Narrative Review of Prolonged Times to Tracheal Extubation After General Anesthesia With Intubation and Extubation in the Operating Room.

This narrative review summarizes research about prolonged times to tracheal extubation after general anesthesia with both intubation and extubation occurring in the operating room or other anesthetizing location where the anesthetic was performed. The literature search was current through May 2023 and included prolonged extubations defined either as >15 minutes or at least 15 minutes. The studies showed that prolonged times to extubation can be measured accurately, are associated with reintubations and respiratory treatments, are rated poorly by anesthesiologists, are treated with flumazenil and naloxone, are associated with impaired operating room workflow, are associated with longer operating room times, are associated with tardiness of starts of to-follow cases and surgeons, and are associated with longer duration workdays. When observing prolonged extubations among all patients receiving general anesthesia, covariates accounting for most prolonged extubations are characteristics of the surgery, positioning, and anesthesia provider's familiarity with the surgeon. Anesthetic drugs and delivery systems routinely achieve substantial differences in the incidences of prolonged extubations. Occasional claims made that anesthesia drugs have unimportant differences in recovery times, based on medians and means of extubation times, are misleading, because benefits of different anesthetics are achieved principally by reducing the variability in extubation times, specifically by decreasing the incidence of extubation times sufficiently long to have economic impact (ie, the prolonged extubations). Collectively, the results show that when investigators in anesthesia pharmacology quantify the rate of patient recovery from general anesthesia, the incidence of prolonged times to tracheal extubation should be included as a study end point.

Lack of Validity of Absolute Percentage Errors in Estimated Operating Room Case Durations as a Measure of Operating Room Performance: A Focused Narrative Review.

Commonly reported end points for operating room (OR) and surgical scheduling performance are the percentages of estimated OR times whose absolute values differ from the actual OR times by ≥15%, or by various intervals from ≥5 to ≥60 minutes. We show that these metrics are invalid assessments of OR performance. Specifically, from 19 relevant articles, multiple OR management decisions that would increase OR efficiency or productivity would also increase the absolute percentage error of the estimated case durations. Instead, OR managers should check the mean bias of estimated OR times (ie, systematic underestimation or overestimation), a valid and reliable metric.

Bibliometric Analysis of Contributions of Anesthesiology Journals and Anesthesiologists to Operating Room Management Science.

BACKGROUND: Anesthesiology journals appear to have been progressively publishing a smaller percentage of operating room (OR) management studies. Similarly, non-anesthesiologists have increasingly been authors of these publications. Five hypotheses were formulated to evaluate these impressions based on 2 of the authors' curation of an online, comprehensive bibliography of OR management articles and corresponding referenced course materials. METHODS: We studied all 2938 publications having Scopus' SciVal topic T.6319 (OR management) more than 28 years from 1996 through May 2023, including 8608 distinct authors. RESULTS: Half (50%) of the publications were absent from PubMed, and the percentage absent has been increasing progressively (Kendall's τ = 0.71; P < .0001). Fewer than half were published in journals including anesthesiology as the sole classification (20%) or as one of the classifications (27%). The anesthesiology journals have been publishing a progressively decreasing fraction (τ = -0.61; P < .0001). Among the 11 authors each contributing at least 1% of the OR management science publications, 9 were anesthesiologists and the other 2 had anesthesiologists as coauthors on all these publications. Only 3% of authors had at least 10 OR management publications from earlier years. There were 75% of authors with no such earlier publications and 85% with 0 or 1. There was a progressive increase in the number of authors publishing OR management annually and with at most 1 such earlier publication (τ = 0.90; P < .0001). Only 20% of publications had any author with at least 10 earlier OR management publications, 48% had every author with no such earlier publications, and 60% had all authors with 0 or 1. CONCLUSIONS: Although most of the authors with the greatest production of OR management science were anesthesiologists, the percentage of publications in anesthesiology journals has been decreasing progressively. Anesthesiologists cannot rely solely on anesthesiology journals to keep up with the field. For most publications, every author had few or no earlier publications on the topic. Clinicians and managers relying on OR management science will continue to need to apply more information when judging whether published results can reliably be applied to their facilities.

Introduction to Bayesian Analyses for Clinical Research.

Bayesian analyses are becoming more popular as a means of analyzing data, yet the Bayesian approach is novel to many members of the broad clinical audience. While Bayesian analyses are foundational to anesthesia pharmacokinetic/pharmacodynamic modeling, they also can be used for analyzing data from clinical trials or observational studies. The traditional null hypothesis significance testing (frequentist) approach uses only the data collected from the current study to make inferences. On the other hand, the Bayesian approach quantifies the external information or expert knowledge and combines the external information with the study data, then makes inference from this combined information. We introduce to the clinical and translational science researcher what it means to do Bayesian statistics, why a researcher would choose to perform their analyses using the Bayesian approach, when it would be advantageous to use a Bayesian instead of a frequentist approach, and how Bayesian analyses and interpretations differ from the more traditional frequentist methods. Throughout this paper, we use various pain- and anesthesia-related examples to highlight the ideas and statistical concepts that should be relatable to other areas of research as well.

Poor Concordance Between Intensive Care Unit Patients' and Family Members' Patient Dignity Inventory Scores Despite Communication of Dignity-Related Distress.

BACKGROUND: Promptly assessing and treating the distress of intensive care unit (ICU) patients may improve long-term psychological outcomes. One holistic approach to reduce patient distress is through dignity-centered care, traditionally used in palliative care. The 25-item Patient Dignity Inventory has construct validity and reliability for measuring dignity-related distress among ICU patients. Because family members often serve as ICU patients' surrogates and play an integral role in patients' dignity, we examined whether family members reliably recognized ICU patients' sources of distress. METHODS: Two single-center observational studies of adult ICU patients were performed from May to June 2022. Inclusion criteria were ICU length-of-stay >48 hours, awake and alert, intact cognition, and no delirium. Study #1 evaluated concordance between patient and family for dignity-related distress. Both completed the Patient Dignity Inventory independently. The next Study #2 measured how many distressing items that the patient reported discussing with family members. RESULTS: Study #1 of concordance had 33 patient-family dyads complete the Patient Dignity Inventory. The concordance correlation coefficient was small, 0.20 (99% confidence interval -0.21 to 0.55) and less than the inventory's test-retest reliability (r = .85). Study #2 examined sharing of Patient Dignity Inventory-related items between patients and family members. There were 12 of 19 patients who had severe distress based on an average Patient Dignity Inventory item score ≥1.92. The median patient shared multiple items of distress with their family (median 12, 99% 2-sided exact Hodges-Lehmann interval 4.0-17.5). CONCLUSIONS: Although ICU patients often report sharing sources of distress with their loved ones, family members cannot accurately or reliably assess the extent to which patients experience psychosocial, existential, and symptom-related distress during critical illness. Treatments of distress should not be delayed by the absence of family members.

Predictive Validity of Anesthesiologists' Quality of Clinical Supervision and Nurse Anesthetists' Work Habits Assessed by Their Associations With Operating Room Times.

BACKGROUND: At all Joint Commission-accredited hospitals, the anesthesia department chair must report quantitative assessments of anesthesiologists' and nurse anesthetists' (CRNAs') clinical performance at least annually. Most metrics lack evidence of usefulness, cost-effectiveness, reliability, or validity. Earlier studies showed that anesthesiologists' clinical supervision quality and CRNAs' work habits have content, convergent, discriminant, and construct validity. We evaluated predictive validity by testing for (expected) small but statistically significant associations between higher quality of supervision (work habits) and reduced probabilities of cases taking longer than estimated. METHODS: Supervision quality of each anesthesiologist was evaluated daily by assigned trainees using the 9-item de Oliveira Filho scale. The work habits of each CRNA were evaluated daily by assigned anesthesiologists using a 6-item scale. Both are scored binary, 1 if all items are rated the maximum, 0 otherwise. From 40,718 supervision evaluations and 53,722 work habit evaluations over 8 fiscal years, 16 mixed-effects logistic regression models were estimated, with raters as fixed effects and ratees (anesthesiologists or CRNAs) as random effects. Empirical Bayes means in the logit scale were obtained for 561 anesthesiologist-years and 605 CRNA-years. The binary-dependent variable was whether the case took longer than estimated from the historical mean time for combinations of scheduled procedures and surgeons. From 264,060 cases, 8 mixed-effects logistic regression models were fitted, 1 per fiscal year, using ratees as random effects. Predictive validity was tested by pairing the 8 one-year analyses of clinical supervision, and the 8 one-year analyses of work habits, by ratee, with the 8 one-year analyses of whether OR time was longer than estimated. Bivariate errors in variable linear least squares linear regressions minimized total variances. RESULTS: Among anesthesiologists, 8.2% (46/561) had below-average supervision quality, and 17.7% (99/561), above-average. Among CRNAs, 6.3% (38/605) had below-average work habits, and 10.9% (66/605) above-average. Increases in the logits of the quality of clinical supervision were associated with decreases in the logits of the probabilities of cases taking longer than estimated, unitless slope = -0.0361 (SE, 0.0053), P < .00001. Increases in the logits of CRNAs' work habits were associated with decreases in the logits of probabilities of cases taking longer than estimated, slope = -0.0238 (SE, 0.0054), P < .00001. CONCLUSIONS: Predictive validity was confirmed, providing further evidence for using supervision and work habits scales for ongoing professional practice evaluations. Specifically, OR times were briefer when anesthesiologists supervised residents more closely, and when CRNAs had better work habits.

A threshold of 100 or more colony-forming units on the anesthesia machine predicts bacterial pathogen detection: a retrospective laboratory-based analysis.

PURPOSE: Preventing the spread of pathogens in the anesthesia work area reduces surgical site infections. Improved cleaning reduces the percentage of anesthesia machine samples with ≥ 100 colony-forming units (CFU) per surface area sampled. Targeting a threshold of < 100 CFU when cleaning anesthesia machines may be associated with a lower prevalence of bacterial pathogens. We hypothesized that anesthesia work area reservoir samples returning < 100 CFU would have a low (< 5%) prevalence of pathogens. METHODS: In this retrospective cohort study of bacterial count data from nine hospitals, obtained between 2017 and 2022, anesthesia attending and assistants' hands, patient skin sites (nares, axilla, and groin), and anesthesia machine (adjustable pressure-limiting valve and agent dials) reservoirs were sampled at case start and at case end. The patient intravenous stopcock set was sampled at case end. The isolation of ≥ 1 CFU of Staphylococcus aureus, methicillin-resistant Staphylococcus aureus, Enterococcus, vancomycin-resistant Enterococcus, gram-negative (i.e., Klebsiella, Acinetobacter, Pseudomonas, and Enterobacter spp.) or coagulase-negative Staphylococcus was compared for reservoir samples returning ≥ 100 CFU vs those returning < 100 CFU. RESULTS: Bacterial pathogens were isolated from 24% (7,601/31,783) of reservoir samples, 93% (98/105) of operating rooms, and 83% (2,170/2,616) of cases. The ratio of total pathogen isolates to total CFU was < 0.0003%. Anesthesia machine reservoirs returned ≥ 100 CFU for 44% (2,262/5,150) of cases. Twenty-three percent of samples returning ≥ 100 CFU were positive for ≥ 1 bacterial pathogen (521/2,262; 99% lower confidence limit, 22%) vs 3% of samples returning < 100 CFU (96/2,888; 99% upper limit, 4%). CONCLUSIONS: Anesthesia machine reservoir samples returning < 100 CFU were associated with negligible pathogen detection. This threshold can be used for assessment of terminal, routine, and between-case cleaning of the anesthesia machine and equipment. Such feedback may be useful because the 44% prevalence of ≥ 100 CFU was comparable to the 46% (25/54) reported earlier from an unrelated hospital.

RéSUMé: OBJECTIF: La prévention de la propagation des agents pathogènes dans la zone de travail de l'anesthésie réduit les infections du site opératoire. L'amélioration du nettoyage réduit le pourcentage d'échantillons de l'appareil d'anesthésie présentant ≥ 100 unités de formation de colonie (UFC) par surface échantillonnée. Le fait de cibler un seuil < 100 UFC lors du nettoyage des appareils d'anesthésie pourrait être associé à une prévalence plus faible d'agents pathogènes bactériens. Nous avons émis l'hypothèse que les échantillons des réservoirs de la zone de travail d'anesthésie < 100 UFC résulteraient en une faible prévalence (< 5 %) d'agents pathogènes. MéTHODE: Dans cette étude de cohorte rétrospective des données de décompte bactérien de neuf hôpitaux, obtenues entre 2017 et 2022, les mains des anesthésiologistes et des assistant·es en anesthésie, les sites cutanés des patient·es (narines, aisselles et aines) et les réservoirs de l'appareil d'anesthésie (soupape de réglage de limitation de pression et cadrans d'agent) ont été échantillonnés au début et à la fin de chaque cas. Les échantillons sur l'ensemble de robinets d'arrêt intraveineux des patient·es ont été prélevés à la fin de chaque cas. L'isolement de ≥ 1 UFC de staphylocoque doré, de staphylocoque doré résistant à la méthicilline, d'entérocoque, d'entérocoque résistant à la vancomycine, de staphylocoque à Gram négatif (c.-à-d. Klebsiella, Acinetobacter, Pseudomonas et Enterobacter spp.) ou à coagulase négative a été comparé pour les échantillons de réservoir retournant ≥ 100 UFC vs ceux qui comportaient < 100 UFC. RéSULTATS: Des bactéries pathogènes ont été isolées dans 24 % (7601/31 783) des échantillons de réservoir, 93 % (98/105) des salles d'opération et 83 % (2170/2616) des cas. Le rapport entre le nombre total d'isolats d'agents pathogènes et le nombre total d'UFC était de < 0,0003 %. Les échantillons pris sur les réservoirs d'appareils d'anesthésie ont retourné ≥ 100 UFC dans 44 % (2262/5150) des cas. Vingt-trois pour cent des échantillons retournés ≥ 100 UFC étaient positifs pour ≥ 1 agent pathogène bactérien (521/2262; limite de confiance inférieure à 99 %, 22 %) vs 3 % des échantillons retournant < 100 UFC (96/2888 ; 99 % de la limite supérieure, 4 %). CONCLUSION: Les échantillons pris sur les réservoirs de l'appareil d'anesthésie comportant < 100 UFC étaient associés à une détection négligeable d'agents pathogènes. Ce seuil peut être utilisé pour l'évaluation du nettoyage final, de routine et entre les cas de l'appareil et de l'équipement d'anesthésie. Une telle rétroaction peut être utile parce que la prévalence de 44 % de ≥ 100 UFC était comparable aux 46 % (25/54) rapportés précédemment dans un autre hôpital.

Generalized Confidence Intervals for Ratios of Standard Deviations Based on Log-Normal Distribution when Times Follow Weibull Distributions.

Modern anesthetic drugs ensure the efficacy of general anesthesia. Goals include reducing variability in surgical, tracheal extubation, post-anesthesia care unit, or intraoperative response recovery times. Generalized confidence intervals based on the log-normal distribution compare variability between groups, specifically ratios of standard deviations. The alternative statistical approaches, performing robust variance comparison tests, give P-values, not point estimates nor confidence intervals for the ratios of the standard deviations. We performed Monte-Carlo simulations to learn what happens to confidence intervals for ratios of standard deviations of anesthesia-associated times when analyses are based on the log-normal, but the true distributions are Weibull. We used simulation conditions comparable to meta-analyses of most randomized trials in anesthesia, n ≈ 25 and coefficients of variation ≈ 0.30 . The estimates of the ratios of standard deviations were positively biased, but slightly, the ratios being 0.11% to 0.33% greater than nominal. In contrast, the 95% confidence intervals were very wide (i.e., > 95% of P ≥ 0.05). Although substantive inferentially, the differences in the confidence limits were small from a clinical or managerial perspective, with a maximum absolute difference in ratios of 0.016. Thus, P < 0.05 is reliable, but investigators should plan for Type II errors at greater than nominal rates.

Dignity-related distress and recall among alert, non-delirious critically ill patients.

OBJECTIVES: Critical illness is associated with multiple undesired impacts, including residual psychological distress, frequently associated with recollections of critical illness. Dignity-related distress is highly prevalent among the one-fifth of critically ill patients who are alert. The distress may be associated with unpleasant recollections of care. We examined whether patients at risk for dignity-related distress had recall of their reported distress approximately 1 week after assessment and whether this recall differed from another high-risk group, specifically patients undergoing dialysis for end-stage renal disease. METHODS: The prospective cohort study included patients with critical illness and patients with end-stage renal disease enrolled from intensive care units (ICUs) and dialysis units at 1 academic center. Distress was assessed using the Patient Dignity Inventory (PDI). Participants received in-patient or telephonic follow-up 7-10 days after the initial interaction. Follow-up encounters focused on recollection of key aspects of the interpersonal interaction as well as the content of the PDI. RESULTS: A total of 32 critically ill patients participated in initial assessment and follow-up. In total, 26 dialysis patients participated in both phases. The groups' demographics differed. Fifty percent (n = 16) of critically ill patients and 58% (n = 15) of dialysis patients reported a mean score per item of >1.6, corresponding with severe distress on the PDI. Among the ICU patients, the 95% upper 2-sided confidence interval for the median level of recall was commensurate with the participant having had no recall of the initial interview beyond remembering that there was an interview. The end-stage renal disease group did not demonstrate significantly better recall. SIGNIFICANCE OF RESULTS: Dignity-related distress is high in both critically ill patients and those with end-stage renal disease; however, recollection of assessment is poor in both groups. Any intervention designed to mitigate dignity-related distress will need either to be immediately deployable or not to be reliant upon recollection for impact.

Associations Between Fresh Gas Flow and Duration of Anesthetic on the Maximum Potential Benefit of Anesthetic Gas Capture in Operating Rooms and in Postanesthesia Care Units to Capture Waste Anesthetic Gas.

BACKGROUND: Sevoflurane and desflurane are halogenated hydrocarbons with global warming potential. We examined the maximum potential benefit assuming 100% efficiency of waste gas capture technology used in operating rooms and recovery locations. METHODS: We performed computer simulations of adult patients using the default settings of the Gas Man software program, including the desflurane vaporizer setting of 9% and the sevoflurane vaporizer setting of 3.7%. We performed 21 simulations with desflurane and 21 simulations with sevoflurane, the count of 21 = 1 simulation with 0-hour maintenance + (1, 2, 3, 4, or 5 hours of maintenance) × (0.5, 1, 2, or 4 L per minute fresh gas flow during maintenance). RESULTS: (1) A completely efficient gas capture system could recover a substantive amount of agent even when the case is managed with low flows. All simulations had at least 22 mL agent recovered per case, considerably greater than the 12 mL that we considered the minimum volume of economic and environmental importance. (2) All 42 simulations had at least 73% recovery of the total agent administered, considerably greater than the median 52% recovery measured during an experimental study with one gas capture technology and desflurane. (3) The maximum percentage desflurane (or sevoflurane) that could be captured decreased substantively with progressively longer duration anesthetics for low-flow anesthetics but not for higher-flow anesthetics. However, for all 8 combinations of drug and liters per minute simulated, there was a substantively greater recovery in milliliters of agent for longer duration anesthetics. In other words, if gas capture could be near perfectly efficient, it would have greater utility per case for longer duration anesthetics. (4) Even using a 100% efficient gas capture process, at most 6 mL liquid desflurane or 3 mL sevoflurane per case would be exhaled during the patient's stay in the postanesthesia care unit. Therefore, the volume of agent exhaled during the first 1 hour postoperatively is not a substantial amount from an environmental and economic perspective to warrant consideration of agent capture by having all these patients in the postanesthesia care unit, or equivalent locations, using the specialized anesthetic gas scavenging masks with access to the hospital scavenging system at each bed. CONCLUSIONS: Simulations with Gas Man show a strong rationale based on agent uptake and distribution for using volatile anesthetic agent capture in operating rooms if the technology can be highly efficient at volatile agent recovery.

Lack of Useful Predictors of Dignity-Related Distress Among the Critically Ill as Assessed With the Patient Dignity Inventory.

BACKGROUND: Many intensive care unit patients are awake (ie, alert and engaging in conversation), actively experiencing many facets of their critical care. The Patient Dignity Inventory can be used to elicit sources of distress in these patients. We examined the administrative question as to which awake intensive care unit patients should be evaluated and potentially treated (eg, through palliative care consultation) for distress. Should the decision to screen for distress be based on patient demographics or treatment conditions? METHODS: This was a retrospective cohort study of 155 adult patients from 5 intensive care units of one hospital from 2019 to 2020. Each patient had ≥48 hours without delirium, dementia, or sedation. The Patient Dignity Inventory has 25 items to which patients responded on a 1 (not a problem) to 5 (an overwhelming problem) scale. Multiple complete, stepwise forward, and stepwise backward logistic regression models were created among patient and treatment variables for predicting thresholds of the mean among the 25 items. RESULTS: There were 50% (78/155; 95% confidence interval [CI], 42-58) of patients with significant dignity-related distress (mean score ≥1.60). There were 34% (52/155; CI, 26-42) of patients with severe dignity-related distress (mean score ≥1.92; previously associated with often feeling like wanting to die). Models including combinations of vasopressor medication (protective of distress), tracheostomy (greater risk of distress), and female gender (greater risk of distress) had some predictive value. However, all combinations of potential predictors had misclassification rates significantly >20%. CONCLUSIONS: Identification of subsets of patients with little potential benefit to screening for dignity-related distress would have a reduced workload of palliative care team members (eg, nurses or social workers). Our results show that this is impractical. Given that approximately one-third of critical care patients who are alert and without delirium demonstrate severe dignity-related distress, all such patients with prolonged intensive care unit length of stay should probably be evaluated for distress.

Patients Undergoing Elective Inpatient Major Therapeutic Procedures in Florida Had No Significant Change in Hospital Mortality or Mortality-Related Comorbidities Between 2007 and 2019.

BACKGROUND: In a recent study, rapid response team implementation at 1 hospital was associated with only a 0.1% reduction in inpatient mortality from 2005 to 2018, characterized in the accompanying editorial as a "tepid" improvement. The editorialist postulated that an increase in the degree of illness of hospitalized patients might have masked a larger reduction that otherwise might have occurred. Impressions of greater patient acuity during the studied period might have been an artifact of efforts to document more comorbidities and complications, possibly facilitated by the change in diagnosis coding from the International Classification of Diseases , Ninth Revision ( ICD-9 ) to the Tenth Revision ( ICD-10 ). METHODS: We used inpatient data from every nonfederal hospital in Florida from the last quarter of 2007 through 2019. We studied hospitalizations for major therapeutic surgical procedures with lengths of stay ≥2 days. Using logistic regression with clustering by the Clinical Classification Software (CCS) code of the primary surgical procedure, we evaluated the trends for decreased mortality, changes in the prevalence of Medicare Severity Diagnosis Related Groups (MS-DRG) with complications or comorbidities (CC) or major complications or major comorbidities (MCC), and changes in the van Walraven index (vWI), a measure of patient comorbidities associated with increased inpatient mortality. Also incorporated in the modeling was the change from ICD-9 to ICD-10 . RESULTS: There were 3,151,107 hospitalizations comprising 130 distinct CCS codes and 453 MS-DRG groups among 213 hospitals. Despite a progressive increase of 4.1% per year in the odds of a CC or MCC ( P = .001), there were no significant changes in the marginal estimates of in-house mortality over time (net estimated decrease, 0.036%; 99% confidence interval [CI], -0.168% to 0.097%; P = .49). There was also absence of a significantly greater fraction of discharges with vWI >0 attributable to the year of the study (odds ratio, 1.017 per year; 99% CI, 0.995-1.041). The changes in MS-DRG to those with CC or MCC were not increased significantly from either the ICD-10 coding change or the number of years after the change. CONCLUSIONS: Consistent with the previous study, there was at most a small decrease in the mortality rate over a 12-year period. We found no reliable evidence that patients undergoing elective inpatient surgical procedures were any sicker in 2019 than in 2007. There were substantively more comorbidities and complications documented over time, but this was unrelated to the change to ICD-10 coding.

Most hospital patients at risk for bacterial infection undergo an anesthetic: implications for infection control practices related to the anesthesia workspace.

PURPOSE: Even with nearly 100% compliance with prophylactic antibiotic protocols, many surgical patients (> 5%) develop surgical site infections, some caused by pathogens transmitted from the anesthesia workspace (e.g., anesthesia machine), including multidrug-resistant Staphylococcus aureus. Reducing contamination of the anesthesia workspace substantively reduces the risk of surgical site infections. We estimated the percentage of hospital patients at risk for health care-associated infections who may benefit from the application of basic preventive measures under the control of anesthesia practitioners (e.g., their hand hygiene). METHODS: We conducted a retrospective cohort study which included every patient admitted to the University of Miami Health System from April 2021 through March 2022 for hospitalization, surgery, emergency department visits, or outpatient visits. Lists were created for the start date and times of every parenteral antibiotic administered and every anesthetic. RESULTS: Among 28,213 patient encounters including parenteral antibiotic(s), more than half (64.3%) also included an anesthetic (99% confidence interval, 62.2 to 66.6). The hypothesis that most antibiotics were administered during encounters when a patient underwent an anesthetic was accepted (P < 0.001). This observation may seem counterintuitive because parenteral antibiotics were administered for fewer than half of the 53,235 anesthetics (34.2%). The result was a consequence of most anesthetics (63.5%) at the health system being conducted in nonoperating room locations, and only 7.2% of such patients received a parenteral antibiotic. CONCLUSIONS: Because approximately two-thirds of patients who receive an intravenous antibiotic also undergo an anesthetic, greater use of effective infection control measures in the anesthesia operating room workspace has the potential to substantively reduce overall rates of hospital infections.

RéSUMé: OBJECTIF: Même avec un respect de près de 100 % des protocoles antibiotiques prophylactiques, bon nombre de patients et patientes en chirurgie (> 5 %) développent des infections du site opératoire, dont certaines sont causées par des agents pathogènes transmis par l'espace de travail anesthésique (p. ex. appareil d'anesthésie), y compris un staphylocoque doré multirésistant. La réduction de la contamination de l'espace de travail anesthésique réduit considérablement le risque d'infections du site opératoire. Nous avons estimé le pourcentage de patientes et patients hospitalisé·es à risque d'infections associées aux soins de santé qui pourraient bénéficier de l'application de mesures préventives de base sous le contrôle de praticiens et praticiennes d'anesthésie (par exemple, leur hygiène des mains). MéTHODE: Nous avons mené une étude de cohorte rétrospective qui comprenait toutes les personnes admises au Système de santé de l'Université de Miami d'avril 2021 à mars 2022 pour une hospitalisation, une intervention chirurgicale, des visites aux urgences ou des consultations externes. Des listes ont été créées pour la date et l'heure de début de chaque antibiotique parentéral administré et de chaque anesthésique. RéSULTATS: Parmi les 28 213 consultations avec les patient·es comprenant des antibiotiques parentéraux, plus de la moitié (64,3 %) comportaient également un anesthésique (intervalle de confiance à 99 %, 62,2 à 66,6). L'hypothèse selon laquelle la plupart des antibiotiques étaient administrés lors de rencontres lorsqu'une personne bénéficiait d'une anesthésie a été acceptée (P < 0,001). Cette observation peut sembler contre-intuitive, car des antibiotiques parentéraux ont été administrés pour moins de la moitié des 53 235 anesthésiques (34,2 %). En effet, la plupart des anesthésies (63,5 %) ont été administrées en dehors de la salle d'opération, et seulement 7,2 % de cette patientèle a reçu un antibiotique parentéral. CONCLUSION: Étant donné qu'environ les deux tiers des patientes et patients qui reçoivent un antibiotique par voie intraveineuse bénéficient également d'une anesthésie, une plus grande utilisation de mesures efficaces de contrôle des infections dans l'espace de travail anesthésique de la salle d'opération pourrait réduire considérablement les taux globaux d'infections hospitalières.

Interpretable machine learning models for hospital readmission prediction: a two-step extracted regression tree approach.

BACKGROUND: Advanced machine learning models have received wide attention in assisting medical decision making due to the greater accuracy they can achieve. However, their limited interpretability imposes barriers for practitioners to adopt them. Recent advancements in interpretable machine learning tools allow us to look inside the black box of advanced prediction methods to extract interpretable models while maintaining similar prediction accuracy, but few studies have investigated the specific hospital readmission prediction problem with this spirit. METHODS: Our goal is to develop a machine-learning (ML) algorithm that can predict 30- and 90- day hospital readmissions as accurately as black box algorithms while providing medically interpretable insights into readmission risk factors. Leveraging a state-of-art interpretable ML model, we use a two-step Extracted Regression Tree approach to achieve this goal. In the first step, we train a black box prediction algorithm. In the second step, we extract a regression tree from the output of the black box algorithm that allows direct interpretation of medically relevant risk factors. We use data from a large teaching hospital in Asia to learn the ML model and verify our two-step approach. RESULTS: The two-step method can obtain similar prediction performance as the best black box model, such as Neural Networks, measured by three metrics: accuracy, the Area Under the Curve (AUC) and the Area Under the Precision-Recall Curve (AUPRC), while maintaining interpretability. Further, to examine whether the prediction results match the known medical insights (i.e., the model is truly interpretable and produces reasonable results), we show that key readmission risk factors extracted by the two-step approach are consistent with those found in the medical literature. CONCLUSIONS: The proposed two-step approach yields meaningful prediction results that are both accurate and interpretable. This study suggests a viable means to improve the trust of machine learning based models in clinical practice for predicting readmissions through the two-step approach.

Exceedance Probabilities of Log-normal Distributions for One Group, Two Groups, and Meta-analysis of Multiple Two-group Studies, With Application to Analyses of Prolonged Times to Tracheal Extubation.

Many randomized trials measure means and standard deviations of anesthesia recovery time (e.g., times to tracheal extubation). We show how to use generalized pivotal methods to compare the probabilities of exceeding a tolerance limit (e.g., > 15 min, prolonged times to tracheal extubation). The topic is important because the economic benefits of faster anesthesia emergence depend on reducing variability, not means, especially prevention of very long recovery times. Generalized pivotal methods are applied using computer simulation (e.g., using two Excel formulas for one group and three formulas for two group comparisons). The endpoint for each study with two groups is the ratio between groups of the probabilities of times exceeding a threshold or the ratio of the standard deviations. Confidence intervals and variances for the incremental risk ratio of the exceedance probabilities and for ratios of standard deviations are calculated using studies' sample sizes, sample means in the time scale of recovery times, and sample standard deviations in the time scale. Ratios are combined among studies using the DerSimonian-Laird estimate of the heterogeneity variance estimate, with Knapp-Hartung adjustment for the relatively small (N = 15) numbers of studies in the meta-analysis. We show larger absolute variability among studies' results when analyzed based on exceedance probabilities rather than standard deviations. Therefore, if an investigator's primary goal is to quantify reductions in the variability of recovery times (e.g., times until patients are ready for post-anesthesia care unit discharge), we recommend analyzing the standard deviations. When exceedance probabilities themselves are relevant, they can be analyzed from the original studies' summary measures.

Managing capacity for urgent surgery: staffing, staff scheduling in-house or on-call from home, and work assignments.

Parmar and colleagues developed and validated a graphical method for choosing the number of operating theatres to set aside for urgent surgical cases. We address appropriate usage of their new method for calculating anaesthesia staffing, including comparison with previously published techniques. Parmar and colleagues' method is based on all staff scheduled in-house, rather than some on-call from home. We review that this is not nearly as large a limitation as it may seem because of behavioural factors of staff assignment.

Case duration prediction and estimating time remaining in ongoing cases.

In this issue of the British Journal of Anaesthesia, Jiao and colleagues applied a neural network model for surgical case durations to predict the operating room times remaining for ongoing anaesthetics. We review estimation of case durations before each case starts, showing why their scientific focus is useful. We also describe managerial epidemiology studies of historical data by the scheduled procedure or distinct combinations of scheduled procedures included in each surgical case. Most cases have few or no historical data for the scheduled procedures. Generalizability of observational results such as theirs, and automatic computer assisted clinical and managerial decision-making, are both facilitated by using structured vocabularies when analysing surgical procedures.

Relationship Between Glottic View and Intubation Force During Macintosh and Airtraq Laryngoscopy and Intubation.

BACKGROUND: Because intubation-mediated cervical spine and spinal cord injury are likely determined by intubation force magnitude, understanding the determinants of intubation force magnitude is clinically relevant. With direct (Macintosh) laryngoscopy, when glottic view is less favorable, anesthesiologists apply greater force. We hypothesized that, when compared with direct (Macintosh) laryngoscopy, intubation force with an optical indirect laryngoscope (Airtraq) would be less dependent on glottic visualization. METHODS: Using data obtained in a prior clinical study, we tested whether the slope of the intubation force versus glottic view relationship differed between intubations performed in 14 patients who were intubated twice, once with a Macintosh and once with an Airtraq videolaryngoscope. Slopes were compared using least-squares linear regression and robust regression. RESULTS: The slope of the intubation force (N) versus glottic view (%) relationship with the Macintosh (-0.679 [standard error {SE}, 0.147]) was significantly more negative than that of the Airtraq (-0.076 [SE, 0.246]). The least-squares regression difference in slopes was -0.603 (SE, 0.287); P = .046. The robust regression difference in slopes was -0.747 (SE, 0.187); P = .0005. Thus, when compared with the Macintosh, intubation force magnitude with Airtraq laryngoscopy was less dependent on glottic visualization. CONCLUSIONS: Previously, we reported that intubation force with the Airtraq was less in magnitude compared with the Macintosh. Our current study adds that intubation force also is less dependent on glottic view with Airtraq compared with the Macintosh.

Epidemiology of Enterococcus , Staphylococcus aureus , Klebsiella , Acinetobacter , Pseudomonas , and Enterobacter Species Transmission in the Pediatric Anesthesia Work Area Environment With and Without Practitioner Use of a Personalized Body-Worn Alcohol Dispenser.

BACKGROUND: Personalized body-worn alcohol dispensers may serve as an important tool for perioperative infection control, but the impact of these devices on the epidemiology of transmission of high-risk Enterococcus , Staphylococcus aureus , Klebsiella, Acinetobacter , Pseudomonas , and Enterobacter (ESKAPE) pathogens is unknown. We aimed to characterize the epidemiology of ESKAPE transmission in the pediatric anesthesia work area environment with and without a personalized body-worn alcohol dispenser. METHODS: This controlled before and after study included 40 pediatric patients enrolled over a 1-year study period. Two groups of operating room cases were compared: (1) operating room cases caring for patients with usual care (December 17, 2019, to August 25, 2020), and (2) operating room cases caring for patients with usual care plus the addition of a personalized, body-worn alcohol hand rub dispenser (September 30, 2020, to December 16, 2020). Operating rooms were randomly selected for observation of ESKAPE transmission in both groups. Device use was tracked via wireless technology and recorded in hourly hand decontamination events. RESULTS: Anesthesia providers used the alcohol dispenser 3.3 ± 2.1 times per hour. A total of 57 ESKAPE transmission events (29 treatment and 28 control) were identified. The personalized body-worn alcohol dispenser impacted ESKAPE transmission by increasing the contribution of provider hand contamination at case start (21/29 device versus 10/28 usual care; relative risk, [RR] 2.03; 99.17% confidence interval [CI], 1.025-5.27; P = .0066) and decreasing the contribution of environmental contamination at case end (3/29 device versus 12/28 usual care; RR, 0.24; 99.17% CI, 0.022-0.947; P = .0059). ESKAPE pathogen contamination involved 20% (8/40) of patient intravascular devices. There were 85% (34/40) of preoperative patient skin surfaces contaminated with ≥1 (1.78 ± 0.19 [standard deviation {SD}]) ESKAPE pathogens. CONCLUSIONS: A personalized body-worn alcohol dispenser can impact the epidemiology of ESKAPE transmission in the pediatric anesthesia work area environment. Improved preoperative patient decolonization and vascular care are indicated to address ESKAPE pathogens among pediatric anesthesia work area reservoirs.

More surgery in December among US patients with commercial insurance is offset by unrelated but lesser surgery among patients with Medicare insurance.

STUDY OBJECTIVE: Evaluate whether there is more surgery (in the US State of Florida) at the end of the year, specifically among patients with commercial insurance. DESIGN: Observational cohort study. SETTING: The 712 facilities in Florida that performed inpatient or outpatient elective surgery from January 2010 through December 2019. RESULTS: Among patients with commercial insurance, December had more cases than November (1.108 [1.092-1.125]) or January (1.257 [1.229-1.286]). In contrast, among patients with Medicare insurance (traditional or managed care), December had fewer cases than November (ratio 0.917 [99% confidence interval 0.904-0.930]) or January (0.823 [0.807-0.839]) of the same year. Summing among all cases, December did not have more cases than November (ratio 1.003 [0.992-1.014]) or January (0.998 [0.984-1.013]). Comparing December versus November (January) ratios for cases among patients with commercial insurance to the corresponding ratios for cases among patients with Medicare, years with more commercial insurance cases had more Medicare cases (Spearman rank correlation +0.36 [+0.25], both p < 0.0001). CONCLUSIONS: In the US State of Florida, although some surgeons' procedural workloads may have seasonal variation if they care mostly for patients with one category of insurance, surgical facilities with patients undergoing many procedures will have less variability. Importantly, more commercial insurance cases were not causing Medicare cases to be postponed or vice-versa, providing mechanistic explanation for why forecasts of surgical demand can reasonably be treated as the sum of the independent workloads among many surgeons.