RESUMEN
OBJECTIVE: To investigate the environmental precipitants, treatment and outcome of critically ill patients affected by the largest and most lethal reported epidemic of thunderstorm asthma. DESIGN, SETTING AND PARTICIPANTS: Retrospective multicentre observational study. Meteorological, airborne particulate and pollen data, and a case series of 35 patients admitted to 15 intensive care units (ICUs) due to the thunderstorm asthma event of 21-22 November 2016, in Victoria, Australia, were analysed and compared with 1062 total ICU-admitted Australian patients with asthma in 2016. MAIN OUTCOME MEASURES: Characteristics and outcomes of total ICU versus patients with thunderstorm asthma, the association between airborne particulate counts and storm arrival, and ICU resource utilisation. RESULTS: All 35 patients had an asthma diagnosis; 13 (37%) had a cardiac or respiratory arrest, five (14%) died. Compared with total Australian ICU-admitted patients with asthma in 2016, patients with thunderstorm asthma had a higher mortality (15% v 1.3%, P < 0.001), were more likely to be male (63% v 34%, P < 0.001), to be mechanically ventilated, and had shorter ICU length of stay in survivors (median, 31.8 hours [interquartile range (IQR), 14.8-43.6 hours] v 40.7 hours [IQR, 22.3-75.1 hours]; P = 0.025). Patients with cardiac arrest were more likely to be born in Asian or subcontinental countries (5/10 [50%] v 4/25 [16%]; relative risk, 3.13; 95% CI, 1.05-9.31). A temporal link was demonstrated between airborne particulate counts and arrival of the storm. The event used 15% of the public ICU beds in the region. CONCLUSION: Arrival of a triggering storm is associated with an increase in respirable airborne particles. Affected critically ill patients are young, have a high mortality, a short duration of bronchospasm, and a prior diagnosis of asthma is common.
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Contaminación del Aire/estadística & datos numéricos , Asma/epidemiología , Cuidados Críticos/métodos , Tiempo (Meteorología) , Adolescente , Adulto , Anciano , Asma/terapia , Niño , Enfermedad Crítica/epidemiología , Femenino , Humanos , Tiempo de Internación/estadística & datos numéricos , Masculino , Persona de Mediana Edad , Material Particulado , Polen , Lluvia , Respiración Artificial/estadística & datos numéricos , Estudios Retrospectivos , Victoria/epidemiología , Adulto JovenRESUMEN
BACKGROUND: A multidisciplinary collaboration investigated the world's largest, most catastrophic epidemic thunderstorm asthma event that took place in Melbourne, Australia, on Nov 21, 2016, to inform mechanisms and preventive strategies. METHODS: Meteorological and airborne pollen data, satellite-derived vegetation index, ambulance callouts, emergency department presentations, and data on hospital admissions for Nov 21, 2016, as well as leading up to and following the event were collected between Nov 21, 2016, and March 31, 2017, and analysed. We contacted patients who presented during the epidemic thunderstorm asthma event at eight metropolitan health services (each including up to three hospitals) via telephone questionnaire to determine patient characteristics, and investigated outcomes of intensive care unit (ICU) admissions. FINDINGS: Grass pollen concentrations on Nov 21, 2016, were extremely high (>100 grains/m3). At 1800 AEDT, a gust front crossed Melbourne, plunging temperatures 10°C, raising humidity above 70%, and concentrating particulate matter. Within 30 h, there were 3365 (672%) excess respiratory-related presentations to emergency departments, and 476 (992%) excess asthma-related admissions to hospital, especially individuals of Indian or Sri Lankan birth (10% vs 1%, p<0·0001) and south-east Asian birth (8% vs 1%, p<0·0001) compared with previous 3 years. Questionnaire data from 1435 (64%) of 2248 emergency department presentations showed a mean age of 32·0 years (SD 18·6), 56% of whom were male. Only 28% had current doctor-diagnosed asthma. 39% of the presentations were of Asian or Indian ethnicity (25% of the Melbourne population were of this ethnicity according to the 2016 census, relative risk [RR] 1·93, 95% CI 1·74-2·15, p <0·0001). Of ten individuals who died, six were Asian or Indian (RR 4·54, 95% CI 1·28-16·09; p=0·01). 35 individuals were admitted to an intensive care unit, all had asthma, 12 took inhaled preventers, and five died. INTERPRETATION: Convergent environmental factors triggered a thunderstorm asthma epidemic of unprecedented magnitude, tempo, and geographical range and severity on Nov 21, 2016, creating a new benchmark for emergency and health service escalation. Asian or Indian ethnicity and current doctor-diagnosed asthma portended life-threatening exacerbations such as those requiring admission to an ICU. Overall, the findings provide important public health lessons applicable to future event forecasting, health care response coordination, protection of at-risk populations, and medical management of epidemic thunderstorm asthma. FUNDING: None.
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Asma/epidemiología , Asma/etiología , Epidemias/estadística & datos numéricos , Adolescente , Adulto , Alérgenos/efectos adversos , Australia/epidemiología , Servicio de Urgencia en Hospital/estadística & datos numéricos , Femenino , Humanos , Masculino , Persona de Mediana Edad , Polen/efectos adversos , Factores de Riesgo , Encuestas y Cuestionarios , Tiempo (Meteorología) , Adulto JovenRESUMEN
BACKGROUND: Some ventilated intensive care unit (ICU) patients may experience reduced oxygenation following hyperbaric oxygen treatment (HBOT). METHODS: In a prospective, single-centre, observational study, we documented changes in oxygenation and the need for associated changes in ventilator settings in 25 consecutive, mechanically ventilated ICU patients immediately post-treatment and 1, 2, 3 and 6 hours following 61 HBOT sessions. The primary outcome measure of oxygenation was the ratio of arterial partial pressure of oxygen (P(a)O2) against the level of inspired oxygen (F(i)O2), P(a)O2/F(i)O2. RESULTS: Following HBOT, the P(a)O2/F(i)O2 ratio decreased by 27% on return to ICU (P < 0.001, 95% confidence intervals (CI) 20.6 to 34.2); 22% at 1 hour post-HBOT (P < 0.001, 95% CI 15.1 to 28.6); and 8% at 2 hours post (P = 0.03, 95% CI 0.8 to 14.4). The ratio showed no significant differences from pre-HBOT at 3 and 6 hours post-HBOT. P(a)O2/F(i)O2 ratio changes necessitated adjustments to ventilation parameters upon return to ICU following 30 of 61 HBOT sessions in 17 out of the 25 patients. The most common ventilation parameter altered was F(i)O2 (n = 20), increased by a mean of +0.17 (95% CI 0.11 to 0.23) above baseline for two hours following HBOT. CONCLUSIONS: Following HBOT, oxygenation is reduced in a majority of mechanically ventilated ICU patients and requires temporary alterations to mechanical ventilation settings. Further study to identify predictive characteristics and to determine causation for those at risk of needing ventilation alterations is required.
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Respiración de la Célula , Enfermedad Crítica/terapia , Oxigenoterapia Hiperbárica/métodos , Consumo de Oxígeno/fisiología , Oxígeno/sangre , Respiración Artificial/métodos , Adulto , Anciano , Intervalos de Confianza , Femenino , Humanos , Unidades de Cuidados Intensivos , Masculino , Persona de Mediana Edad , Presión Parcial , Estudios Prospectivos , Respiración Artificial/normas , Factores de TiempoRESUMEN
This review describes the methods for displaying riskadjusted mortality data for critical care units. Two applications are considered. The comparison within a cohort of risk-adjusted mortality performance uses standardised mortality ratios (SMRs), league tables, caterpillar plots and funnel plots. Monitoring of riskadjusted performance over time is considered using SMRs, risk-adjusted p (RAP), observed minus expected outcome (VLAD), risk-adjusted cumulative sum (RACUSUM), riskadjusted sequential probability ratio test (RASPRT), and riskadjusted exponentially weighted moving average (RAEWMA) charts. Examples of the charts are provided, and calculation of the statistics and design of the charts are described in the Appendix. This overview is an introduction to the use of riskadjustment methods to track mortality rates. The importance of model performance and relevance of the risk-adjustment models is emphasised. The relative merits of different methods are discussed. Risk-adjusted monitoring plays a role in the context of a holistic quality development strategy. The importance of a planned approach to response and intervention is stressed.