Discussing protein requirements of intensive care UNIT (ICU) patients

Abstract Background Point-of-care lung ultrasound (LU) is an established tool in the first assessment of patients with coronavirus disease (COVID-19). Purpose of this study was to evaluate the value of lung ultrasound in COVID-19 intensive care unit (ICU) patients in predicting clinical course and outcome. Methods We analyzed lung ultrasound score (LUS) of all COVID-19 patients admitted from March 2020 to December 2020 to the Internal Intensive Care Unit, Ludwig-Maximilians-University (LMU) of Munich. LU was performed according to a standardized protocol at ICU admission and in case of clinical deterioration with the need for intubation. A normal lung scores 0 points, the worst LUS has 24 points. Patients were stratified in a low (0–12 points) and a high (13–24 points) lung ultrasound score group. Results The study included 42 patients, 69% of them male. The most common comorbidities were hypertension (81%) and obesity (57%). The values of pH (7.42 ± 0.09 vs 7.35 ± 0.1; p = 0.047) and paO2 (107 [80–130] vs 80 [66–93] mmHg; p = 0.034) were significantly reduced in patients of the high LUS group. Furthermore, the duration of ventilation (12.5 [8.3–25] vs 36.5 [9.8–70] days; p = 0.029) was significantly prolonged in this group. Patchy subpleural thickening (n = 38; 90.5%) and subpleural consolidations (n = 23; 54.8%) were present in most patients. Pleural effusion was rare (n = 4; 9.5%). The median total LUS was 11.9 ± 3.9 points. In case of clinical deterioration with the need for intubation, LUS worsened significantly compared to baseline LU. Twelve patients died during the ICU stay (29%). There was no difference in survival in both LUS groups (75% vs 66.7%, p = 0.559). Conclusions LU can be a useful monitoring tool to predict clinical course but not outcome of COVID-19 ICU patients and can early recognize possible deteriorations.

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Should the CIWA-Ar be the standard monitoring strategy for alcohol withdrawal syndrome in the intensive care unit?

Addiction Science & Clinical Practice ◽

10.1186/s13722-021-00226-w ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Tessa L. Steel ◽

Shewit P. Giovanni ◽

Sarah C. Katsandres ◽

Shawn M. Cohen ◽

Kevin B. Stephenson ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Alcohol Withdrawal ◽

Withdrawal Syndrome ◽

Alcohol Withdrawal Syndrome ◽

Patient Characteristics ◽

Response To Treatment ◽

Alternative Measure ◽

Icu Patients ◽

Verbal Responses

Abstract Background The Clinical Institute Withdrawal Assessment for Alcohol-Revised (CIWA-Ar) is commonly used in hospitals to titrate medications for alcohol withdrawal syndrome (AWS), but may be difficult to apply to intensive care unit (ICU) patients who are too sick or otherwise unable to communicate. Objectives To evaluate the frequency of CIWA-Ar monitoring among ICU patients with AWS and variation in CIWA-Ar monitoring across patient demographic and clinical characteristics. Methods The study included all adults admitted to an ICU in 2017 after treatment for AWS in the Emergency Department of an academic hospital that standardly uses the CIWA-Ar to assess AWS severity and response to treatment. Demographic and clinical data, including Richmond Agitation-Sedation Scale (RASS) assessments (an alternative measure of agitation/sedation), were obtained via chart review. Associations between patient characteristics and CIWA-Ar monitoring were tested using logistic regression. Results After treatment for AWS, only 56% (n = 54/97) of ICU patients were evaluated using the CIWA-Ar; 94% of patients had a documented RASS assessment (n = 91/97). Patients were significantly less likely to receive CIWA-Ar monitoring if they were intubated or identified as Black. Conclusions CIWA-Ar monitoring was used inconsistently in ICU patients with AWS and completed less often in those who were intubated or identified as Black. These hypothesis-generating findings raise questions about the utility of the CIWA-Ar in ICU settings. Future studies should assess alternative measures for titrating AWS medications in the ICU that do not require verbal responses from patients and further explore the association of race with AWS monitoring.

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Beta-Lactams Toxicity in the Intensive Care Unit: An Underestimated Collateral Damage?

Microorganisms ◽

10.3390/microorganisms9071505 ◽

2021 ◽

Vol 9 (7) ◽

pp. 1505

Author(s):

Claire Roger ◽

Benjamin Louart

Keyword(s):

Risk Factors ◽

Intensive Care Unit ◽

Intensive Care ◽

Clinical Manifestations ◽

Acute Interstitial Nephritis ◽

Convulsive Status Epilepticus ◽

Beta Lactam ◽

Beta Lactams ◽

Drug Induced ◽

Icu Patients

Beta-lactams are the most commonly prescribed antimicrobials in intensive care unit (ICU) settings and remain one of the safest antimicrobials prescribed. However, the misdiagnosis of beta-lactam-related adverse events may alter ICU patient management and impact clinical outcomes. To describe the clinical manifestations, risk factors and beta-lactam-induced neurological and renal adverse effects in the ICU setting, we performed a comprehensive literature review via an electronic search on PubMed up to April 2021 to provide updated clinical data. Beta-lactam neurotoxicity occurs in 10–15% of ICU patients and may be responsible for a large panel of clinical manifestations, ranging from confusion, encephalopathy and hallucinations to myoclonus, convulsions and non-convulsive status epilepticus. Renal impairment, underlying brain abnormalities and advanced age have been recognized as the main risk factors for neurotoxicity. In ICU patients, trough concentrations above 22 mg/L for cefepime, 64 mg/L for meropenem, 125 mg/L for flucloxacillin and 360 mg/L for piperacillin (used without tazobactam) are associated with neurotoxicity in 50% of patients. Even though renal complications (especially severe complications, such as acute interstitial nephritis, renal damage associated with drug induced hemolytic anemia and renal obstruction by crystallization) remain rare, there is compelling evidence of increased nephrotoxicity using well-known nephrotoxic drugs such as vancomycin combined with beta-lactams. Treatment mainly relies on the discontinuation of the offending drug but in the near future, antimicrobial optimal dosing regimens should be defined, not only based on pharmacokinetics/pharmacodynamic (PK/PD) targets associated with clinical and microbiological efficacy, but also on PK/toxicodynamic targets. The use of dosing software may help to achieve these goals.

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Contamination of Propofol Infusions in the Intensive Care Unit: Incidence and Clinical Significance

Anaesthesia and Intensive Care ◽

10.1177/0310057x9802600205 ◽

1998 ◽

Vol 26 (2) ◽

pp. 162-164 ◽

Cited By ~ 27

Author(s):

S. A. R. Webb ◽

B. Roberts ◽

F. X. Breheny ◽

C. L. Golledge ◽

P. D. Cameron ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Observational Study ◽

Nosocomial Infection ◽

Wound Infection ◽

Clinical Significance ◽

Low Grade ◽

Clinical Infection ◽

Icu Patients

Epidemics of bacteraemia and wound infection have been associated with the infusion of bacterially contaminated propofol administered during anaesthesia. We conducted an observational study to determine the incidence and clinical significance of administration of potentially contaminated propofol to patients in an ICU setting. One hundred patients received a total of 302 infusions of propofol. Eighteen episodes of possible contamination of propofol syringes were identified, but in all cases contamination was by a low-grade virulence pathogen. There were no episodes of clinical infection or colonization which could be attributed to the administration of contaminated propofol. During the routine use of propofol to provide sedation in ICU patients the risk of nosocomial infection secondary to contamination of propofol is extremely low.

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Comparing Vitamin A and Moist Chamber in Preventing Ocular Surface Disorders

Clinical Nursing Research ◽

10.1177/1054773817695618 ◽

2017 ◽

Vol 27 (6) ◽

pp. 714-729 ◽

Cited By ~ 2

Author(s):

Hassan Babamohamadi ◽

Monir Nobahar ◽

Jalaladin Razi ◽

Raheb Ghorbani

Keyword(s):

Clinical Trial ◽

Intensive Care Unit ◽

Intensive Care ◽

Vitamin A ◽

Ocular Surface ◽

Slight Reduction ◽

Moist Chamber ◽

Icu Patients ◽

Schirmer’S Test

The present study was conducted to determine the effectiveness of vitamin A eye ointment (VAEO) and moist chamber (MC) in preventing ocular surface disorders (OSD) in intensive care unit (ICU) patients. A total of 38 eligible patients were selected for participation in the present clinical trial. All the patients were randomly administered VAEO in one eye every 6 hr for 5 days and had a polyethylene cover (PC) placed on their other eye to create an MC that was replaced every 12 hr as well. The results of Schirmer’s test also increased by 2.06 mm in the VAEO group ( p < .001), while they showed a slight reduction by 0.15 mm in the MC group ( p = .669). VAEO was more effective in preventing OSD in ICU patients than MC and is, therefore, recommended to be used as a method of preventing OSD.

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Comparison of Non–Intensive Care Unit (ICU) versus ICU Rates of Catheter-Associated Urinary Tract Infection in Community Hospitals

Infection Control and Hospital Epidemiology ◽

10.1086/671000 ◽

2013 ◽

Vol 34 (7) ◽

pp. 744-747 ◽

Cited By ~ 18

Author(s):

Sarah S. Lewis ◽

Lauren P. Knelson ◽

Rebekah W. Moehring ◽

Luke F. Chen ◽

Daniel J. Sexton ◽

...

Keyword(s):

Intensive Care Unit ◽

Urinary Tract Infection ◽

Intensive Care ◽

Urinary Tract ◽

Tract Infection ◽

Community Hospitals ◽

Icu Patients ◽

Important Target

We describe and compare the epidemiology of catheter-associated urinary tract infection (CAUTI) occurring in non-intensive care unit (ICU) versus ICU wards in a network of community hospitals over a 2-year period. Overall, 72% of cases of CAUTI occurred in non-ICU patients, which indicates that this population is an important target for dedicated surveillance and prevention efforts.

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Patterns of Antimicrobial Resistance Among Intensive Care Unit Patients of A Private Medical College Hospital in Dhaka

Bangladesh Journal of Medicine ◽

10.3329/bjmed.v25i2.25088 ◽

2015 ◽

Vol 25 (2) ◽

pp. 47-51 ◽

Cited By ~ 2

Author(s):

Quazi Tarikul Islam ◽

Md Mahmudur Rahman Siddiqui ◽

Farhana Raz ◽

Mohammad Asrafuzzaman ◽

Md Robed Amin

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Tracheal Aspirate ◽

College Hospital ◽

Icu Patients ◽

Gram Negative ◽

Pseudomonas Spp ◽

Medical College ◽

Acinetobacter Spp ◽

Klebsiella Spp

Because of importance of Hospital acquired infections (HAIs), it is critical to conduct surveillance studies to obtain the required data about the regional microorganisms and their susceptibility to antibiotics. This study to investigate antimicrobial resistance pattern among Intensive Care Unit (ICU) patients in a private medical college hospital setup. In a cross sectional study, 100 specimens from patients admitted in the ICU who had signs or symptoms of nosocomial infection were collected from 2012 - 2013. For each patient, samples of blood, urine, tracheal aspirate, sputum, wound swab, pus, and endotracheal tubes were obtained, cultured and analyzed with antibiogram. The most common primary diagnosis were aspiration pneumonia (49%) and UTI (20%) respectively. The most common locations for infection were tracheal aspirate (54%). The most frequent gram negative microorganisms derived from samples were Acinetobacter spp (29%), Klebsiella spp (26%) and Pseudomonas spp (18%). Klebsiella spp, Acinetobacter spp and Pseudomonas spp were most common resistant organisms among all. Klebsiella spp were resistant against Ceftriaxone (84.6%), Ceftazidime (82.6%), Amikacin (46.1%), Gentamicin (66.6%) and Quinolones (65-66.6%) respectively. Acinetobacter spp were resistant against Ceftriaxone (85%), Ceftazidime (88.8%), Cefotaxime (85.7%), Meropenem (79.3%),Amikacin (86.2%), Gentamicin (84.5%) and Quinolons (86.2-89.2%) respectively. Pseudomonas spp were resistant against Ceftriaxone (70.5%), Ceftazidime (66.6%), Amikacin (68.7%), Gentamicin (58.8%), Meropenem (52.9%) and Quinolones (81.2-86.6%) respectively. Meropenem was the most sensitive antibiotic against Klebsiella spp (84.6%) but Cotrimoxazole in case of Acinetobacter spp (60%) respectively. Escherichia coli were mostly isolated from urine, which was sensitive to Amikacin (73.3%) and Meropenem (86.6%) respectively. Gram-negative pathogens obtained from ICU patients in our settings show high resistance to antibiotics. Regular monitoring of the pattern of resistance of common pathogens in the ICUs is essential to up-to-date the use of rational antibiotics regiments.Bangladesh J Medicine Jul 2014; 25 (2) : 47-51

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Quality improvement of delirium status communication and documentation for intensive care unit patients during daily multidisciplinary rounds

BMJ Open Quality ◽

10.1136/bmjoq-2017-000239 ◽

2018 ◽

Vol 7 (2) ◽

pp. e000239 ◽

Cited By ~ 2

Author(s):

Krishna Aparanji ◽

Shreedhar Kulkarni ◽

Megan Metzke ◽

Yvonne Schmudde ◽

Peter White ◽

...

Keyword(s):

Intensive Care Unit ◽

Critical Care ◽

Intensive Care ◽

Tertiary Care ◽

Care Hospital ◽

Icu Patients ◽

Quality Metric ◽

Risk Of Mortality ◽

Simulation Based ◽

Multidisciplinary Rounds

Delirium is a key quality metric identified by The Society of Critical Care Medicine for intensive care unit (ICU) patients. If not recognised early, delirium can lead to increased length of stay, hospital and societal costs, ventilator days and risk of mortality. Clinical practice guidelines recommend ICU patients be assessed for delirium at least once per shift. An initial audit at our urban tertiary care hospital in Illinois, USA determined that delirium assessments were only being performed 31% of the time. Nurses completed simulation based education and were trained using delirium screening videos. After the educational sessions, delirium documentation increased from 40% (12/30) to 69% (41/59) (two-proportion test, p<0.01) for dayshift nurses and from 27% (8/30) to 61% (36/59) (two-proportion test, p<0.01) during the nightshift. To further increase the frequency of delirium assessments, the delirium screening tool was standardised and a critical care progress note was implemented that included a section on delirium status, management strategy and discussion on rounds. After the documentation changes were implemented, delirium screening during dayshift increased to 93% (75/81) (two-proportion test, p<0.01). Prior to this project, physicians were not required to document delirium screening. After the standardised critical care note was implemented, documentation by physicians was 95% (106/111). Standardising delirium documentation, communication of delirium status on rounds, in addition to education, improved delirium screening compliance for ICU patients.

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Middle meatal vs antral lavage cultures in intensive care unit patients

Otolaryngology ◽

10.1067/mhn.2002.123444 ◽

2002 ◽

Vol 126 (4) ◽

pp. 377-381 ◽

Cited By ~ 11

Author(s):

Stilianos E. Kountakis ◽

Ioannis G. Skoulas

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Prospective Study ◽

Medical Center ◽

Icu Patients

OBJECTIVE: The study goal was to compare endoscopically guided middle meatal cultures with cultures of antral lavage aspirate in intensive care unit (ICU) patients with sinusitis. METHODS: Prospective study of febrile ICU patients seen for sinusitis at a tertiary medical center. RESULTS: Of 31 antral lavages performed in 18 patients, 19 lavages yielded purulent or mucopurulent aspirate. Endoscopically guided middle meatal cultures yielded the same pathogen, as did cultures of the lavage aspirate in 4 (21%) of these 19 cases. The antral lavage was negative (absence of purulent/mucopurulent aspirate) in 12 cases, and of those, 5 (42%) of the 12 middle meatal cultures showed no growth (sensitivity = 21%, specificity = 58%, χ2-1.52, P = 0.218). CONCLUSION: Endoscopically guided middle meatal cultures did not correlate well with cultures from the antral lavage aspirate in febrile ICU patients evaluated for sinusitis.

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Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Comparative Machine Learning Study (Preprint)

10.2196/preprints.23508 ◽

2020 ◽

Author(s):

Sujeong Hur ◽

Ji Young Min ◽

Junsang Yoo ◽

Kyunga Kim ◽

Chi Ryang Chung ◽

...

Keyword(s):

Machine Learning ◽

Intensive Care Unit ◽

Patient Safety ◽

Intensive Care ◽

Predictive Value ◽

Prediction Models ◽

Support Vector ◽

Unplanned Extubation ◽

Electronic Health Record Data ◽

Icu Patients

BACKGROUND Patient safety in the intensive care unit (ICU) is one of the most critical issues, and unplanned extubation (UE) is considered as the most adverse event for patient safety. Prevention and early detection of such an event is an essential but difficult component of quality care. OBJECTIVE This study aimed to develop and validate prediction models for UE in ICU patients using machine learning. METHODS This study was conducted an academic tertiary hospital in Seoul. The hospital had approximately 2,000 inpatient beds and 120 intensive care unit (ICU) beds. The number of patients, on daily basis, was approximately 9,000 for the out-patient. The number of annual ICU admission was approximately 10,000. We conducted a retrospective study between January 1, 2010 and December 31, 2018. A total of 6,914 extubation cases were included. We developed an unplanned extubation prediction model using machine learning algorithms, which included random forest (RF), logistic regression (LR), artificial neural network (ANN), and support vector machine (SVM). For evaluating the model’s performance, we used area under the receiver operator characteristic curve (AUROC). Sensitivity, specificity, positive predictive value negative predictive value, and F1-score were also determined for each model. For performance evaluation, we also used calibration curve, the Brier score, and the Hosmer-Lemeshow goodness-of-fit statistic. RESULTS Among the 6,914 extubation cases, 248 underwent UE. In the UE group, there were more males than females, higher use of physical restraints, and fewer surgeries. The incidence of UE was more likely to occur during the night shift compared to the planned extubation group. The rate of reintubation within 24 hours and hospital mortality was higher in the UE group. The UE prediction algorithm was developed, and the AUROC for RF was 0.787, for LR was 0.762, for ANN was 0.762, and for SVM was 0.740. CONCLUSIONS We successfully developed and validated machine learning-based prediction models to predict UE in ICU patients using electronic health record data. The best AUROC was 0.787, which was obtained using RF. CLINICALTRIAL N/A

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