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1.
Crit Care Explor ; 6(8): e1137, 2024 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-39162643

RESUMO

IMPORTANCE: Persistent hypothermia after cardiopulmonary bypass (CPB) in neonates with congenital heart defects (CHD) has been historically considered benign despite lack of evidence on its prognostic significance. OBJECTIVES: Examine associations between the magnitude and pattern of unintentional postoperative hypothermia and odds of complications in neonates with CHD undergoing CPB. DESIGN: Retrospective cohort study. SETTING: Single northeastern U.S., urban pediatric quaternary care center with an established cardiac surgery program. PARTICIPANTS: Population-based sample of neonates greater than or equal to 34 weeks gestation undergoing their first CPB between 2015 and 2019. INTERVENTIONS: None. MAIN OUTCOMES AND MEASUREMENTS: Hourly temperature measurements for the first 48 postoperative hours were extracted from inpatient medical records, and clinical characteristics and outcomes were accessed through the local patient registry. Group-based trajectory modeling (GBTM) identified latent temporal temperature trajectories. Associations of trajectories with outcomes were assessed using multivariable binary logistic regression. Outcomes (postoperative complications) were manually adjudicated by experts or were predefined by the patient registry. RESULTS: Four hundred fifty neonates met inclusion criteria. Their mean (sd) gestational age was 38 weeks (1.3), mean (sd) birth weight was 3.19 kilograms (0.55), median (interquartile range) surgical age was 4.7 days (3.3-7.0), 284 of 450 (63%) were male, and 272 of 450 (60%) were White. GBTM identified three distinct curvilinear temperature trajectories: persistent hypothermia (n = 38, 9%), resolving hypothermia (n = 233, 52%), and normothermia (n = 179, 40%). Compared with the normothermic group, those with persistent hypothermia had significantly higher odds of cardiac arrest, actionable arrhythmia, delayed first successful extubation, prolonged cardiac ICU length of stay, very poor weight gain, and 30-day hospital mortality. The persistent hypothermia group was characterized by greater odds of having a lower gestational age, more prevalent neurologic abnormalities, more unplanned reoperations, and a low surgical mortality risk assessment. CONCLUSIONS: Persistent postoperative hypothermia in neonates after CPB is independently associated with having greater odds of complications. Recovery patterns from postoperative hypothermia may be a clinically useful marker to identify patient instability in neonates. Additional research is needed for causal modeling and prospective validation before clinical adoption.


Assuntos
Ponte Cardiopulmonar , Cardiopatias Congênitas , Hipotermia , Complicações Pós-Operatórias , Humanos , Recém-Nascido , Estudos Retrospectivos , Ponte Cardiopulmonar/efeitos adversos , Masculino , Feminino , Hipotermia/etiologia , Hipotermia/epidemiologia , Complicações Pós-Operatórias/etiologia , Complicações Pós-Operatórias/epidemiologia , Cardiopatias Congênitas/cirurgia , Fatores de Risco , Estudos de Coortes
2.
Ann Emerg Med ; 81(1): 57-69, 2023 01.
Artigo em Inglês | MEDLINE | ID: mdl-36253296

RESUMO

STUDY OBJECTIVE: Ischemic electrocardiogram (ECG) changes are subtle and transient in patients with suspected non-ST-segment elevation (NSTE)-acute coronary syndrome. However, the out-of-hospital ECG is not routinely used during subsequent evaluation at the emergency department. Therefore, we sought to compare the diagnostic performance of out-of-hospital and ED ECG and evaluate the incremental gain of artificial intelligence-augmented ECG analysis. METHODS: This prospective observational cohort study recruited patients with out-of-hospital chest pain. We retrieved out-of-hospital-ECG obtained by paramedics in the field and the first ED ECG obtained by nurses during inhospital evaluation. Two independent and blinded reviewers interpreted ECG dyads in mixed order per practice recommendations. Using 179 morphological ECG features, we trained, cross-validated, and tested a random forest classifier to augment non ST-elevation acute coronary syndrome (NSTE-ACS) diagnosis. RESULTS: Our sample included 2,122 patients (age 59 [16]; 53% women; 44% Black, 13.5% confirmed acute coronary syndrome). The rate of diagnostic ST elevation and ST depression were 5.9% and 16.2% on out-of-hospital-ECG and 6.1% and 12.4% on ED ECG, with ∼40% of changes seen on out-of-hospital-ECG persisting and ∼60% resolving. Using expert interpretation of out-of-hospital-ECG alone gave poor baseline performance with area under the receiver operating characteristic (AUC), sensitivity, and negative predictive values of 0.69, 0.50, and 0.92. Using expert interpretation of serial ECG changes enhanced this performance (AUC 0.80, sensitivity 0.61, and specificity 0.93). Interestingly, augmenting the out-of-hospital-ECG alone with artificial intelligence algorithms boosted its performance (AUC 0.83, sensitivity 0.75, and specificity 0.95), yielding a net reclassification improvement of 29.5% against expert ECG interpretation. CONCLUSION: In this study, 60% of diagnostic ST changes resolved prior to hospital arrival, making the ED ECG suboptimal for the inhospital evaluation of NSTE-ACS. Using serial ECG changes or incorporating artificial intelligence-augmented analyses would allow correctly reclassifying one in 4 patients with suspected NSTE-ACS.


Assuntos
Síndrome Coronariana Aguda , Humanos , Feminino , Pessoa de Meia-Idade , Masculino , Síndrome Coronariana Aguda/diagnóstico , Inteligência Artificial , Estudos Prospectivos , Eletrocardiografia , Aprendizado de Máquina , Hospitais
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