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1.
Crit Care ; 28(1): 247, 2024 Jul 17.
Article in English | MEDLINE | ID: mdl-39020419

ABSTRACT

BACKGROUND: Binary classification models are frequently used to predict clinical deterioration, however they ignore information on the timing of events. An alternative is to apply time-to-event models, augmenting clinical workflows by ranking patients by predicted risks. This study examines how and why time-to-event modelling of vital signs data can help prioritise deterioration assessments using lift curves, and develops a prediction model to stratify acute care inpatients by risk of clinical deterioration. METHODS: We developed and validated a Cox regression for time to in-hospital mortality. The model used time-varying covariates to estimate the risk of clinical deterioration. Adult inpatient medical records from 5 Australian hospitals between 1 January 2019 and 31 December 2020 were used for model development and validation. Model discrimination and calibration were assessed using internal-external cross validation. A discrete-time logistic regression model predicting death within 24 h with the same covariates was used as a comparator to the Cox regression model to estimate differences in predictive performance between the binary and time-to-event outcome modelling approaches. RESULTS: Our data contained 150,342 admissions and 1016 deaths. Model discrimination was higher for Cox regression than for discrete-time logistic regression, with cross-validated AUCs of 0.96 and 0.93, respectively, for mortality predictions within 24 h, declining to 0.93 and 0.88, respectively, for mortality predictions within 1 week. Calibration plots showed that calibration varied by hospital, but this can be mitigated by ranking patients by predicted risks. CONCLUSION: Time-varying covariate Cox models can be powerful tools for triaging patients, which may lead to more efficient and effective care in time-poor environments when the times between observations are highly variable.


Subject(s)
Clinical Deterioration , Humans , Male , Female , Aged , Middle Aged , Proportional Hazards Models , Hospital Mortality , Australia , Aged, 80 and over , Time Factors , Risk Assessment/methods , Risk Assessment/standards , Risk Assessment/statistics & numerical data , Adult
2.
Sci Rep ; 14(1): 13462, 2024 06 12.
Article in English | MEDLINE | ID: mdl-38862591

ABSTRACT

There have been 774,075,242 cases of COVID-19 and 7,012,986 deaths worldwide as of January 2024. In the early stages of the pandemic, there was an urgent need to reduce the severity of the disease and prevent the need for hospitalization to avoid stress on healthcare systems worldwide. The repurposing of drugs to prevent clinical deterioration of COVID-19 patients was trialed in many studies using many different drugs. Fluvoxamine (an SSRI and sigma-1 receptor agonist) was initially identified to potentially provide beneficial effects in COVID-19-infected patients, preventing clinical deterioration and the need for hospitalization. Fourteen clinical studies have been carried out to date, with seven of those being randomized placebo-controlled studies. This systematic review and meta-analysis covers the literature from the outbreak of SARS-CoV-2 in late 2019 until January 2024. Search terms related to fluvoxamine, such as its trade names and chemical names, along with words related to COVID-19, such as SARS-CoV-2 and coronavirus, were used in literature databases including PubMed, Google Scholar, Scopus, and the ClinicalTrials.gov database from NIH, to identify the trials used in the subsequent analysis. Clinical deterioration and death data were extracted from these studies where available and used in the meta-analysis. A total of 7153 patients were studied across 14 studies (both open-label and double-blind placebo-controlled). 681 out of 3553 (19.17%) in the standard care group and 255 out of 3600 (7.08%) in the fluvoxamine-treated group experienced clinical deterioration. The estimated average log odds ratio was 1.087 (95% CI 0.200 to 1.973), which differed significantly from zero (z = 2.402, p = 0.016). The seven placebo-controlled studies resulted in a log odds ratio of 0.359 (95% CI 0.1111 to 0.5294), which differed significantly from zero (z = 3.103, p = 0.002). The results of this study identified fluvoxamine as effective in preventing clinical deterioration, and subgrouping analysis suggests that earlier treatment with a dose of 200 mg or above provides the best outcomes. We hope the outcomes of this study can help design future studies into respiratory viral infections and potentially improve clinical outcomes.


Subject(s)
COVID-19 Drug Treatment , COVID-19 , Fluvoxamine , SARS-CoV-2 , Fluvoxamine/therapeutic use , Humans , COVID-19/mortality , SARS-CoV-2/isolation & purification , SARS-CoV-2/drug effects , Treatment Outcome , Clinical Deterioration , Selective Serotonin Reuptake Inhibitors/therapeutic use , Selective Serotonin Reuptake Inhibitors/adverse effects , Selective Serotonin Reuptake Inhibitors/administration & dosage
3.
Crit Care Clin ; 40(3): 561-581, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38796228

ABSTRACT

Early warning systems (EWSs) are designed and deployed to create a rapid assessment and response for patients with clinical deterioration outside the intensive care unit (ICU). These models incorporate patient-level data such as vital signs and laboratory values to detect or prevent adverse clinical events, such as vital signs and laboratories to allow detection and prevention of adverse clinical events such as cardiac arrest, intensive care transfer, or sepsis. The applicability, development, clinical utility, and general perception of EWS in clinical practice vary widely. Here, we review the field as it has grown from early vital sign-based scoring systems to contemporary multidimensional algorithms and predictive technologies for clinical decompensation outside the ICU.


Subject(s)
Critical Illness , Early Warning Score , Humans , Critical Illness/therapy , Vital Signs , Intensive Care Units , Clinical Deterioration , Critical Care/methods , Critical Care/standards , Algorithms , Monitoring, Physiologic/methods
4.
PLoS One ; 19(5): e0301643, 2024.
Article in English | MEDLINE | ID: mdl-38696424

ABSTRACT

BACKGROUND: Delayed response to clinical deterioration of hospital inpatients is common. Deployment of an electronic automated advisory vital signs monitoring and notification system to signal clinical deterioration is associated with significant improvements in clinical outcomes but there is no evidence on the cost-effectiveness compared with routine monitoring, in the National Health Service (NHS) in the United Kingdom (UK). METHODS: A decision analytic model was developed to estimate the cost-effectiveness of an electronic automated advisory notification system versus standard care, in adults admitted to a district general hospital. Analyses considered: (1) the cost-effectiveness of the technology based on secondary analysis of patient level data of 3787 inpatients in a before-and-after study; and (2) the cost-utility (cost per quality-adjusted life-year (QALY)) over a lifetime horizon, extrapolated using published data. Analysis was conducted from the perspective of the NHS. Uncertainty in the model was assessed using a range of sensitivity analyses. RESULTS: The study population had a mean age of 68 years, 48% male, with a median inpatient stay of 6 days. Expected life expectancy at discharge was assumed to be 17.74 years. (1) Cost-effectiveness analysis: The automated notification system was more effective (-0.027 reduction in mean events per patient) and provided a cost saving of -£12.17 (-182.07 to 154.80) per patient admission. (2) Cost-utility analysis: Over a lifetime horizon the automated notification system was dominant, demonstrating a positive incremental QALY gain (0.0287 QALYs, equivalent to ~10 days of perfect health) and a cost saving of £55.35. At a threshold of £20,000 per QALY, the probability of automated monitoring being cost-effective in the NHS was 81%. Increased use of cableless sensors may reduce cost-savings, however, the intervention remains cost-effective at 100% usage (ICER: £3,107/QALY). Stratified cost-effectiveness analysis by age, National Early Warning Score (NEWS) on admission, and primary diagnosis indicated the automated notification system was cost-effective for most strategies and that use representative of the patient population studied was the most cost-saving strategy. CONCLUSION: Automated notification system for adult patients admitted to general wards appears to be a cost-effective use in the NHS; adopting this technology could be good use of scarce resources with significance for patient safety.


Subject(s)
Cost-Benefit Analysis , Quality-Adjusted Life Years , Humans , Male , Aged , Female , United Kingdom , Middle Aged , Clinical Deterioration , Aged, 80 and over , Adult , Automation/economics
5.
Hosp Pediatr ; 14(6): e260-e266, 2024 Jun 01.
Article in English | MEDLINE | ID: mdl-38784994

ABSTRACT

OBJECTIVES: Rapid response system (RRS) activations resulting in emergency transfers (ETs) and codes outside the ICU are associated with increased mortality and length of stay. We aimed to evaluate the patient and care team characteristics of RRS activations resulting in ETs and codes outside the ICU (together classified as "deterioration events") versus those that did not result in a deterioration event. METHODS: For each RRS activation at our institution from 2019 to 2021, data were gathered on patient demographics and medical diagnoses, care team and treatment factors, and ICU transfer. Descriptive statistics, bivariate analyses, and multivariable logistic regression using a backward elimination model selection method were performed to assess potential risk factors for deterioration events. RESULTS: Over the 3-year period, 1765 RRS activations were identified. Fifty-three (3%) activations were deemed acute care codes, 64 (4%) were noncode ETs, 921 (52%) resulted in nonemergent transfers to an ICU, and 727 (41%) patients remained in an acute care unit. In a multivariable model, any complex chronic condition (adjusted odds ratio, 6.26; 95% confidence interval, 2.83-16.60) and hematology/oncology service (adjusted odds ratio, 2.19; 95% confidence interval, 1.28-3.74) were independent risk factors for a deterioration event. CONCLUSIONS: Patients with medical complexity and patients on the hematology/oncology service had a higher risk of deterioration events than other patients with RRS activations. Further analyzing how our hospital evaluates and treats these specific patient populations is critical as we develop targeted interventions to reduce deterioration events.


Subject(s)
Clinical Deterioration , Hospital Rapid Response Team , Patient Transfer , Humans , Risk Factors , Female , Male , Child , Hospital Rapid Response Team/statistics & numerical data , Child, Preschool , Patient Transfer/statistics & numerical data , Adolescent , Infant , Retrospective Studies
7.
J Cardiothorac Surg ; 19(1): 231, 2024 Apr 16.
Article in English | MEDLINE | ID: mdl-38627781

ABSTRACT

BACKGROUND: Cardiac herniation occurs when there is a residual pericardial defect post thoracic surgery and is recognised as a rare but fatal complication. It confers a high mortality and requires immediate surgical correction upon recognition. We present a case of cardiac herniation occurring post thymectomy and left upper lobectomy. CASE PRESENTATION: Initial presentation: A 48-year-old male, hypertensive smoker presented with progressive breathlessness and was found to have a left upper zone mass confirmed on CT biopsy as carcinoid of unclear origin. PET-CT revealed avidity in a left anterior mediastinal area, left upper lobe (LUL) lung mass, mediastinal lymph nodes, and a right thymic satellite nodule. Intraoperatively: Access via left thoracotomy and sternotomy. The LUL tumour involved the left thymic lobe (LTL), left superior pulmonary vein (LSPV), left phrenic nerve and intervening mediastinal fat and pericardium, which were resected en-masse. The satellite nodule in the right thymic lobe (RTL) was adjacent to the junction between the left innominate vein and superior vena cava (SVC). The pericardium was resected from the SVC to the left atrial appendage. Clinical deterioration: Initially the patient was doing well clinically on day 1, however there was sudden bradycardia, hypotension, clamminess, and oligoanuria, with raised central venous pressures and troponins. ECG: no capture in leads V1-2, but positive deflections seen on posterior leads. Echo: no acoustic windows, but good windows seen posteriorly. CXR: left mediastinal shift. Redo operation: After initial resuscitation and stabilisation on the intensive care unit, on day 2 a redo-sternotomy revealed cardiac herniation into the left thoracic cavity with the left ventricular apex pointing towards the spine, and inferior caval kinking. After reduction and repair of the pericardial defect with a fenestrated GoreTex patch, the patient recovered well with complete resolution of the ECG and CXR. CONCLUSION: Cardiac herniation can even occur following sub-pneumonectomy lung resections and should be considered as a differential when faced with a sudden clinical deterioration, warranting early surgical correction.


Subject(s)
Clinical Deterioration , Heart Diseases , Male , Humans , Middle Aged , Thymectomy/adverse effects , Vena Cava, Superior/surgery , Positron Emission Tomography Computed Tomography , Heart Diseases/surgery , Hernia/etiology , Hernia/complications , Pneumonectomy/adverse effects
8.
J Neurol ; 271(6): 2980-2991, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38507074

ABSTRACT

BACKGROUND: Early neurological deterioration, a common complication in patients with intracerebral hemorrhage, is associated with poor outcomes. Despite the fact that the prevalence and predictors of early neurological impairment are widely addressed, few studies have consolidated these findings. This study aimed to systematically investigate the prevalence and predictors of early neurological deterioration. METHODS: The PubMed, Embase, Cochrane Library, CIHNAL, and Web of Science databases were systematically searched for relevant studies from the inception to December 2023. The data were extracted using a predefined worksheet. Quality assessment was conducted using the Newcastle-Ottawa Scale. Two reviewers independently performed the study selection, data extraction, and quality appraisal. The pooled effect size and 95% confidence intervals were calculated using the STATA 17.0 software package. RESULTS: In total, 32 studies and 5,014 patients were included in this meta-analysis. The prevalence of early neurological deterioration was 23% (95% CI 21-26%, p < 0.01). The initial NIHSS score (OR = 1.24, 95% CI 1.17, 1.30, p < 0.01), hematoma volume (OR = 1.07, 95% CI 1.06, 1.09, p < 0.01), intraventricular hemorrhage (OR = 3.50, 95% CI 1.64, 7.47, p < 0.01), intraventricular extension (OR = 3.95, 95% CI 1.96, 7.99, p < 0.01), hematoma expansion (OR = 9.77, 95% CI 4.43, 17.40, p < 0.01), and computed tomographic angiography spot sign (OR = 5.77, 95% CI 1.53, 20.23, p = 0.01) were predictors of early neurological deterioration. The funnel plot and Egger's test revealed significant publication bias (p < 0.001). CONCLUSIONS: This meta-analysis revealed a pooled prevalence of early neurological deterioration of 23% in patients with intracerebral hemorrhage. The initial NIHSS score, hematoma volume, intraventricular hemorrhage, intraventricular expansion, hematoma expansion, and spot sign enhanced the probability of early neurological deterioration. These findings provide healthcare providers with an evidence-based basis for detecting and managing early neurological deterioration in patients with intracerebral hemorrhage.


Subject(s)
Cerebral Hemorrhage , Humans , Cerebral Hemorrhage/diagnostic imaging , Cerebral Hemorrhage/complications , Nervous System Diseases/etiology , Nervous System Diseases/epidemiology , Clinical Deterioration , Disease Progression
9.
J Clin Nurs ; 33(7): 2544-2561, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38454551

ABSTRACT

AIM(S): To explore the published research related to nurses' documentation and use of vital signs in recognising and responding to deteriorating patients. DESIGN: Scoping review of international, peer-reviewed research studies. DATA SOURCES: Cumulative Index to Nursing and Allied Health Literature Complete, Medline Complete, American Psychological Association PsycInfo and Excerpta Medica were searched on 25 July 2023. REPORTING METHOD: Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. RESULTS: Of 3880 potentially eligible publications, 32 were included. There were 26 studies of nurses' vital sign documentation: 21 adults and five paediatric. The most and least frequently documented vital signs were blood pressure and respiratory rate respectively. Seven studies focused on vital signs and rapid response activation or afferent limb failure. Five studies of vital signs used to trigger the rapid response system showed heart rate was the most frequent and respiratory rate and conscious state were the least frequent. Heart rate was least likely and oxygen saturation was most likely to be associated with afferent limb failure (n = 4 studies). CONCLUSION: Despite high reliance on using vital signs to recognise clinical deterioration and activate a response to deteriorating patients in hospital settings, nurses' documentation of vital signs and use of vital signs to activate rapid response systems is poorly understood. There were 21studies of nurses' vital sign documentation in adult patients and five studies related to children. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: A deeper understanding of nurses' decisions to assess (or not assess) specific vital signs, analysis of the value or importance nurses place (or not) on specific vital sign parameters is warranted. The influence of patient characteristics (such as age) or the clinical practice setting, and the impact of nurses' workflows of vital sign assessment warrants further investigation. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.


Subject(s)
Clinical Deterioration , Vital Signs , Humans , Vital Signs/physiology , Adult , Nursing Staff, Hospital/psychology , Documentation/methods , Documentation/standards
10.
Nurs Stand ; 39(4): 40-45, 2024 04 03.
Article in English | MEDLINE | ID: mdl-38523526

ABSTRACT

Nurses may encounter deteriorating patients in their clinical practice, so they require an understanding of the early physiological signs of deterioration and a structured approach to patient assessment. This enables appropriate management and a timely response to the most life-threatening issues identified, such as a compromised airway. This article describes how nurses can use early warning scores and a structured patient assessment, using the ABCDE (airway, breathing, circulation, disability, exposure) framework, to identify early signs of deterioration and facilitate the timely escalation of patient care where necessary.


Subject(s)
Clinical Deterioration , Early Warning Score , Humans
11.
Intensive Care Med ; 50(4): 493-501, 2024 Apr.
Article in English | MEDLINE | ID: mdl-38526578

ABSTRACT

An implantable left ventricular assist device (LVAD) is indicated as a bridge to transplantation or recovery in the United Kingdom (UK). The mechanism of action of the LVAD results in a unique state of haemodynamic stability with diminished arterial pulsatility. The clinical assessment of an LVAD recipient can be challenging because non-invasive blood pressure, pulse and oxygen saturation measurements may be hard to obtain. As a result of this unusual situation and complex interplay between the device and the native circulation, resuscitation of LVAD recipients requires bespoke guidelines. Through collaboration with key UK stakeholders, we assessed the current evidence base and developed guidelines for the recognition of clinical deterioration, inadequate circulation and time-critical interventions. Such guidelines, intended for use in transplant centres, are designed to be deployed by those providing immediate care of LVAD patients under conditions of precipitous clinical deterioration. In summary, the Joint British Societies and Transplant Centres LVAD Working Group present the UK guideline on management of emergencies in implantable LVAD recipients for use in advanced heart failure centres. These recommendations have been made with a UK resuscitation focus but are widely applicable to professionals regularly managing patients with implantable LVADs.


Subject(s)
Clinical Deterioration , Heart Failure , Heart Transplantation , Heart-Assist Devices , Humans , Emergencies , Heart Failure/therapy
12.
JAMA Intern Med ; 184(5): 557-562, 2024 May 01.
Article in English | MEDLINE | ID: mdl-38526472

ABSTRACT

Importance: Inpatient clinical deterioration is associated with substantial morbidity and mortality but may be easily missed by clinicians. Early warning scores have been developed to alert clinicians to patients at high risk of clinical deterioration, but there is limited evidence for their effectiveness. Objective: To evaluate the effectiveness of an artificial intelligence deterioration model-enabled intervention to reduce the risk of escalations in care among hospitalized patients using a study design that facilitates stronger causal inference. Design, Setting, and Participants: This cohort study used a regression discontinuity design that controlled for confounding and was based on Epic Deterioration Index (EDI; Epic Systems Corporation) prediction model scores. Compared with other observational research, the regression discontinuity design facilitates causal analysis. Hospitalized adults were included from 4 general internal medicine units in 1 academic hospital from January 17, 2021, through November 16, 2022. Exposure: An artificial intelligence deterioration model-enabled intervention, consisting of alerts based on an EDI score threshold with an associated collaborative workflow among nurses and physicians. Main Outcomes and Measures: The primary outcome was escalations in care, including rapid response team activation, transfer to the intensive care unit, or cardiopulmonary arrest during hospitalization. Results: During the study, 9938 patients were admitted to 1 of the 4 units, with 963 patients (median [IQR] age, 76.1 [64.2-86.2] years; 498 males [52.3%]) included within the primary regression discontinuity analysis. The median (IQR) Elixhauser Comorbidity Index score in the primary analysis cohort was 10 (0-24). The intervention was associated with a -10.4-percentage point (95% CI, -20.1 to -0.8 percentage points; P = .03) absolute risk reduction in the primary outcome for patients at the EDI score threshold. There was no evidence of a discontinuity in measured confounders at the EDI score threshold. Conclusions and Relevance: Using a regression discontinuity design, this cohort study found that the implementation of an artificial intelligence deterioration model-enabled intervention was associated with a significantly decreased risk of escalations in care among inpatients. These results provide evidence for the effectiveness of this intervention and support its further expansion and testing in other care settings.


Subject(s)
Artificial Intelligence , Clinical Deterioration , Humans , Male , Female , Aged , Middle Aged , Cohort Studies , Early Warning Score , Hospitalization/statistics & numerical data , Hospital Rapid Response Team , Intensive Care Units
13.
Crit Care Med ; 52(7): 1007-1020, 2024 Jul 01.
Article in English | MEDLINE | ID: mdl-38380992

ABSTRACT

OBJECTIVES: Machine learning algorithms can outperform older methods in predicting clinical deterioration, but rigorous prospective data on their real-world efficacy are limited. We hypothesized that real-time machine learning generated alerts sent directly to front-line providers would reduce escalations. DESIGN: Single-center prospective pragmatic nonrandomized clustered clinical trial. SETTING: Academic tertiary care medical center. PATIENTS: Adult patients admitted to four medical-surgical units. Assignment to intervention or control arms was determined by initial unit admission. INTERVENTIONS: Real-time alerts stratified according to predicted likelihood of deterioration sent either to the primary team or directly to the rapid response team (RRT). Clinical care and interventions were at the providers' discretion. For the control units, alerts were generated but not sent, and standard RRT activation criteria were used. MEASUREMENTS AND MAIN RESULTS: The primary outcome was the rate of escalation per 1000 patient bed days. Secondary outcomes included the frequency of orders for fluids, medications, and diagnostic tests, and combined in-hospital and 30-day mortality. Propensity score modeling with stabilized inverse probability of treatment weight (IPTW) was used to account for differences between groups. Data from 2740 patients enrolled between July 2019 and March 2020 were analyzed (1488 intervention, 1252 control). Average age was 66.3 years and 1428 participants (52%) were female. The rate of escalation was 12.3 vs. 11.3 per 1000 patient bed days (difference, 1.0; 95% CI, -2.8 to 4.7) and IPTW adjusted incidence rate ratio 1.43 (95% CI, 1.16-1.78; p < 0.001). Patients in the intervention group were more likely to receive cardiovascular medication orders (16.1% vs. 11.3%; 4.7%; 95% CI, 2.1-7.4%) and IPTW adjusted relative risk (RR) (1.74; 95% CI, 1.39-2.18; p < 0.001). Combined in-hospital and 30-day-mortality was lower in the intervention group (7% vs. 9.3%; -2.4%; 95% CI, -4.5% to -0.2%) and IPTW adjusted RR (0.76; 95% CI, 0.58-0.99; p = 0.045). CONCLUSIONS: Real-time machine learning alerts do not reduce the rate of escalation but may reduce mortality.


Subject(s)
Clinical Deterioration , Machine Learning , Humans , Female , Male , Prospective Studies , Middle Aged , Aged , Hospital Rapid Response Team/organization & administration , Hospital Rapid Response Team/statistics & numerical data , Hospital Mortality
14.
BMJ Paediatr Open ; 8(1)2024 02 07.
Article in English | MEDLINE | ID: mdl-38325899

ABSTRACT

INTRODUCTION: Early recognition of clinical deterioration and timely intervention are important to improve morbidity and mortality in paediatric care. The Paediatric Early Warning Score (PEWS) is a scoring system aiming to identify hospitalised children at risk for deterioration. Currently, there is a large heterogeneity of PEWS systems in the Netherlands, with a considerable number remaining unvalidated or self-designed. Therefore, a consensus-based Dutch PEWS has been developed in a national study using the Core Outcome Measures in Effectiveness Trials initiative. The Dutch PEWS is a uniform system that integrates a core set of vital parameters together with pre-existing risk factors and uses risk stratification to proactively follow-up on patients at risk (so-called 'watcher patients'). This study aims to validate the Dutch PEWS and to determine its impact on improving patient safety in various hospital settings. METHODS AND ANALYSIS: This national study will be a large multicentre evaluation study, in which the Dutch PEWS will be implemented and evaluated in 12 hospitals in the Netherlands. In this study, a mixed methods methodology will be used and evaluated on predefined outcome measures. To examine the validity of the Dutch PEWS, statistical analyses will be undertaken on quantitative data retrieved from electronic health records. Surveys among physicians and nurses; semistructured interviews with healthcare providers and parents; and daily evaluation forms are being conducted to determine the impact of the Dutch PEWS. The study is being conducted from December 2020 to June 2024.


Subject(s)
Clinical Deterioration , Early Warning Score , Humans , Child , Netherlands , Hospitals , Research Design , Multicenter Studies as Topic
15.
Br J Hosp Med (Lond) ; 85(2): 1-6, 2024 Feb 02.
Article in English | MEDLINE | ID: mdl-38416522

ABSTRACT

AIMS/BACKGROUND: Martha's rule stipulates the right of patients and their families to escalate care as a way to improve safety while in hospital. This article analyses the possible impact of the proposed policy through the lens of a behaviour change framework and explores new opportunities presented by the implementation of Martha's rule.. METHODS: A descriptive analysis was undertaken of interactions between patients, family, friends and clinicians during clinical deterioration in hospital. The capability-opportunity-motivation behaviour change framework was applied to understand reasons for failure to respond to deterioration. RESULTS: Care of deteriorating patients requires recording of vital signs, recognition of abnormalities, reporting through escalation and response by a competent clinician. Regarding the care of patients who deteriorate in hospital, healthcare professionals have capability and motivation to provide safe, high-quality care, but often lack the physical and social opportunity to report or respond through lack of time and peer pressure. Patients and family members have motivation and might have time to support safety systems. Martha's rule or similar arrangements allow healthcare organisations to create opportunities for patients and families to report and escalate care to experts in critical care when they recognise deterioration. CONCLUSIONS: The capability-opportunity-motivation behaviour change framework provides insights into the causes of failure to rescue in deteriorating patients and an argument for opportunities through escalation by patients and families through Martha's rule. This might reduce the number of system failures and enable safer care.


Subject(s)
Clinical Deterioration , Hospitals , Humans , Motivation , Critical Care , Dissent and Disputes
16.
Can J Surg ; 67(1): E70-E76, 2024.
Article in English | MEDLINE | ID: mdl-38383031

ABSTRACT

BACKGROUND: Trauma care in Nunavik, Quebec, is highly challenging. Geographic distances and delays in transport can translate into precarious patient transfers to tertiary trauma care centres. The objective of this study was to identify predictors of clinical deterioration during transport and eventual intensive care unit (ICU) admission for trauma patients transferred from Nunavik to a tertiary trauma care centre. METHODS: This is a retrospective cohort study using the Montreal General Hospital (MGH) trauma registry. All adult trauma patients transferred from Nunavik and admitted to the MGH from 2010 to 2019 were included. Main outcomes of interest were hemodynamic and neurologic deterioration during transport and ICU admission. RESULTS: In total, 704 patients were transferred from Nunavik and admitted to the MGH during the study period. The median age was 33 (interquartile range [IQR] 23-47) years and the median Injury Severity Score was 10 (IQR 5-17). On multiple regression analysis, transport time from site of injury to the MGH (odds ratio [OR] 1.04, 95% confidence interval [CI] 1.01-1.06), thoracic injuries (OR 1.75, 95% CI 1.03-2.99), and head and neck injuries (OR 3.76, 95% CI 2.10-6.76) predicted clinical deterioration during transfer. Injury Severity Score (OR 1.04, 95% CI 1.01-1.08), abnormal local Glasgow Coma Scale score (OR 2.57, 95% CI 1.34-4.95), clinical deterioration during transfer (OR 4.22, 95% CI 1.99-8.93), traumatic brain injury (OR 2.44, 95% CI 1.05-5.68), and transfusion requirement at the MGH (OR 4.63, 95% CI 2.35-9.09) were independent predictors of ICU admission. CONCLUSION: Our study identified several predictors of clinical deterioration during transfer and eventual ICU admission for trauma patients transferred from Nunavik. These factors could be used to refine triage criteria in Nunavik for more timely evacuation and higher level care during transport.


Subject(s)
Clinical Deterioration , Trauma Centers , Adult , Humans , Young Adult , Middle Aged , Retrospective Studies , Quebec/epidemiology , Intensive Care Units , Injury Severity Score
17.
Circ Heart Fail ; 17(2): e010837, 2024 02.
Article in English | MEDLINE | ID: mdl-38299331

ABSTRACT

BACKGROUND: In 2018, an algorithm-based allocation system for heart transplantation (HT) was implemented in France. Its effect on access to HT of patients with rare causes of heart failure (HF) has not been assessed. METHODS: In this national study, including adults listed for HT between 2018 and 2020, we analyzed waitlist and posttransplant outcomes of candidates with rare causes of HF (restrictive cardiomyopathy [RCM], hypertrophic cardiomyopathy, and congenital heart disease). The primary end point was death on the waitlist or delisting for clinical deterioration. Secondary end points included access to HT and posttransplant mortality. The cumulative incidence of waitlist mortality estimated with competing risk analysis and incidence of transplantation were compared between diagnosis groups. The association of HF cause with outcomes was determined by Fine-Gray or Cox models. RESULTS: Overall, 1604 candidates were listed for HT. At 1 year postlisting, 175 patients met the primary end point and 1040 underwent HT. Candidates listed for rare causes of HF significantly differed in baseline characteristics and had more frequent score exceptions compared with other cardiomyopathies (31.3%, 32.0%, 36.4%, and 16.7% for patients with hypertrophic cardiomyopathy, RCM, congenital heart disease, and other cardiomyopathies). The cumulative incidence of death on the waitlist and probability of HT were similar between diagnosis groups (P=0.17 and 0.40, respectively). The adjusted risk of death or delisting for clinical deterioration did not significantly differ between candidates with rare and common causes of HF (subdistribution hazard ratio (HR): hypertrophic cardiomyopathy, 0.51 [95% CI, 0.19-1.38]; P=0.18; RCM, 1.04 [95% CI, 0.42-2.58]; P=0.94; congenital heart disease, 1.82 [95% CI, 0.78-4.26]; P=0.17). Similarly, the access to HT did not significantly differ between causes of HF (hypertrophic cardiomyopathy: HR, 1.18 [95% CI, 0.92-1.51]; P=0.19; RCM: HR, 1.19 [95% CI, 0.90-1.58]; P=0.23; congenital heart disease: HR, 0.76 [95% CI, 0.53-1.09]; P=0.14). RCM was an independent risk factor for 1-year posttransplant mortality (HR, 2.12 [95% CI, 1.06-4.24]; P=0.03). CONCLUSIONS: Our study shows equitable waitlist outcomes among HT candidates whatever the indication for transplantation with the new French allocation scheme.


Subject(s)
Cardiomyopathies , Cardiomyopathy, Hypertrophic , Cardiomyopathy, Restrictive , Clinical Deterioration , Heart Defects, Congenital , Heart Failure , Heart Transplantation , Adult , Humans , Heart Failure/diagnosis , Heart Failure/surgery , Heart Failure/complications , Cardiomyopathies/complications , Heart Transplantation/adverse effects , Cardiomyopathy, Hypertrophic/complications , Cardiomyopathy, Restrictive/complications , Waiting Lists , Retrospective Studies
18.
J Med Internet Res ; 26: e53343, 2024 Mar 29.
Article in English | MEDLINE | ID: mdl-38414056

ABSTRACT

BACKGROUND: Few studies have used standardized nursing records with Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) to identify predictors of clinical deterioration. OBJECTIVE: This study aims to standardize the nursing documentation records of patients with COVID-19 using SNOMED CT and identify predictive factors of clinical deterioration in patients with COVID-19 via standardized nursing records. METHODS: In this study, 57,558 nursing statements from 226 patients with COVID-19 were analyzed. Among these, 45,852 statements were from 207 patients in the stable (control) group and 11,706 from 19 patients in the exacerbated (case) group who were transferred to the intensive care unit within 7 days. The data were collected between December 2019 and June 2022. These nursing statements were standardized using the SNOMED CT International Edition released on November 30, 2022. The 260 unique nursing statements that accounted for the top 90% of 57,558 statements were selected as the mapping source and mapped into SNOMED CT concepts based on their meaning by 2 experts with more than 5 years of SNOMED CT mapping experience. To identify the main features of nursing statements associated with the exacerbation of patient condition, random forest algorithms were used, and optimal hyperparameters were selected for nursing problems or outcomes and nursing procedure-related statements. Additionally, logistic regression analysis was conducted to identify features that determine clinical deterioration in patients with COVID-19. RESULTS: All nursing statements were semantically mapped to SNOMED CT concepts for "clinical finding," "situation with explicit context," and "procedure" hierarchies. The interrater reliability of the mapping results was 87.7%. The most important features calculated by random forest were "oxygen saturation below reference range," "dyspnea," "tachypnea," and "cough" in "clinical finding," and "oxygen therapy," "pulse oximetry monitoring," "temperature taking," "notification of physician," and "education about isolation for infection control" in "procedure." Among these, "dyspnea" and "inadequate food diet" in "clinical finding" increased clinical deterioration risk (dyspnea: odds ratio [OR] 5.99, 95% CI 2.25-20.29; inadequate food diet: OR 10.0, 95% CI 2.71-40.84), and "oxygen therapy" and "notification of physician" in "procedure" also increased the risk of clinical deterioration in patients with COVID-19 (oxygen therapy: OR 1.89, 95% CI 1.25-3.05; notification of physician: OR 1.72, 95% CI 1.02-2.97). CONCLUSIONS: The study used SNOMED CT to express and standardize nursing statements. Further, it revealed the importance of standardized nursing records as predictive variables for clinical deterioration in patients.


Subject(s)
COVID-19 , Clinical Deterioration , Humans , Nursing Records , Reproducibility of Results , Dyspnea , Oxygen
19.
Intensive Crit Care Nurs ; 83: 103628, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38244252

ABSTRACT

OBJECTIVES: This prospective cohort study aimed to assess the predictive value of the Nurse Intuition Patient Deterioration Scale (NIPDS) combined with the National Early Warning Score (NEWS) for identifying serious adverse events in patients admitted to diverse hospital wards. RESEARCH METHODOLOGY/DESIGN: Data was collected between December 2020 and February 2021 in a 350-bed acute hospital near Brussels, Belgium. The study followed a prospective cohort design, employing NIPDS alongside NEWS for risk assessment. Patients were monitored for 24 h post-registration, with outcomes recorded. SETTING: The study was conducted in a hospital with a Rapid Response System (RRS) and electronic patient record wherein NEWS was routinely collected. Patients admitted to two medical, two surgical, and two geriatric wards were included. MAIN OUTCOME MEASURES: The primary outcome included death, urgent code calls, or unplanned ICU transfers within 24 h after NIPDS registration. The secondary outcome comprised rapid response team activations or changes in Do-Not-Resuscitate codes. RESULTS: In a cohort of 313 patients, 10/313 and 31/313 patients reached the primary and secondary outcome respectively. For the primary outcome, NIPDS had a sensitivity of 0.900 and specificity of 0.927, while NEWS had a sensitivity of 0.300 and specificity of 0.974. Decision Curve Analysis demonstrated that NIPDS provided more Net Benefit across various Threshold Probabilities. Combining NIPDS and NEWS showed potential for optimizing rapid response systems. Especially in resource-constrained settings, NIPDS could be used as a calling criterion. CONCLUSION: The NIPDS displayed strong predictive capabilities for adverse events. Integrating NIPDS into existing rapid response systems can objectify nurse intuition, enhancing patient safety. IMPLICATIONS FOR CLINICAL PRACTICE: The Nurse Intuition Patient Deterioration Scale (NIPDS) is a valuable tool for detecting patient deterioration. Implementing NIPDS alongside traditional scores such as NEWS can improve patient care and safety. The optimal NIPDS threshold to activate rapid response is ≥5.


Subject(s)
Early Warning Score , Humans , Prospective Studies , Female , Male , Aged , Belgium , Cohort Studies , Middle Aged , Aged, 80 and over , Clinical Deterioration , Adult , Predictive Value of Tests
20.
Jt Comm J Qual Patient Saf ; 50(7): 507-515, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38220586

ABSTRACT

BACKGROUND: Maternal morbidity and mortality is rising in the United States. Previous studies focus on patient attributes, and most of the national data are based on research performed at urban tertiary care centers. Although it is well understood that nurses affect patient outcomes, there is scant evidence to understand the nurse work system, and no studies have specifically studied rural nurses. The authors sought to understand the systems-level factors affecting rural obstetric nurses when their patients experience clinical deterioration. METHODS: The research team used a qualitative descriptive approach, including a modified critical incident technique, in interviews with bedside nurses (n = 7) and physicians (n = 4) to understand what happens when patients experience clinical deterioration. Physicians were included to better understand the systems in which nurses work. Clinicians were interviewed at three rural hospitals in New England, with a mean births per year of 190. FINDINGS: Six systems-level factors/themes were identified: (1) shortages of resources; (2) need for teamwork; (3) physicians' multiple conflicting and simultaneous responsibilities, such as seeing patients in the office while women labor on the hospital floor; (4) need for all team members to be at the top of their game; (5) process issues during high-acuity patient transfer, including difficulty finding available beds at tertiary care centers; and (6) insufficient policies that take low-resource contexts into account, such as requiring two registered nurses to remove emergency medications from the medication cabinet. CONCLUSION: Rural nurses need policies and protocols that are written with their hospital context in mind. Hospitals may need outside support for content expertise, but policies should be co-created with clinicians with rural practice experience.


Subject(s)
Qualitative Research , Humans , Female , Obstetric Nursing , Hospitals, Rural/organization & administration , Pregnancy , Clinical Deterioration , Patient Care Team/organization & administration , Interviews as Topic , New England , Nursing Staff, Hospital/organization & administration , Emergencies , Health Resources
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