Applicability of Paediatric Index of Mortality 2 Score to Predict Outcome in Children Admitted to Paediatric Intensive Care Unit

Introduction: Research on critically ill children admitted to the intensive care unit has shown the usefulness of Paediatric Index of Mortality 2 (PIM2) score at admission to predict outcome. This study was conducted to estimate PIM2 score in children admitted to Paediatric Intensive Care Unit and its correlation with clinical outcome. Methods: This prospective observational study was conducted in children of age group one month to 18 years admitted to the paediatric intensive care unit of a tertiary care hospital. Data including demographics, diagnostic categories, duration of hospital stay, predicted death rate (PDR) measured by PIM2 score was compared between survivors and non survivors. Logistic regression analysis was performed to arrive at a risk adjusted relationship between the different predictor variables and the probability of death. Results: Consecutive 130 children admitted to PICU during the study period were enrolled. The mean PDR (%) of the total study population was 22.4 ± 10.60. The mean PDR in survivors was 12.4 ± 7.80 while the PDR in non survivors was 44.2 ± 12.62 (p value < 0.001). Children with PDR < 1% had a mortality rate of 2.4% when compared to 71.4% in children with PDR > 5% (p value < 0.001). PDR by PIM2 score and the presence of hypo-albuminemia remained significant even after adjusting for age in multivariate logistic regression analysis. Conclusion: PDR measured by PIM2 score differentiated well between survivors and non survivors in PICU. The predicted death rate was less than the observed death rate. PIM2 score is a useful tool to assess the severity of illness and predict outcome.

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Effect of Sleep Disorder on Delirium in Post-Cardiac Surgery Patients

Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques ◽

10.1017/cjn.2020.62 ◽

2020 ◽

Vol 47 (5) ◽

pp. 627-633 ◽

Cited By ~ 2

Author(s):

Hongbai Wang ◽

Liang Zhang ◽

Qipeng Luo ◽

Yinan Li ◽

Fuxia Yan

Keyword(s):

Intensive Care Unit ◽

Logistic Regression ◽

Regression Analysis ◽

Cardiac Surgery ◽

Intensive Care ◽

Sleep Quality ◽

Sleep Disorder ◽

Logistic Regression Analysis ◽

Univariate Analysis ◽

Post Cardiac Surgery

ABSTRACT:Background:Post-cardiac surgery patients exhibit a higher incidence of postoperative delirium (PD) compared to non-cardiac surgery patients. Patients with various cardiac diseases suffer from preoperative sleep disorder (SPD) induced by anxiety, depression, breathing disorder, or other factors.Objective:To examine the effect of sleep disorder on delirium in post-cardiac surgery patients.Methods:We prospectively selected 186 patients undergoing selective cardiac valve surgery. Preoperative sleep quality and cognitive function of all eligible participants were assessed through the Pittsburgh Sleep Quality Index (PSQI) and the Montreal Cognitive Assessment, respectively. The Confusion Assessment Method for Intensive Care Unit was used to assess PD from the first to seventh day postoperatively. Patients were divided into two groups according to the PD diagnosis: (1) No PD group and (2) the PD group.Results:Of 186 eligible patients, 29 (15.6%) were diagnosed with PD. A univariate analysis showed that gender (p = 0.040), age (p = 0.009), SPD (p = 0.008), intraoperative infusion volume (p = 0.034), postoperative intubation time (p = 0.001), and intensive care unit stay time (p = 0.009) were associated with PD. A multivariate logistic regression analysis demonstrated that age (odds ratio (OR): 1.106; p = 0.001) and SPD (OR: 3.223; p = 0.047) were independently associated with PD. A receiver operating characteristic curve demonstrated that preoperative PSQI was predictive of PD (area under curve: 0.706; 95% confidence interval: 0.595–0.816). A binomial logistic regression analysis showed that there was a significant association between preoperative 6 and 21 PSQI scores and PD incidence (p = 0.009).Conclusions:Preoperative SPD was significantly associated with PD and a main predictor of PD.

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MRSA colonisation rates on a neonatal and paediatric intensive care unit

Journal of Infection Prevention ◽

10.1177/1757177419885009 ◽

2019 ◽

Vol 21 (2) ◽

pp. 68-71

Author(s):

Rebecca Borg ◽

David Pace

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Paediatric Intensive Care Unit ◽

Average Rate ◽

Control Measures ◽

Paediatric Intensive Care ◽

Molecular Diagnostic ◽

Molecular Diagnostic Techniques ◽

Invasive Infection ◽

The Mean

Methicillin-resistant Staphylococcus aureus (MRSA) colonisation is a challenge in healthcare institutions worldwide. In this retrospective nation-wide study, the rates of MRSA colonisation and infection from 2012 to 2015, on the only neonatal and paediatric intensive care unit (NPICU) in the country, were determined. Mean local rates were compared to rates of MRSA colonisation reported in units in North America, Asia and Europe between 2001 and 2010. The average rate of MRSA colonisation on admission to NPICU from 2012 to 2015 was 3.71% (95% confidence interval [CI] 2.17–5.25), while the mean rate of acquired colonisation was 14.60% (95% CI 6.16–23.04). Both were significantly higher than in units abroad: 1.9% and 4.1%, respectively ( P = 0.04 and P < 0.001). There were no cases of invasive MRSA infection, while the mean rate of non-invasive infection was 0.77% (95% CI 0.54–1.01). Improved adherence to infection control measures and newer molecular diagnostic techniques are needed to further decrease the acquisition of MRSA.

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Introduction of a prescribing ward round to reduce prescribing errors on a paediatric intensive care unit

Archives of Disease in Childhood - Education and Practice ◽

10.1136/archdischild-2019-318732 ◽

2020 ◽

pp. edpract-2019-318732

Author(s):

Aisling Walsh ◽

Rachelle Booth ◽

Kalindi Rajani ◽

Lynne Cochrane ◽

Mark Peters ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Paediatric Intensive Care Unit ◽

Ward Round ◽

Paediatric Intensive Care ◽

Prescribing Errors ◽

Prescription Errors ◽

Total Prescription ◽

The Mean ◽

Almost All

Our paediatric intensive care unit (PICU) performs active surveillance for prescribing errors and detects a mean of 1.66 with an SD of 0.18 total prescription errors per occupied bed day. The primary aim of this project was to reduce the number of prescribing errors in PICU. The secondary aims were to improve the workflow in the unit and reduce the time staff spent on medication queries/prescribing. We introduced a daily multidisciplinary prescribing round to our PICU. Prescribing errors reduced, with the mean number of total prescription errors per bed day falling from 1.66 (0.18) to 1.19 (0.13), the mean number of clinical prescription errors per bed day falling from 0.46 (0.09) to 0.3 (0.07), and the mean number of non-clinical prescribing errors per bed day falling from 1.12 (0.15) to 0.67 (0.1). Forty-eight staff responded to the survey, 39 of whom had been directly involved in the rounds. The majority (37 of 39; 95%) said the prescribing round reduced the overall time they spent on prescribing/medication queries during their shift, and 9 of 10 (90%) prescribers said that they were interrupted fewer times for medication queries while doing other tasks. Almost all (47 of 48; 98%) said that they thought the prescribing ward round should continue. Introduction of a prescribing round with senior medical and pharmacist involvement was associated with a reduction in prescribing errors as well as reduction in the overall time staff spent on medication queries and prescribing. The round was well received by staff, with 98% wanting it to continue.

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Neonatal Mortality and Its Associated Factors among Neonates Admitted to Wollega University Referral Hospital Neonatal Intensive Care Unit, East Wollega, Ethiopia

Global Pediatric Health ◽

10.1177/2333794x211030157 ◽

2021 ◽

Vol 8 ◽

pp. 2333794X2110301

Author(s):

Tesfaye Abera ◽

Lami Bayisa ◽

Teshome Bekele ◽

Mulugeta Dessalegn ◽

Diriba Mulisa ◽

...

Keyword(s):

Intensive Care Unit ◽

Logistic Regression ◽

Regression Analysis ◽

Intensive Care ◽

Neonatal Intensive Care Unit ◽

Neonatal Mortality ◽

Logistic Regression Analysis ◽

Neonatal Intensive Care ◽

Multiple Logistic Regression Analysis ◽

Birth Asphyxia

Ethiopia has a high neonatal mortality rate in spite of dearth of study. Therefore we aimed to assess magnitude and associated factors of neonatal mortality among neonates admitted to neonatal intensive care units of Wollega University Referral Hospital. Accordingly, a facility based cross-sectional study was conducted on 289 by reviewing medical records of neonates admitted to neonatal intensive care unit. The collected data were entered in to Epi data version 3.1 and Stata version 14 used for analysis. Variables with P-value < 0.25 at with 95% confidence interval in binary logistic regression analysis were taken to the multiple logistic regression analysis. Finally, variables with Likewise, variable with P-value < 0.05 at 95% confidence interval in multiple logistic regression analysis were considered as statistically significant. Among 289 neonates admitted to neonatal intensive care unit, 53 (18.34 %) were died. Majority 42(79.25%) of those deaths occurred at ≤ 7 days of birth. Preterm [AOR 4.15, 95% CI (1.67-10.33)], neonates faced birth asphyxia [AOR 3.26, 95% CI (1.33-7.98)], neonates who developed sepsis [AOR 2.29 95% CI (1.01-5.20)] and neonates encountered with jaundice [(AOR 11.08, 95% CI (1.03-119.59)] were more at risk to die. In general, the magnitude of neonatal mortality among neonates admitted to neonatal intensive care unit was high. Gestational age (maturity of new born), birth asphyxia, neonatal sepsis and neonatal jaundice were predictors of neonatal mortality. Neonates admitted to neonatal intensive care unit with sepsis, jaundice, and birth asphyxia demand special attention to reduce neonatal mortality.

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