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Sheehan KA, Shin S, Hall E, Mak DYF, Lapointe-Shaw L, Tang T, Marwaha S, Gandell D, Rawal S, Inouye S, Verma AA, Razak F. Characterizing medical patients with delirium: A cohort study comparing ICD-10 codes and a validated chart review method. PLoS One 2024; 19:e0302888. [PMID: 38739670 PMCID: PMC11090329 DOI: 10.1371/journal.pone.0302888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 04/15/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Delirium is a major cause of preventable mortality and morbidity in hospitalized adults, but accurately determining rates of delirium remains a challenge. OBJECTIVE To characterize and compare medical inpatients identified as having delirium using two common methods, administrative data and retrospective chart review. METHODS We conducted a retrospective study of 3881 randomly selected internal medicine hospital admissions from six acute care hospitals in Toronto and Mississauga, Ontario, Canada. Delirium status was determined using ICD-10-CA codes from hospital administrative data and through a previously validated chart review method. Baseline sociodemographic and clinical characteristics, processes of care and outcomes were compared across those without delirium in hospital and those with delirium as determined by administrative data and chart review. RESULTS Delirium was identified in 6.3% of admissions by ICD-10-CA codes compared to 25.7% by chart review. Using chart review as the reference standard, ICD-10-CA codes for delirium had sensitivity 24.1% (95%CI: 21.5-26.8%), specificity 99.8% (95%CI: 99.5-99.9%), positive predictive value 97.6% (95%CI: 94.6-98.9%), and negative predictive value 79.2% (95%CI: 78.6-79.7%). Age over 80, male gender, and Charlson comorbidity index greater than 2 were associated with misclassification of delirium. Inpatient mortality and median costs of care were greater in patients determined to have delirium by ICD-10-CA codes (5.8% greater mortality, 95% CI: 2.0-9.5 and $6824 greater cost, 95%CI: 4713-9264) and by chart review (11.9% greater mortality, 95%CI: 9.5-14.2% and $4967 greater cost, 95%CI: 4415-5701), compared to patients without delirium. CONCLUSIONS Administrative data are specific but highly insensitive, missing most cases of delirium in hospital. Mortality and costs of care were greater for both the delirium cases that were detected and missed by administrative data. Better methods of routinely measuring delirium in hospital are needed.
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Affiliation(s)
- Kathleen A. Sheehan
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Centre for Mental Health, University Health Network, Toronto, ON, Canada
| | - Saeha Shin
- St. Michael’s Hospital, Unity Health Network, Toronto, ON, Canada
| | - Elise Hall
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, Unity Health Network, Toronto, ON, Canada
| | - Denise Y. F. Mak
- St. Michael’s Hospital, Unity Health Network, Toronto, ON, Canada
| | - Lauren Lapointe-Shaw
- Department of Medicine, University of Toronto, Toronto ON, Canada
- Department of Medicine, University Health Network, Toronto, ON, Canada
| | - Terence Tang
- Department of Medicine, University of Toronto, Toronto ON, Canada
- Institute for Better Health, Trillium Health Partners, Mississauga, ON, Canada
| | - Seema Marwaha
- Department of Medicine, University of Toronto, Toronto ON, Canada
- Department of Medicine, Unity Health Network, Toronto, ON, Canada
| | - Dov Gandell
- Department of Medicine, University of Toronto, Toronto ON, Canada
- Department of Medicine, Sunnybrook Heatlh Sciences Centre, Toronto, ON, Canada
| | - Shail Rawal
- Department of Medicine, University of Toronto, Toronto ON, Canada
- Department of Medicine, University Health Network, Toronto, ON, Canada
| | - Sharon Inouye
- Aging Brain Center, Hebrew Senior Life, Boston, MA, United States of America
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States of America
| | - Amol A. Verma
- Department of Medicine, University of Toronto, Toronto ON, Canada
- Department of Medicine, Unity Health Network, Toronto, ON, Canada
| | - Fahad Razak
- Department of Medicine, University of Toronto, Toronto ON, Canada
- Department of Medicine, Unity Health Network, Toronto, ON, Canada
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Missett RM, Beig Zali S, Winograd J, Scemama de Gialluly P, Sabouri AS. Intraoperative Ultrasound-Guided Transversus Abdominis Plane Catheters Placed for Post-operative Analgesia Following Pedicled Transverse Rectus Abdominis Myocutaneous Flap Breast Reconstruction: A Case Report. Cureus 2023; 15:e39045. [PMID: 37323334 PMCID: PMC10266741 DOI: 10.7759/cureus.39045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/15/2023] [Indexed: 06/17/2023] Open
Abstract
Transverse rectus abdominis (TRAM) flap reconstruction of the breast is a procedure in which a flap of skin, fat, and underlying rectus abdominis muscle is used to reconstruct the breast. This procedure is commonly performed after mastectomy and results in significant pain at the donor abdominal site. We present this case of a 50-year-old female undergoing pedicled TRAM flap surgery in which ultrasound-guided transversus abdominis plane (TAP) catheters were placed intraoperatively, in a novel fashion: under ultrasound guidance, directly on the abdominal musculature, without overlying fat, subcutaneous tissue, or dressing. Our case-reported numeric pain scores ranged from 0-5/10 during postoperative days one to two. The patient's IV morphine requirement on postoperative days zero to two ranged between 1.34 mg to 2.6 mg per day, representing a significant decrease compared to literature-reported opioid consumption after such surgery. Her pain and opioid consumption increased significantly after catheter removal, suggesting the efficacy of our intraoperative TAP catheters.
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Affiliation(s)
- Richard M Missett
- Anesthesiology, Children's Hospital of Philadelphia, Philadelphia, USA
| | | | - Jonathan Winograd
- Plastic and Reconstructive Surgery, Massachusetts General Hospital, Boston, USA
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Impact of Alcohol Misuse on Requirements for Critical Care Services and Development of Hospital Delirium in Patients With COVID-19 pneumonia. Crit Care Explor 2023; 5:e0829. [PMID: 36713630 PMCID: PMC9876025 DOI: 10.1097/cce.0000000000000829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Alcohol misuse has been associated with increased morbidity in the setting of pulmonary infections, including the need for critical care resource utilization and development of delirium. How alcohol misuse impacts morbidity and outcomes among patients admitted with COVID-19 pneumonia is not well described. We sought to determine if alcohol misuse was associated with an increased need for critical care resources and development of delirium among patients hospitalized with COVID-19 pneumonia. DESIGN Retrospective cohort study. SETTING Twelve University of Colorado hospitals between March 2020 and April 2021. PATIENTS Adults with a COVID-19 diagnosis. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS The primary outcome was admission to the ICU. Secondary outcomes included need for mechanical ventilation, development of delirium, and in-hospital mortality. Alcohol misuse was defined by International Classification of Diseases, 10th Revision codes. Of 5,979 patients hospitalized with COVID-19, 26% required ICU admission and 15.4% required mechanical ventilation. Delirium developed in 4.5% and 10.5% died during hospitalization. Alcohol misuse was identified in 4%. In analyses adjusted for age, sex, body mass index, diabetes, and liver disease, alcohol misuse was associated with increased odds of ICU admission (adjusted odds ratio [aOR], 1.46; p < 0.01), mechanical ventilation (aOR, 1.43; p = 0.03), and delirium (aOR, 5.55; p < 0.01) compared with patients without misuse. Mortality rates were not associated with alcohol misuse alone, although the presence of both alcohol misuse and in-hospital delirium significantly increased odds of in-hospital death (aOR, 2.60; p = 0.04). CONCLUSIONS Among patients hospitalized with COVID-19, alcohol misuse was associated with increased utilization of critical care resources including ICU admission and mechanical ventilation. Delirium was an important modifiable risk factor associated with worse outcomes in hospitalized patients with alcohol misuse, including increased odds of death.
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Abstract
PURPOSE OF REVIEW Perioperative neurocognitive disorders (PNDs) are among the most frequent complications after surgery and are associated with considerable morbidity and mortality. We analysed the recent literature regarding risk assessment of PND. RECENT FINDINGS Certain genetic variants of the cholinergic receptor muscarinic 2 and 4, as well as a marked degree of frailty but not the kind of anaesthesia (general or spinal) are associated with the risk to develop postoperative delirium (POD). Models predict POD with a discriminative power, for example, area under the receiver operating characteristics curve between 0.52 and 0.94. SUMMARY Advanced age as well as preexisting cognitive, functional and sensory deficits remain to be the main risk factors for the development of PND. Therefore, aged patients should be routinely examined for both preexisting and new developing deficits, as recommended in international guidelines. Appropriate tests should have a high discrimination rate, be feasible to be administered by staff that do not require excessive training, and only take a short time to be practical for a busy outpatient clinic. Models to predict PND, should be validated appropriately (and externally if possible) and should not contain a too large number of predictors to prevent overfitting of models.
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