single-center analysis of hospitalized adult patients (age >18) with confirmed COVID-19 on Nucleic Acid Amplification testing who had been discharged or had died by May 15, 2020. Demographics, comorbidities, travel history, Rothman Index (RI), admission vital signs, laboratory, and imaging were compared between survivors and non-survivors. Unpaired t-tests and chi-square tests were utilized to determine unadjusted associations between clinical indicators and mortality. Multivariate logistic regression models were used to determine associations simultaneously adjusting for multiple clinical indicators. RESULTS: Of the 111 patients that were included in the study, 35 (32%) patients died and 76 (68%) patients were discharged either to home or a facility. Mean age for the mortality group was 71 years and 63 years for the discharged group (p=0.008). Of the 5 patients with recent travel history, 80% died [p=0.03]. In the mortality group, more than half (53.7%) were from a facility (p=0.001). 40.9% of patients in the mortality group had hyperlipidemia (p=0.08), 29.6% had hypertension (p=0.56), and 33.3% had diabetes (p=0.7). A higher mean temperature of 38.4 C on admission was observed in the mortality group compared to 37.9 C for the discharged group (p=0.03). In addition, among the admission laboratory values, mean procalcitonin and c-reactive protein (CRP) were higher in the mortality group (procalcitonin 1.97 vs 0.59 [p=0.03];CRP 165 vs.109.5 [p=0.005]). Initial mean RI was lower in the mortality group 45.4 compared to 64.7 for the discharged group (p=0.0003). In the multivariate logistic regression model, only age remained significant (p=0.01). CONCLUSIONS: More indicators of mortality have been identified in our study compared to prior studies: age, residing in facility, recent travel, temperature on admission, procalcitonin, CRP and RI. Only age was statistically significant in multivariate logistic regression modeling. Comorbidities (e.g. hypertension and diabetes) did not play a significant role in mortality. CLINICAL IMPLICATIONS: Age was the only factor in multivariate analysis that predicted mortality in COVID-19. Other factors that were significant in univariate analysis may not have reached significance in multivariate models due to limited sample size. However, these factors can potentially be used to develop a mortality risk calculator to help determine early ICU admission and aggressive treatment. DISCLOSURES: No relevant relationships by Christopher D'Adamo, source=Web Response No relevant relationships by Lee-Gardie Jean, source=Web Response No relevant relationships by Nicole Rapista, source=Web Response No relevant relationships by Sauradeep Sarkar, source=Web Response No relevant relationships by Sahib Singh, source=Web Response No relevant relationships by Shashi Yalamanchili, source=Web Response

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