Development and Validation of a Neurological Outcome Prediction Score for Children Requiring Mechanical Ventilation: The NOPS-VC Score

<div xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="section"> <a class="named-anchor" id="d880065e158"> <!-- named anchor --> </a> <h5 class="section-title" id="d880065e159">Background and aims</h5> <p dir="auto" id="d880065e161">Currently, no validated scoring system exists to predict neurological outcomes in mechanically ventilated children. We aimed to develop and validate such a score in this population. </p> </div><div xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="section"> <a class="named-anchor" id="d880065e163"> <!-- named anchor --> </a> <h5 class="section-title" id="d880065e164">Patients and methods</h5> <p dir="auto" id="d880065e166">We developed the NOPS-VC score, comprising eight items. Each parameter is rated on a Likert scale, where a minimum score of 1 indicates no significant risk, and a maximum score of 3 represents the highest risk for poor neurological outcomes. The face and content validity of the score were assessed using the content validity index (CVI) and content validity ratio. Neurological outcomes were determined at discharge and at 6 months of follow-up. Construct validity was assessed by correlating the NOPS-VC score with the Pediatric Cerebral Performance Category score, functional status scale (FSS), intelligence quotient (IQ), Vineland Adaptive Behavior Scale, gross motor function measure (GMFM), child behavior checklist, and pediatric quality of life inventory. </p> </div><div xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="section"> <a class="named-anchor" id="d880065e168"> <!-- named anchor --> </a> <h5 class="section-title" id="d880065e169">Results</h5> <p dir="auto" id="d880065e171">Among 170 participants, 87 had good functional outcomes. The scale-level content validity index (S-CVI/UA) was 0.95, and S-CVI/Ave was 0.9, indicating excellent content validity. The one-factor model demonstrated a good fit, with all item loadings exceeding 0.7 [Tucker–Lewis index (TLI) = 0.95, comparative fit index (CFI) = 0.96, root mean squared error of approximation (RMSEA) = 0.067 (0.059–0.074)]. The area under the receiver operating characteristic (ROC) curve for the maximum and baseline NOPS-VC scores was 0.92 and 0.91, respectively. The optimal cutoff value for both scores was 18, with sensitivity/specificity of 82/97% for the maximum score and 80/97% for the baseline score. Construct validity showed strong correlations ( <i>r</i> ≥ 0.70) with all parameters. </p> </div><div xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="section"> <a class="named-anchor" id="d880065e176"> <!-- named anchor --> </a> <h5 class="section-title" id="d880065e177">Conclusion</h5> <p dir="auto" id="d880065e179">The NOPS-VC score, when applied at the initiation of mechanical ventilation in critically ill children, demonstrates strong validity in predicting neurological outcomes at 6 months, with an optimal cutoff value of 18. </p> </div><div xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="section"> <a class="named-anchor" id="d880065e181"> <!-- named anchor --> </a> <h5 class="section-title" id="d880065e182">How to cite this article</h5> <p dir="auto" id="d880065e184">Tomar A, Panda PK, Elwadhi A, Tiwari LK, Sharawat IK. Development and Validation of a Neurological Outcome Prediction Score for Children Requiring Mechanical Ventilation: The NOPS-VC Score. Indian J Crit Care Med 2025;29(7):578–585. </p> </div>

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Clinical Electroencephalography for Anesthesiologists: Part I: Background and Basic Signatures

Abstract. The widely used electroencephalogram-based indices for depth-of-anesthesia monitoring assume that the same index value defines the same level of unconsciousness for all anesthetics. In contrast, we show that different anesthetics act at different molecular targets and neural circuits to produce distinct brain states that are readily visible in the electroencephalogram. We present a two-part review to educate anesthesiologists on use of the unprocessed electroencephalogram and its spectrogram to track the brain states of patients receiving anesthesia care. Here in part I, we review the biophysics of the electroencephalogram and the neurophysiology of the electroencephalogram signatures of three intravenous anesthetics: propofol, dexmedetomidine, and ketamine, and four inhaled anesthetics: sevoflurane, isoflurane, desflurane, and nitrous oxide. Later in part II, we discuss patient management using these electroencephalogram signatures. Use of these electroencephalogram signatures suggests a neurophysiologically based paradigm for brain state monitoring of patients receiving anesthesia care.Abstract. The authors review the neurophysiology of the electroencephalogram signatures of the anesthetics: propofol, dexmedetomidine, ketamine, sevoflurane, isoflurane, desflurane, and nitrous oxide. These signatures provide a neurophysiologically based paradigm for brain state monitoring of patients receiving anesthesia care.

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