Browsing by Subject "ICU"

Now showing 1 - 10 of 11
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    Beyond Biomarkers: Machine Learning in Diagnosing Acute Kidney Injury
    (Mayo Clinic, 2019-05) Molitoris, Bruce A.; Medicine, School of Medicine
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    Biomarkers of Delirium Duration and Delirium Severity in the ICU
    (Wolters Kluwer, 2020-03) Khan, Babar A.; Perkins, Anthony J.; Prasad, Nagendra K.; Shekhar, Anantha; Campbell, Noll L.; Gao, Sujuan; Wang, Sophia; Khan, Sikandar H.; Marcantonio, Edward R.; Twigg, Homer L., III.; Boustani, Malaz A.; Medicine, School of Medicine
    Objectives: Both delirium duration and delirium severity are associated with adverse patient outcomes. Serum biomarkers associated with delirium duration and delirium severity in ICU patients have not been reliably identified. We conducted our study to identify peripheral biomarkers representing systemic inflammation, impaired neuroprotection, and astrocyte activation associated with delirium duration, delirium severity, and in-hospital mortality. Design: Observational study. Setting: Three Indianapolis hospitals. Patients: Three-hundred twenty-one critically ill delirious patients. Interventions: None. Measurements and main results: We analyzed the associations between biomarkers collected at delirium onset and delirium-/coma-free days assessed through Richmond Agitation-Sedation Scale/Confusion Assessment Method for the ICU, delirium severity assessed through Confusion Assessment Method for the ICU-7, and in-hospital mortality. After adjusting for age, gender, Acute Physiology and Chronic Health Evaluation II score, Charlson comorbidity score, sepsis diagnosis and study intervention group, interleukin-6, -8, and -10, tumor necrosis factor-α, C-reactive protein, and S-100β levels in quartile 4 were negatively associated with delirium-/coma-free days by 1 week and 30 days post enrollment. Insulin-like growth factor-1 levels in quartile 4 were not associated with delirium-/coma-free days at both time points. Interleukin-6, -8, and -10, tumor necrosis factor-α, C-reactive protein, and S-100β levels in quartile 4 were also associated with delirium severity by 1 week. At hospital discharge, interleukin-6, -8, and -10 retained the association but tumor necrosis factor-α, C-reactive protein, and S-100β lost their associations with delirium severity. Insulin-like growth factor-1 levels in quartile 4 were not associated with delirium severity at both time points. Interleukin-8 and S-100β levels in quartile 4 were also associated with higher in-hospital mortality. Interleukin-6 and -10, tumor necrosis factor-α, and insulin-like growth factor-1 were not found to be associated with in-hospital mortality. Conclusions: Biomarkers of systemic inflammation and those for astrocyte and glial activation were associated with longer delirium duration, higher delirium severity, and in-hospital mortality. Utility of these biomarkers early in delirium onset to identify patients at a higher risk of severe and prolonged delirium, and delirium related complications during hospitalization needs to be explored in future studies.
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    The CAM-ICU-7 Delirium Severity Scale: A Novel Delirium Severity Instrument for Use in the Intensive Care Unit
    (Wolters Kluwer, 2017-05) Khan, Babar A.; Perkins, Anthony J.; Gao, Sujuan; Hui, Siu L.; Campbell, Noll L.; Farber, Mark O.; Chlan, Linda L.; Boustani, Malaz A.; Medicine, School of Medicine
    OBJECTIVES: Delirium severity is independently associated with longer hospital stays, nursing home placement, and death in patients outside the ICU. Delirium severity in the ICU is not routinely measured because the available instruments are difficult to complete in critically ill patients. We designed our study to assess the reliability and validity of a new ICU delirium severity tool, the Confusion Assessment Method for the ICU-7 delirium severity scale. DESIGN: Observational cohort study. SETTING: Medical, surgical, and progressive ICUs of three academic hospitals. PATIENTS: Five hundred eighteen adult (≥ 18 yr) patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patients received the Confusion Assessment Method for the ICU, Richmond Agitation-Sedation Scale, and Delirium Rating Scale-Revised-98 assessments. A 7-point scale (0-7) was derived from responses to the Confusion Assessment Method for the ICU and Richmond Agitation-Sedation Scale items. Confusion Assessment Method for the ICU-7 showed high internal consistency (Cronbach's α = 0.85) and good correlation with Delirium Rating Scale-Revised-98 scores (correlation coefficient = 0.64). Known-groups validity was supported by the separation of mechanically ventilated and nonventilated assessments. Median Confusion Assessment Method for the ICU-7 scores demonstrated good predictive validity with higher odds (odds ratio = 1.47; 95% CI = 1.30-1.66) of in-hospital mortality and lower odds (odds ratio = 0.8; 95% CI = 0.72-0.9) of being discharged home after adjusting for age, race, gender, severity of illness, and chronic comorbidities. Higher Confusion Assessment Method for the ICU-7 scores were also associated with increased length of ICU stay (p = 0.001). CONCLUSIONS: Our results suggest that Confusion Assessment Method for the ICU-7 is a valid and reliable delirium severity measure among ICU patients. Further research comparing it to other delirium severity measures, its use in delirium efficacy trials, and real-life implementation is needed to determine its role in research and clinical practice.
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    Clinical features and prognostic factors of intensive and non-intensive 1014 COVID-19 patients: an experience cohort from Alahsa, Saudi Arabia
    (BioMed Central, 2021-05-24) Alhumaid, Saad; Al Mutair, Abbas; Al Alawi, Zainab; Al Salman, Khulud; Al Dossary, Nourah; Omar, Ahmed; Alismail, Mossa; Al Ghazal, Ali M.; Jubarah, Mahdi Bu; Al Shaikh, Hanan; Al Mahdi, Maher M.; Alsabati, Sarah Y.; Philip, Dayas K.; Alyousef, Mohammed Y.; Al Brahim, Abdulsatar H.; Al Athan, Maitham S.; Alomran, Salamah A.; Ahmed, Hatim S.; Al-Shammari, Haifa; Elhazmi, Alyaa; Rabaan, Ali A.; Al-Tawfiq, Jaffar A.; Al-Omari, Awad; Medicine, School of Medicine
    COVID-19 is a worldwide pandemic and has placed significant demand for acute and critical care services on hospitals in many countries.
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    Coronavirus disease 2019-associated nephropathy in an African American patient: a case report and review of the literature
    (BMC, 2023-04-07) Dhillon, Vijaypal S.; Alkashash, Ahmad; Viquez‑Beita, Karolina; Pathology and Laboratory Medicine, School of Medicine
    Background: Acute kidney injury is now recognized as a common complication of coronavirus disease 2019, affecting up to 46% of patients, with acute tubular injury as the most common etiology. Recently, we have seen an increase in cases of collapsing glomerulonephritis in patients with coronavirus disease 2019, also known as coronavirus disease 2019-associated nephropathy. It has been noted to be seen with a higher incidence in African American patients who are carriers of the APOL1 variant allele. Case presentation: A 47-year-old African American male with a past medical history of asthma presented to the emergency department with complaints of intermittent chest pain, shortness of breath, and worsening confusion. On admission, he was found to be hemodynamically stable, but labs were significant for elevated creatinine and blood urea nitrogen, signifying acute kidney injury. He was admitted and taken for emergent dialysis. During his hospitalization, he was found to be positive for coronavirus disease 2019. Renal biopsy was done, which showed collapsing glomerulopathy, and the patient continues to require outpatient dialysis after discharge. Conclusion: Collapsing glomerulonephritis has emerged as a complication in patients with coronavirus disease 2019. This condition should be particularly suspected in African American patients who present with acute kidney injury, nephrotic-range proteinuria, and who are positive for coronavirus disease 2019. Current treatment options are limited to supportive treatment and renal replacement therapy. More clinical cases and trials are needed to better understand and improve therapeutic outcomes in these patients.
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    The Critical Care Recovery Center: An Innovative Collaborative Care Model for ICU Survivors
    (Wolters, 2015-03) Khan, Babar A.; Lasiter, Sue; Boustani, Malaz A.; School of Nursing
    Five million Americans require admission to ICUs annually owing to life-threatening illnesses. Recent medical advances have resulted in higher survival rates for critically ill patients, who often have significant cognitive, physical, and psychological sequelae, known as postintensive care syndrome (PICS). This growing population threatens to overwhelm the current U.S. health care system, which lacks established clinical models for managing their care. Novel innovative models are urgently needed. To this end, the pulmonary/critical care and geriatrics divisions at the Indiana University School of Medicine joined forces to develop and implement a collaborative care model, the Critical Care Recovery Center (CCRC). Its mission is to maximize the cognitive, physical, and psychological recovery of ICU survivors. Developed around the principles of implementation and complexity science, the CCRC opened in 2011 as a clinical center with a secondary research focus. Care is provided through a pre-CCRC patient and caregiver needs assessment, an initial diagnostic workup visit, and a follow-up visit that includes a family conference. With its sole focus on the prevention and treatment of PICS, the CCRC represents an innovative prototype aimed at modifying post–critical illness morbidities and improving the ICU survivor's quality of life.
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    Factors associated with poor outcomes among hospitalized patients with COVID-19: Experience from a MERS-CoV referral hospital
    (Elsevier, 2021-10) Barry, Mazin; Alotaibi, Muath; Almohaya, Abdulellah; Aldrees, Abdulwahab; AlHijji, Ali; Althabit, Nouf; Alhasani, Sara; Akkielah, Layan; AlRajhi, Abdulaziz; Nouh, Thamer; Temsah, Mohamad-Hani; Al-Tawfiq, Jaffar A.; Medicine, School of Medicine
    BACKGROUND: Coronavirus disease 2019 (COVID-19) has resulted in millions of deaths, including more than 6000 deaths in the Kingdom of Saudi Arabia (KSA). Identifying key predictors of intensive care unit (ICU) admission and mortality among infected cases would help in identifying individuals at risk to optimize their care. We aimed to determine factors of poor outcomes in hospitalized patients with COVID-19 in a large academic hospital in Riyadh, KSA that serves as a Middle East Respiratory Syndrome coronavirus (MERS-CoV) referral center. METHODS: This is a single-center retrospective cohort study of hospitalized patients between March 15 and August 31, 2020. The study was conducted at King Saud University Medical City (KSUMC). COVID-19 infection was confirmed using real-time reverse transcriptase polymerase chain reaction (RT-PCR) for SARS-COV-2. Demographic data, clinical characteristics, laboratory, radiological features, and length of hospital stay were obtained. Poor outcomes were, admission to ICU, need for invasive mechanical ventilation (IMV), and in-hospital all-cause mortality. RESULTS: Out of 16,947 individuals tested in KSUMC, 3480 (20.5%) tested positive for SARS-CoV-2 and of those 743 patients (21%) were hospitalized. There were 62% males, 77% were younger than 65 years. Of all cases, 204 patients (28%) required ICU admission, 104 (14%) required IMV, and 117 (16%) died in hospital. In bivariate analysis, multiple factors were associated with mortality among COVID-19 patients. Further multivariate analysis revealed the following factors were associated with mortality: respiratory rate more than 24/min and systolic blood pressure <90 mmHg in the first 24h of presentation, lymphocyte count <1 × 109/L and aspartate transaminase level >37 units/L in the first 48 h of presentation, while a RT-PCR cycle threshold (Ct) value ≤24 was a predictor for IMV. CONCLUSION: Variable factors were identified as predictors of different outcomes among COVID-19 patients. The only predictor of IMV was a low initial Ct values of SARS-CoV-2 PCR. The presence of tachypnea, hypotension, lymphopenia, and elevated AST in the first 48h of presentation were independently associated with mortality. This study provides possible independent predictors of mortality and invasive mechanical ventilation. The data may be helpful in the early identification of high-risk COVID-19 patients in areas endemic with MERS-CoV.
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    Machine learning decision tree algorithm role for predicting mortality in critically ill adult COVID-19 patients admitted to the ICU
    (Elsevier, 2022) Elhazmi, Alyaa; Al-Omari, Awad; Sallam, Hend; Mufti, Hani N.; Rabie, Ahmed A.; Alshahrani, Mohammed; Mady, Ahmed; Alghamdi, Adnan; Altalaq, Ali; Azzam, Mohamed H.; Sindi, Anees; Kharaba, Ayman; Al-Aseri, Zohair A.; Almekhlafi, Ghaleb A.; Tashkandi, Wail; Alajmi, Saud A.; Faqihi, Fahad; Alharthy, Abdulrahman; Al-Tawfiq, Jaffar A.; Melibari, Rami Ghazi; Al-Hazzani, Waleed; Arabi, Yaseen M.; Medicine, School of Medicine
    Background: Coronavirus disease-19 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is currently a major cause of intensive care unit (ICU) admissions globally. The role of machine learning in the ICU is evolving but currently limited to diagnostic and prognostic values. A decision tree (DT) algorithm is a simple and intuitive machine learning method that provides sequential nonlinear analysis of variables. It is simple and might be a valuable tool for bedside physicians during COVID-19 to predict ICU outcomes and help in critical decision-making like end-of-life decisions and bed allocation in the event of limited ICU bed capacities. Herein, we utilized a machine learning DT algorithm to describe the association of a predefined set of variables and 28-day ICU outcome in adult COVID-19 patients admitted to the ICU. We highlight the value of utilizing a machine learning DT algorithm in the ICU at the time of a COVID-19 pandemic. Methods: This was a prospective and multicenter cohort study involving 14 hospitals in Saudi Arabia. We included critically ill COVID-19 patients admitted to the ICU between March 1, 2020, and October 31, 2020. The predictors of 28-day ICU mortality were identified using two predictive models: conventional logistic regression and DT analyses. Results: There were 1468 critically ill COVID-19 patients included in the study. The 28-day ICU mortality was 540 (36.8 %), and the 90-day mortality was 600 (40.9 %). The DT algorithm identified five variables that were integrated into the algorithm to predict 28-day ICU outcomes: need for intubation, need for vasopressors, age, gender, and PaO2/FiO2 ratio. Conclusion: DT is a simple tool that might be utilized in the ICU to identify critically ill COVID-19 patients who are at high risk of 28-day ICU mortality. However, further studies and external validation are still required.
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    Mediating ICU patient situation-awareness with visual and tactile notifications
    (2016-03-29) Srinivas, Preethi; Bolchini, Davide; Faiola, Anthony; Brady, Erin; Khan, Babar; Doebbeling, Bradley
    Healthcare providers in hospital intensive care units (ICUs) maintain patient situation awareness by following task management and communication practices. They create and manipulate several paper-based and digital information sources, with the overall aim to constantly inform themselves and their colleagues of dynamically evolving patient conditions. However, when increased communication means that healthcare providers potentially interrupt each other, enhanced patient-situation awareness comes at a price. Prior research discusses both the use of technology to support increased communication and its unintended consequence of (wanted and unwanted) notification interruptions. Using qualitative research techniques, I investigated work practices that enhance the patient-situation awareness of physicians, fellows, residents, nurses, students, and pharmacists in a medical ICU. I used the Locales Framework to understand the observed task management and communication work practices. In this study, paper notes were observed to act as transitional artifacts that are later digitized to organize and coordinate tasks, goals, and patient-centric information at a team and organizational level. Non digital information is often not immediately digitized, and only select information is communicated between certain ICU team members through synchronous mechanisms such as face-to-face or telephone conversations. Thus, although ICU providers are exceptionally skilled at working together to improve a critically ill patient’s condition, the use of paper-based artifacts and synchronous communication mechanisms induces several interruptions while contextually situating a clinical team for patient care. In this dissertation, I also designed and evaluated a mobile health technology tool, known as PANI (Patient-centered Notes and Information Manager), guided by the Locales framework and the participatory involvement of ICU healthcare providers as co designers. PANI-supported task management induces minimal interruptions by: (1) rapidly generating, managing, and sharing clinical notes and action-items among clinicians and (2) supporting the collaboration and communication needs of clinicians through a novel visual and tactile notification system. The long-term contribution of this research suggests guidelines for designing mobile health technology interventions that enhance ICU patient situation-awareness and reduce unwanted interruptions to clinical workflow.
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    Preventing Postoperative Delirium After Major Noncardiac Thoracic Surgery—A Randomized Clinical Trial
    (Wiley, 2018) Khan, Babar A.; Perkins, Anthony J.; Campbell, Noll L.; Gao, Sujuan; Khan, Sikandar H.; Wang, Sophia; Fuchita, Mikita; Weber, Daniel J.; Zarzaur, Ben L.; Boustani, Malaz A.; Kesler, Kenneth; Medicine, School of Medicine
    Objectives: To assess the efficacy of haloperidol in reducing postoperative delirium in individuals undergoing thoracic surgery. Design: Randomized double-blind placebo-controlled trial. Setting: Surgical intensive care unit (ICU) of tertiary care center. Participants: Individuals undergoing thoracic surgery (N=135). Intervention: Low-dose intravenous haloperidol (0.5 mg three times daily for a total of 11 doses) administered postoperatively. Measurements: The primary outcome was delirium incidence during hospitalization. Secondary outcomes were time to delirium, delirium duration, delirium severity, and ICU and hospital length of stay. Delirium was assessed using the Confusion Assessment Method for the ICU and delirium severity using the Delirium Rating Scale-Revised. Results: Sixty-eight participants were randomized to receive haloperidol and 67 placebo. No significant differences were observed between those receiving haloperidol and those receiving placebo in incident delirium (n=15 (22.1%) vs n=19 (28.4%); p = .43), time to delirium (p = .43), delirium duration (median 1 day, interquartile range (IQR) 1-2 days vs median 1 day, IQR 1-2 days; p = .71), delirium severity, ICU length of stay (median 2.2 days, IQR 1-3.3 days vs median 2.3 days, IQR 1-4 days; p = .29), or hospital length of stay (median 10 days, IQR 8-11.5 days vs median 10 days, IQR 8-12 days; p = .41). In the esophagectomy subgroup (n = 84), the haloperidol group was less likely to experience incident delirium (n=10 (23.8%) vs n=17 (40.5%); p = .16). There were no differences in time to delirium (p = .14), delirium duration (median 1 day, IQR 1-2 days vs median 1 day, IQR 1-2 days; p = .71), delirium severity, or hospital length of stay (median 11 days, IQR 10-12 days vs median days 11, IQR 10-15 days; p = .26). ICU length of stay was significantly shorter in the haloperidol group (median 2.8 days, IQR 1.1-3.8 days vs median 3.1 days, IQR 2.1-5.1 days; p = .03). Safety events were comparable between the groups. Conclusion: Low-dose postoperative haloperidol did not reduce delirium in individuals undergoing thoracic surgery but may be efficacious in those undergoing esophagectomy.