Can fluctuations in vital signs be used for pain assessment in critically ill patients with a traumatic brain injury?

Inpatient pain assessment and decision-making in internal medicine and general surgery residents: A qualitative analysis

Background

Understanding physician approaches to pain treatment is a critical component of opioid and analgesic stewardship. Practice patterns learned in residency often persist longitudinally into practice.

Objective

This study sought to identify salient factors and themes in how resident physicians assess and manage pain.

Methods

Video-recorded focus groups of internal medicine and general surgery residents were conducted via videoconferencing software. Data were analyzed using a ground theory approach and constant comparative method to identify themes and subthemes. Focus groups occurred in September and October 2020.

Results

10 focus groups including 35 subjects were conducted. Four general themes emerged: (1) Assessment considerations; (2) Education & Expectations; (3) Systems Factors; and (4) Management considerations. Participants indicated that while it is important to treat pain, its inherently subjective nature makes it difficult to objectively quantify it. The 0-10 numeric rating scale was problematic and infrequently utilized. Patient expectations of no pain following procedures was viewed as particularly challenging. The absence of formal best practices to guide pain assessment and management was noted in every group. Management approaches overall very highly variable, often relying on word-of-mouth relay of the preferences of specific attending physicians.

Conclusions

Pain is highly nuanced and resident physicians struggle to balance pain's subjectivity with a desire to quantify and appropriately treat it. The 0-10 numeric rating pain scale, though ubiquitous, is problematic. Priority areas of improvement identified include education for both patients and physicians, functional pain scales, and expansion of existing effective resources like the nursing pain team.

Diurnal Pain Classification in Critically Ill Patients using Machine Learning on Accelerometry and Analgesic Data

Quantifying pain in patients admitted to intensive care units (ICUs) is challenging due to the increased prevalence of communication barriers in this patient population. Previous research has posited a positive correlation between pain and physical activity in critically ill patients. In this study, we advance this hypothesis by building machine learning classifiers to examine the ability of accelerometer data collected from daily wearables to predict self-reported pain levels experienced by patients in the ICU. We trained multiple Machine Learning (ML) models, including Logistic Regression, CatBoost, and XG-Boost, on statistical features extracted from the accelerometer data combined with previous pain measurements and patient demographics. Following previous studies that showed a change in pain sensitivity in ICU patients at night, we performed the task of pain classification separately for daytime and nighttime pain reports. In the pain versus no-pain classification setting, logistic regression gave the best classifier in daytime (AUC: 0.72, F1-score: 0.72), and CatBoost gave the best classifier at nighttime (AUC: 0.82, F1-score: 0.82). Performance of logistic regression dropped to 0.61 AUC, 0.62 F1-score (mild vs. moderate pain, nighttime), and CatBoost's performance was similarly affected with 0.61 AUC, 0.60 F1-score (moderate vs. severe pain, daytime). The inclusion of analgesic information benefited the classification between moderate and severe pain. SHAP analysis was conducted to find the most significant features in each setting. It assigned the highest importance to accelerometer-related features on all evaluated settings but also showed the contribution of the other features such as age and medications in specific contexts. In conclusion, accelerometer data combined with patient demographics and previous pain measurements can be used to screen painful from painless episodes in the ICU and can be combined with analgesic information to provide moderate classification between painful episodes of different severities.

The Validity of Vital Signs for Pain Assessment in critically Ill Adults: A Narrative Review

OBJECTIVES

Pain assessment in the intensive care unit (ICU) is challenging because many patients are unable to self-report or exhibit pain-related behaviors. In such situations, vital signs (VS) through continuous monitoring are alternative cues for pain assessment. This review aimed to describe the reliability and validity of VS for ICU pain assessment.

DESIGN

Narrative review of the literature.

DATA SOURCES

Medline, Embase, CINAHL, Cochrane.

REVIEW/ANALYSIS METHODS

A narrative review was conducted with a comprehensive search in four databases. Search terms included VS, pain assessment, and ICU.

RESULTS

Out of 1,359 results, 30 studies from 17 countries were included. Heart rate, blood pressure, and respiratory rate were most used for ICU pain assessment. Assessments were performed at rest before procedures, during nociceptive and non-nociceptive procedures, and after procedures. Increases in respiratory rate were clinically significant by more than 25% during nociceptive procedures (e.g., endotracheal suctioning, turning) compared with rest/pre-procedures in five studies. Correlations of VS with self-reported pain (reference standard measure) and behavioral pain scores (alternative measure) were absent or weak.

CONCLUSIONS

VS are not valid indicators for ICU pain assessment. Increases of respiratory rate may be a cue for the detection of pain. However, fluctuations in respiratory rate can be influenced by opioids or controlled ventilation mode. Our results dissuade the use of VS for pain assessment because of the lack of association with ICU pain reference standards. Other physiologic measures of pain in critically ill adults should be explored.

Induced pain affects auricular and body biosignals: From cold stressor to deep breathing

Pain affects every fifth adult worldwide and is a significant health problem. From a physiological perspective, pain is a protective reaction that restricts physical functions and causes responses in physiological systems. These responses are accessible for evaluation via recorded biosignals and can be favorably used as feedback in active pain therapy via auricular vagus nerve stimulation (aVNS). The aim of this study is to assess the significance of diverse parameters of biosignals with respect to their deflection from cold stressor to deep breathing and their suitability for use as biofeedback in aVNS stimulator. Seventy-eight volunteers participated in two cold pressors and one deep breathing test. Three targeted physiological parameters (RR interval of electrocardiogram, cardiac deflection magnitude Z _AC of ear impedance signal, and cardiac deflection magnitude PPG _AC of finger photoplethysmogram) and two reference parameters (systolic and diastolic blood pressures BP _S and BP _D) were derived and monitored. The results show that the cold water decreases the medians of targeted parameters (by 5.6, 9.3%, and 8.0% of RR, Z _AC, and PPG _AC, respectively) and increases the medians of reference parameters (by 7.1% and 6.1% of BP _S and BP _D, respectively), with opposite changes in deep breathing. Increasing pain level from relatively mild to moderate/strong with cold stressor varies the medians of targeted and reference parameters in the range from 0.5% to 6.0% (e.g., 2.9% for RR, Z _AC and 6.0% for BP _D). The physiological footprints of painful cold stressor and relaxing deep breathing were shown for auricular and non-auricular biosignals. The investigated targeted parameters can be used as biofeedback to close the loop in aVNS to personalize the pain therapy and increase its compliance.

Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit

Patients in critical care settings often require continuous and multifaceted monitoring. However, current clinical monitoring practices fail to capture important functional and behavioral indices such as mobility or agitation. Recent advances in non-invasive sensing technology, high throughput computing, and deep learning techniques are expected to transform the existing patient monitoring paradigm by enabling and streamlining granular and continuous monitoring of these crucial critical care measures. In this review, we highlight current approaches to pervasive sensing in critical care and identify limitations, future challenges, and opportunities in this emerging field.

Improving Pain Assessment using Vital Signs and Pain Medication for patients with Sickle Cell Disease: Retrospective Study (Preprint)

Background

Sickle cell disease (SCD) is the most common inherited blood disorder affecting millions of people worldwide. Most patients with SCD experience repeated, unpredictable episodes of severe pain. These pain episodes are the leading cause of emergency department visits among patients with SCD and may last for several weeks. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting a patient’s pain intensity level.

Objective

This study aims to learn deep feature representations of subjective pain trajectories using objective physiological signals collected from electronic health records.

Methods

This study used electronic health record data collected from 496 Duke University Medical Center participants over 5 consecutive years. Each record contained measures for 6 vital signs and the patient’s self-reported pain score, with an ordinal range from 0 (no pain) to 10 (severe and unbearable pain). We also extracted 3 features related to medication: medication type, medication status (given or applied, or missed or removed or due), and total medication dosage (mg/mL). We used variational autoencoders for representation learning and designed machine learning classification algorithms to build pain prediction models. We evaluated our results using an accuracy and confusion matrix and visualized the qualitative data representations.

Results

We designed a classification model using raw data and deep representational learning to predict subjective pain scores with average accuracies of 82.8%, 70.6%, 49.3%, and 47.4% for 2-point, 4-point, 6-point, and 11-point pain ratings, respectively. We observed that random forest classification models trained on deep represented features outperformed models trained on unrepresented data for all pain rating scales. We observed that at varying Likert scales, our models performed better when provided with medication data along with vital signs data. We visualized the data representations to understand the underlying latent representations, indicating neighboring representations for similar pain scores with a higher resolution of pain ratings.

Conclusions

Our results demonstrate that medication information (the type of medication, total medication dosage, and whether the medication was given or missed) can significantly improve subjective pain prediction modeling compared with modeling with only vital signs. This study shows promise in data-driven estimated pain scores that will help clinicians with additional information about the patient’s condition, in addition to the patient’s self-reported pain scores.

Behavioral and Physiological Pain Responses in Brain-Injured Patients Who Are Unable to Communicate in the Intensive Care Unit

BACKGROUND

Assessing pain of critically ill patients with brain injuries who are unable to communicate is a challenge. Current behavioral scales are limited in accurate pain assessments for this population.

AIMS

This study sought to investigate the behavioral and physiological responses induced by routine painful procedures in patients with brain injuries who are unable to communicate.

METHODS

Using a repeated-measure within-subject observational study design, 12 participants admitted to an intensive care unit were observed before, during, and 15 minutes after a nonnociceptive (noninvasive blood pressure measurement) procedure and three nociceptive (suctioning, turning, and trapezius pinch) procedures. During each assessment, patients' behavioral and physiological responses were observed using video cameras and bedside monitors.

RESULTS

In the overall behavioral responses to the nociceptive procedures, clenched teeth with tense jaw, frowning, orbit tightening, closing of eyes, eye movement, fixation-staring, flushing, flexion withdrawal of arm, flexion withdrawal of leg, muscle rigidity, twitching, and coughing were more frequently observed during procedures than before and after procedures (p < .01). Regarding physiological responses, significant increases in systolic blood pressure, diastolic blood pressure, mean arterial pressure, heart rate, and respiratory rate were identified across assessments (p < .001).

CONCLUSIONS

The findings can be used as a basis for pain assessment and the development of pain assessment tools for brain-injured patients who are unable to communicate. However, since physiological responses may be influenced by various factors besides pain, physiological changes may be used as a sign of the need for pain assessment rather than being used alone as a basis for pain assessment.

Comparison of the Zurich Observation Pain Assessment with the Behavioural Pain Scale and the Critical Care Pain Observation Tool in nonverbal patients in the intensive care unit: A prospective observational study

OBJECTIVES

To determine the concordance of Zurich Observation Pain Assessment (ZOPA) with the behavioural Pain Scale (BPS) and the Critical Care Pain Observation Tool (CPOT) to detect pain in nonverbal ICU patients.

DESIGN

Prospective observational study [BASEC-Nr. PB_2016-02324].

SETTING

A total of 49 ICU patients from cardiovascular, visceral and thoracic surgery and neurology and neurosurgery were recruited. Data from 24 patients were analyzed.

MAIN OUTCOME MEASUREMENTS

Three independent observers assessed pain with the BPS, the CPOT or ZOPA prior, during and after a potential painful nursing intervention. Tools were randomized concerning the pain management after each pain assessment. Frequency of nine additional pain indicating items from a previous qualitative, explorative study was calculated.

RESULTS

ZOPA was positive in 32 of 33 measuring cycles (97.0%; 95%CI: 84.2-99.9%), followed by the CPOT (28/33 cycles, 84.8%; 95%CI: 68.1-94.9%) and the BPS (23/33 cycles, 67.0%; 95%CI: 51.3-84.4%). In 22/33 cycles all tools were concordant (66.7%; 95%CI: 48.2-82.0%). Analgesics were provided in 29 out of 33 cycles (87.9%; 95%CI: 71.8-96.6%). Additional pain indicating items were inconsistently reported.

CONCLUSION

ZOPA is concordant with the BPS and the CPOT to indicate pain but detects pain earlier due to the low threshold value. Inclusion of further items does not improve pain assessment.

Acute pain intensity monitoring with the classification of multiple physiological parameters

Current acute pain intensity assessment tools are mainly based on self-reporting by patients, which is impractical for non-communicative, sedated or critically ill patients. In previous studies, various physiological signals have been observed qualitatively as a potential pain intensity index. On the basis of that, this study aims at developing a continuous pain monitoring method with the classification of multiple physiological parameters. Heart rate (HR), breath rate (BR), galvanic skin response (GSR) and facial surface electromyogram were collected from 30 healthy volunteers under thermal and electrical pain stimuli. The collected samples were labelled as no pain, mild pain or moderate/severe pain based on a self-reported visual analogue scale. The patterns of these three classes were first observed from the distribution of the 13 processed physiological parameters. Then, artificial neural network classifiers were trained, validated and tested with the physiological parameters. The average classification accuracy was 70.6%. The same method was applied to the medians of each class in each test and accuracy was improved to 83.3%. With facial electromyogram, the adaptivity of this method to a new subject was improved as the recognition accuracy of moderate/severe pain in leave-one-subject-out cross-validation was promoted from 74.9 ± 21.0 to 76.3 ± 18.1%. Among healthy volunteers, GSR, HR and BR were better correlated to pain intensity variations than facial muscle activities. The classification of multiple accessible physiological parameters can potentially provide a way to differentiate among no, mild and moderate/severe acute experimental pain.

Nurses' Assessment Practices of Pain Among Critically Ill Patients

BACKGROUND

Systematic pain assessment is necessary to ensure effective pain management. Despite the availability of recommendations, guidelines, and valid tools for pain assessment, the actual implementation in clinical practice is inconsistent.

AIMS

The purpose of this study was to investigate intensive care nurses' pain assessment practices among critically ill patients in Jordanian hospitals.

DESIGN

A descriptive cross sectional design was used in this study.

SETTINGS

This study was conducted in 22 intensive care unites located in eight hospitals in Jordan.

PARTICIPANTS/SUBJECTS

Convenience sampling was used to recruit a sample of 300 nurses working in intensive care units.

METHODS

The Pain Assessment and Management for the Critically Ill survey was used to collect data. Descriptive statistics, χ², and correlational analysis were used to analyze data.

RESULTS

A total of 89.7% of nurses (N = 300) used pain assessment tools with patients able to communicate, and the numeric rating scale was the most commonly used tool. A total of 81.7% of the nurses used a pain assessment tool with patients unable to communicate, and the Adult Nonverbal Pain Scale was the most commonly used tool. Nurses' perceived importance of pain assessment was positively associated with frequent use of pain assessment tools. Nurses perceived the use of pain assessment tools for patients able to communicate as being more important than the use of pain assessment tools for patients unable to communicate.

CONCLUSIONS

The majority of intensive care unit nurses used pain assessment tools for patients both able and unable to communicate; however, the most valid and reliable tools were not used often. Nurses were not aware of the pain behaviors most indicative of pain among critically ill patients.

Observational Pain Assessment Instruments for Use With Nonverbal Patients at the End-of-life: A Systematic Review

Purpose:

To review studies pertaining to the reliability and validity of observational pain assessment tools for use with nonverbal patients at the end-of-life, a field of research not documented by previous systematic reviews.

Methods:

Databases (PubMed, Embase, Epistemonikos, the Cochrane Library, and CINAHL) were systematically searched for studies from study inception to February 21, 2016 (update in May 9, 2018). Two independent reviewers screened study titles, abstracts, and full texts according to inclusion and exclusion criteria. Disagreements were resolved through consensus. Reviewers also extracted the psychometrics properties of studies of observational pain assessment instruments dedicated to a noncommunicative population in palliative care or at the end-of-life. A comprehensive quality assessment was conducted using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) to derive poor, fair, good or excellent ratings for the psychometric tests reported in each study.

Results:

Four studies linked to 4 different tools met the inclusion criteria. Study populations included dementia, palliative care and severe illness in the context of intensive care. All the studies included in this review obtained poor COSMIN ratings overall.

Conclusions:

At this point, it is impossible to recommend any of the tools evaluated given the low number and quality of the studies. Other analyses and studies need to be conducted to develop, adapt, or further validate observational pain instruments for the end-of-life population, regardless of the disease.

Psychometric Properties of the Behavioral Pain Scale in Traumatic Brain Injury

BACKGROUND

Pain assessment of patients with traumatic brain injury is a challenge because they are unable to self-report their pain experience.

AIMS

To investigate the psychometric properties of validity, reliability, and responsiveness of the Brazilian version of the Behavioral Pain Scale (BPS-Br) in patients with traumatic brain injury.

METHODS

This was an observational, cross-sectional, repeated-measure and analytical study. This study was developed at the medical and surgical ICUs in a high-complexity public hospital at Aracaju, Sergipe, Brazil. Thirty-seven adult patients with moderate or severe TBI were included. This study was completed with 444 independent observations, a pairwise comparison, and was performed simultaneously before, during, and after eye cleaning and endotracheal suctioning of 37 adult patients with moderate to severe traumatic brain injury.

RESULTS

The BPS-Br had good internal consistency (.7 ≤ α ≤ .9), good discriminant validity (p < .001), moderate to excellent reliability based on inter-rater agreement (intraclass correlation coefficient = 0.66-1.00; κ = 0.5-1.0), and high responsiveness (0.7-1.7). The upper limbs subscale had the highest score during the nociceptive procedure (1.8 ± 0.9). Deep sedation affected the increase of grading during painful procedures (p < .001).

CONCLUSIONS

Our results suggest the BPS-Br is a useful tool for clinical practice to evaluate the pain experienced by patients with traumatic brain injury. Further studies of different samples are needed to evaluate the benefits of systematic pain assessment of critically ill patients.

Pain among non-verbal critically Ill mechanically ventilated patients: Prevalence, correlates and predictors

PURPOSE

To investigate pain levels and factors that are predictive of pain for mechanically ventilated patients during rest and during routine nursing procedures.

MATERIAL AND METHODS

Pain levels were assessed using Behavioral Pain Scale (BPS) and physiological measures among 247 mechanically ventilated patients.

RESULTS

At rest, 33.2% of patients suffered pain, with a BPS > 3; of these, 10% presented significant pain levels (BPS ≥ 5). Variables that correspondingly predicted resting pain were age (β = -0.010, p < 0.001), sedation score (β = -0.153, p < 0.01), and method of ventilation (β = -0.281, p = 0.021). During the procedures, 90% of patients suffered pain, with a median BPS of 6 (IQR: 4-8), and 83% of patients experienced significant pain levels. Age (β = -0.022, p = 0.001), sedation score (β = -0.355, p < 0.001), receiving sedation and/or analgesia in last hour (β = 0.483, p = 0. 01), resting pain levels (β = -0.742, p < 0.001) and the type of painful procedure (β = -0.906, p < 0.001) were significant predictors of procedural pain.

CONCLUSIONS

Many mechanically ventilated patients suffer resting and procedural pain. Many variables were found to play a role. Clinicians need to consider these variables and intervene to decrease pain among patients at risk.

Pain assessment of traumatic brain injury victims using the Brazilian version of the Behavioral Pain Scale

Objective

To evaluate the validity and reliability of the Brazilian version of the Behavioral Pain Scale (BPS-Br) in victims of traumatic brain injury.

Methods

Observational prospective study with paired and repeated measures conducted at two intensive care units (clinical and surgical) of a large general hospital. The convenience sample consisted of adult victims of moderate or severe penetrating or blunt craniocerebral trauma who were sedated and mechanically ventilated. A total of 432 paired observations were performed by independent evaluators simultaneously, prior to eye cleaning, during eye cleaning, during tracheal aspiration and after tracheal aspiration. Sociodemographic, clinical, trauma-related, sedoanalgesia and physiological parameter data (heart rate, systolic and diastolic blood pressure) were collected. The discriminant validity was tested using the Friedman and Wilcoxon paired tests. The intraclass correlation coefficient and Cohen's Kappa coefficient were used to evaluate the reliability. The Spearman correlation test was used to test the association between clinical variables and BPS-Br scores during tracheal aspiration.

Results

There was a significant increase in the physiological parameters during tracheal aspiration, but without correlation with the BPS-Br scores. Pain was significantly more intense during tracheal aspiration (p < 0.005). Satisfactory interobserver agreement was found, with an intraclass correlation coefficient of 0.95 (0.90 - 0.98) and Kappa coefficient of 0.70.

Conclusion

Brazilian version of the Behavioral Pain Scale scores increased during tracheal aspiration. The Brazilian version of the scale was valid and reliable for pain assessment of traumatic brain injury victims undergoing tracheal aspiration.

Use of the critical-care pain observation tool and the bispectral index for the detection of pain in brain-injured patients undergoing mechanical ventilation: A STROBE-compliant observational study

The assessment of pain in patients with brain injury is challenging due to impaired ability to communicate. We aimed to test the reliability and validity of the critical-care pain observation tool (CPOT) and the bispectral index (BIS) for pain detection in critically brain-injured patients.This prospective observational study was conducted in a neurosurgical intensive care unit in a University-Affiliated Hospital. Adult brain-injured patients undergoing mechanical ventilation were enrolled. Nociceptive (endotracheal suctioning) and non-nociceptive (gentle touching) procedures were performed in a random crossover fashion. Before and immediately after the procedure, CPOT was evaluated by 2 residents and 2 chief nurses, and BIS was documented. The ability to self-report pain was also assessed. The inter-observer reliability of CPOT was analyzed. The criterion and discriminant validities of the CPOT and the BIS were tested.During the study, we enrolled 400 brain-injured patients. The ability to self-report pain was maintained in 214 (54%) and 218 (55%) patients during suctioning and gentle touching, respectively. The intraclass correlation coefficients (95% confidence interval) for inter-observer reliability of CPOT ranged from 0.86 (0.83-0.89) to 0.93 (0.91-0.94). Using self-reported pain as the reference, the area under the receiver operating characteristic curve (95% confidence interval) was 0.84 (0.80-0.88) for CPOT and 0.76 (0.72-0.81) for BIS. When the 2 instruments were combined as either CPOT ≥2 or BIS ≥88 after the procedure, the sensitivity and specificity were 0.90 (0.85-0.93) and 0.59 (0.52-0.66), respectively; and when the 2 instruments were combined as both CPOT ≥2 and BIS ≥88, the sensitivity and specificity were 0.62 (0.55-0.68) and 0.89 (0.83-0.93). Both CPOT and BIS increased significantly after suctioning (all P < .001) but remained unchanged after gentle touching (P ranging from .06 to .14).Our criterion and discriminant validity results supported the use of CPOT and BIS to detect pain in critically brain-injured patients. Combining use of CPOT and BIS in different ways might provide comprehensive pain assessment for different purposes.

A Study on the Psychometric Properties of Revised-nonverbal Pain Scale and Original-nonverbal Pain Scale in Iranian Nonverbal-ventilated Patients

Background and Aims:

The nonverbal pain scale is one of the instruments which study pain in nonverbal-ventilated patients with regard to the changes of behavioral and physiological indices. The purpose of the study is to survey the psychometric properties of revised-nonverbal pain scale (R-NVPS) and original-nonverbal pain scale (O-NVPS) in ventilated patients hospitalized in critical care units.

Materials and Methods:

Four nurses studied pain in sixty patients hospitalized in trauma, medical, neurology, and surgical critical care units using R-NVPS and O-NVPS at six times (before, during, and after nociceptive and nonnociceptive procedures). The test was repeated in 37 patients after 8–12 h.

Results:

Cronbach's alpha coefficient for R-NVPS and O-NVPS was 0.8 and 0.76, respectively. The inter-rater correlation coefficient during different times was r = 0.89–0.96 for R-NVPS and r = 0.80–0.87 for O-NVPS. Test-retest correlation coefficient for R-NVPS and O-NVPS was r = 0.55–0.86 and r = 0.51–0.75, respectively. The meaningful difference in pain score between nociceptive and nonnociceptive procedures (P < 0.001) and a higher pain score in patients who confirmed pain (P < 0.001) showed a discriminant and criterion validity for both scales of NVPS, respectively.

Conclusions:

R-NVPS and O-NVPS can both be used as valid and reliable scales in studying pain in ventilated patient. However, in comparing the items, “respiration” (R-NVPS) had a higher sensitivity than “physiology II” (O-NVPS) in assessing pain.

Validation of the Behavioural Indicators of Pain Scale ESCID for pain assessment in non-communicative and mechanically ventilated critically ill patients: a research protocol

AIM

To investigate the validity and reliability of the Behavioural Indicators of Pain Scale (ESCID) in medically and surgically non-communicative and mechanically ventilated critical patients.

BACKGROUND

Scales based on behavioural indicators of pain are suggested to measure pain in non-communicative critically ill patients. Scales proposed thus far have a range not comparable to those used with patients who can report their pain. A scale with a 0-10 range and more behavioural indicators is proposed to improve the detection and measurement of pain.

DESIGN

A multicentre prospective observational design to validate a scale-measuring instrument.

METHODS

Three hundred non-communicative and mechanically ventilated critical patients from 20 different intensive care units will be observed for 5 minutes before, during and 15 minutes after three procedures: turning, tracheal suctioning and soft friction with gauze on healthy tissue. Two independent observers will assess the pain of subjects with the Behavioural Pain Scale and the ESCID scale simultaneously. Descriptive and inferential statistics will be used. Student's t-test will be used to compare components of the twos scales. Inter-rater and intrarater agreement will be investigated. The reliability scale will be measured using Cronbach's alpha. Approval date for this protocol was January 2012.

DISCUSSION

A greater number of behavioural indicators in the ESCID scale than in previously validated scales, with a 0-10 score range, can improve the detection and measurement of pain in non-communicative and mechanically ventilated critical patients. Funding granted in 2011 by the Spanish Health Research Fund (PI 11/00766, Health Ministry).

TRIAL REGISTRATION

Study registered with www.clinicaltrials.gov (NCT01744717).

Generating and selecting pain indicators for brain-injured critical care patients

Current pain assessment tools for nonverbal critical care patients may not be appropriate for those with brain injury, as these patients demonstrate specific responses to pain. The aim of this study was to generate and select items that could be used to assess pain in brain-injured patients. A sequential mixed-method design was chosen with three consecutive steps: 1. Generate items with a literature review, the results of a pilot study, and interviews with 18 clinicians using the nominal group technique. 2. Evaluate content validity with 10 clinicians and four scientists, using a web-based questionnaire. 3. Describe and reduce items with the observation of 116 brain-injured patients in the intensive care unit during common painful procedures. This study took place between May 2010 and October 2011 in two tertiary hospitals in Western Switzerland. Forty-seven items were generated and reduced to 33 during the content validity process. The behaviors most frequently observed during turning were closing the eyes (58.6%), eye movements (57.8%), ventilator asynchrony (55.2%), and frowning/brow lowering (50%). Five items were observed in less than 5% of the patients during nociceptive procedure. Constant motor activity was observed more frequently at rest than during nociceptive stimulation. All physiologic items showed little variability and their reliability was low. Based on these results, the number of items was reduced to 23. This study identified items that could be specific to brain-injured patients and found that the variability of physiologic items was poorly assessed by clinicians.

Pain among mechanically ventilated patients in critical care units

BACKGROUND

Pain is a common experience among mechanically ventilated patients. Pain among mechanically ventilated patients is aggravated by factors such as stage of illness, invasive procedures, and surgical interventions. The aim to this study was to investigate pain levels and predictors among mechanically ventilated patients during rest and routine nursing interventions.

MATERIALS AND METHODS

A cross-sectional descriptive correlational design was used, with a total sample of 301 mechanically ventilated patients. Patients' pain levels were assessed using Behavioral Pain Scale during rest and routine nursing interventions.

RESULTS

The mean pain score levels during rest (mean = 3.69, standard deviation [SD] = 0.81) were lower than mean pain score levels during routine nursing interventions (mean = 7.1, SD = 2.5). During rest, pain scores were significantly correlated with age (r = -0.12, P = 0.046), and heart rate (r = 0.24, P < 0.001). During nursing interventions, pain scores were significantly correlated with age (r = -0.25, P < 0.001), heart rate (r = 0.36, P < 0.001), and diastolic blood pressure (BP) (r = 0.21, P < 0.001). The age and past surgical history were found to be significant (age: β = -0.009, P = 0.002; past surgical history: β = -1.376, P < 0.001).

CONCLUSION

Mechanically ventilated patients experience pain during rest as well as during routine nursing interventions. Pain levels were associated with age, heart rate, and diastolic BP. The age and past surgical history should be considered as important predictive factors.