Publications by authors named "Amit Uppal"

Article Synopsis
  • - The study aimed to create a "Choosing Wisely in COVID-19" list to help reduce unnecessary tests and procedures during the pandemic, which could harm patients and expose staff to risks.
  • - Developed by a High Value Care Council at New York City Health + Hospitals, the list was created through staff input and a scoring process that prioritized evidence and harm prevention.
  • - Top recommendations included avoiding unnecessary intubation, central venous catheters, daily lab tests, routine x-rays, and bronchodilators when not needed, emphasizing high-value, evidence-based care.
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Background: Peripherally inserted central catheters (PICCs) are increasingly used for vascular access in inpatient settings. Compared to multilumen PICCs, single-lumen PICCs carry a lower rate of complications, including central-line-associated bloodstream infection and thrombosis. Despite this, multilumen PICCs are still overused.

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Introduction: Tracheostomy in patients with COVID-19 is a controversial and difficult clinical decision. We hypothesized that a recently validated COVID-19 Severity Score (CSS) would be associated with survival in patients considered for tracheostomy.

Methods: We reviewed 77 mechanically ventilated COVID-19 patients evaluated for decision for percutaneous dilational tracheostomy (PDT) from March to June 2020 at a public tertiary care center.

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Background: Reducing unnecessary routine laboratory testing is a Choosing Wisely® recommendation, and new areas of overuse were noted during the COVID-19 pandemic.

Objective: To reduce unnecessary repetitive routine laboratory testing for patients with COVID-19 during the pandemic across a large safety net health system.

Designs, Settings And Participants: This quality improvement initiative was initiated by the System High-Value Care Council at New York City Health + Hospitals (H + H), the largest public healthcare system in the United States consisting of 11 acute care hospitals.

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Objectives: To evaluate how key aspects of New York State Ventilator Allocation Guidelines (NYSVAG)-Sequential Organ Failure Assessment score criteria and ventilator time trials -might perform with respect to the frequency of ventilator reallocation and survival to hospital discharge in a simulated cohort of coronavirus disease (COVID-19) patients.

Methods: Single center retrospective observational and simulation cohort study of 884 critically ill COVID-19 patients undergoing ventilator allocation per NYSVAG.

Results: In total, 742 patients (83.

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Background: The COVID-19 pandemic overwhelmed New York City hospitals early in the pandemic. Shortages of ventilators and sedatives prompted tracheostomy earlier than recommended by professional societies. This study evaluates the impact of percutaneous dilational tracheostomy (PDT) in COVID+ patients on critical care capacity.

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Background: After the publication of a 2014 consensus statement regarding mass critical care during public health emergencies, much has been learned about surge responses and the care of overwhelming numbers of patients during the COVID-19 pandemic. Gaps in prior pandemic planning were identified and require modification in the midst of severe ongoing surges throughout the world.

Research Question: A subcommittee from The Task Force for Mass Critical Care (TFMCC) investigated the most recent COVID-19 publications coupled with TFMCC members anecdotal experience in order to formulate operational strategies to optimize contingency level care, and prevent crisis care circumstances associated with increased mortality.

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Objectives: To evaluate the impact of ICU surge on mortality and to explore clinical and sociodemographic predictors of mortality.

Design: Retrospective cohort analysis.

Setting: NYC Health + Hospitals ICUs.

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Unlabelled: To explore demographics, comorbidities, transfers, and mortality in critically ill patients with confirmed severe acute respiratory syndrome coronavirus 2.

Design: Retrospective cohort study.

Setting: Data were collected from a large tertiary care public hospital ICU that is part of the largest public healthcare network in the United States.

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New York City has emerged as the global epicenter for the coronavirus disease 2019 (COVID-19) pandemic. The city's public health system, New York City Health + Hospitals, has been key to the city's response because its vulnerable patient population is disproportionately affected by the disease. As the number of cases rose in the city, NYC Health + Hospitals carried out plans to greatly expand critical care capacity.

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In this work, we utilize a combination of free-text and structured data to build Acute Respiratory Distress Syndrome(ARDS) prediction models and ARDS phenotype clusters. We derived 'Patient Context Vectors' representing patientspecific contextual ARDS risk factors, utilizing deep-learning techniques on ICD and free-text clinical notes data. The Patient Context Vectors were combined with structured data from the first 24 hours of admission, such as vital signs and lab results, to build an ARDS patient prediction model and an ARDS patient mortality prediction model achieving AUC of 90.

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Background: Medical errors occur following handoff-related miscommunication. Data regarding the effect on patient-centered outcomes, specifically mortality, are lacking. Our objective was to investigate handoff-related mortality and the effect of duty-hour regulations.

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Rationale: To evaluate factors associated with palliative care consultation (PCC) in an urban public hospital.

Methods: A retrospective chart review of patients who died on inpatient medical services.

Results: Patients with a PCC were more likely to have a "do not resuscitate" (DNR) order at the time of death (p<0.

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Currently, no reliable noninvasive methods exist for monitoring the severity of in vivo cyanide (CN) toxicity, treatment, and resulting physiological changes. We developed a broadband diffuse optical spectroscopy (DOS) system to measure bulk tissue absorption and scattering. DOS was used to optically monitor CN toxicity and treatment with sodium nitrite (NaNO2).

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