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Record W2015390794 · doi:10.1097/aln.0b013e318267ef54

Nausea and Vomiting Treatment after Surgery

2012· letter· en· W2015390794 on OpenAlexaff
J. Lance Lichtor, Frances Chung

Bibliographic record

VenueAnesthesiology · 2012
Typeletter
Languageen
FieldMedicine
TopicNausea and vomiting management
Canadian institutionsToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineNauseaVomitingPostoperative nausea and vomitingGeneral surgeryAnesthesia

Abstract

fetched live from OpenAlex

This Editorial View accompanies the following article: Apfel CC, Philip BK, Cakmakkaya OS, Shilling A, Shi Y-Y, Leslie JB, Allard M, Turan A, Windle P, Odom-Forren J, Hooper VD, Radke OC, Ruiz J, Kovac A: Who is at risk for postdischarge nausea and vomiting after ambulatory surgery? ANESTHESIOLOGY 2012; 117:475–86.POSTOPERATIVE nausea and vomiting was introduced as a MeSH heading in 1999, though in 1946, in this very journal, an article on the topic already appeared.1Initially the topic was thought of as a problem seen within 24 h after surgery. Postdischarge nausea and vomiting (PDNV) is defined as a problem that occurs after a patient has left the hospital. Some who do not have postoperative nausea and/or vomiting (PONV) while in the hospital might still experience PDNV once they are home. In the current issue, in a report published by Apfel et al. , a prediction model for determining who might experience PONV and PDNV after surgery in an ambulatory surgery center was developed.2Patient-specific risk factors were similar for both PONV and PDNV: women, individuals whose age was less than 50 yr, and patients with a history of PONV were more likely to develop PONV or PDNV. Nonsmoking status did not independently predict who might develop PDNV.“Up to 50% of patients have nausea and vomiting after they leave the ambulatory surgery center.”Although the concept of PDNV has been studied for at least 15 yr, to many it is not apparent how pervasive the problem is. Indeed, once a patient leaves the ambulatory surgery center, our direct contact with the patient is minimal. Up to 50% of patients have nausea and vomiting after they leave the ambulatory surgery center.3Resumption of normal activities does not occur until this problem has been resolved.4In medicine, we love to make and use scores. The Apgar, Aldrete, and APACHE scores come first to mind, though there are many others. Scores are useful, in part, because they allow information to be quickly transmitted. It is easier to say that an infant has an Apgar score of 3 than telling the listener that the infant's heart rate is less than 100, respirations are weak, there is some flexion, and the infant has no response to stimulation and is blue. If we heard the number 3, we would probably jump to action more quickly than if we had to listen to the entire list. Yet until now a score to predict who has PDNV has not been devised. Therefore, this newly developed score on PDNV will be very useful. With the exception of the nonsmoking status, it is interesting, though not surprising, that the basis for this score is not that different from the score used for PONV. From previous studies we know that the type of general anesthesia can affect PONV.5What is not clear is whether type of general anesthesia can also affect PDNV.When propofol is used instead of an inhalation agent and nitrous oxide is not used, the risk in PONV reduction is similar to that seen after treatment with a single antiemetic.5It is easy and convenient to conduct anesthesia with a vaporizer – all that is required is to turn the dial, although it is important to make sure that the vaporizer is filled. Propofol is now a generic drug and is not that much more expensive than an inhalation agent. In one study of patients undergoing outpatient gynecologic laparoscopy, patients who received total intravenous anesthesia, no paralysis, as well as ondansetron, droperidol, and dexamethasone, had no retching or vomiting in the postanesthesia recovery unit, although 5% had nausea in the postanesthesia recovery unit and 12% had vomiting after discharge.6In another study of patients undergoing elective gynecologic laparoscopy, although a nitrous oxide–isoflurane anesthetic was less expensive than a propofol–air–oxygen anesthetic, the cost difference was trivial, and more patients who received isoflurane were nauseous.7The same could be said about all inhalation agents, and most others are more expensive than isoflurane.Some claim that a propofol-based anesthetic is more popular outside the United States because of the availability of target-controlled infusions. If the bispectral index monitor is used, anesthesia depth and hemodynamic stability are not different compared with target-controlled infusions.8Admittedly, fewer interventions may be required when target-controlled infusions are used.9Certainly, a propofol-based anesthetic has other advantages: the incidence of emergence delirium is lower, there is less exposure to atmospheric pollutants, the environmental footprint is lower, and coughing and laryngospasm occur less commonly. If we care about our patient's PONV after the procedure, a total intravenous anesthesia technique should be employed much more. In the current study of patients who underwent surgery in ambulatory surgery facilities, all received an inhalation agent. It is unclear how different the PDNV score would have been if propofol was used for anesthesia maintenance instead of an inhalation agent. Would PDNV be less if propofol was used?PONV and PDNV are related to prophylactic antiemetic treatment. Should everyone get prophylactic treatment, or should the decision for prophylactic treatment be reserved for those with factors associated with greater postoperative PDNV, as identified by Apfel et al. ?2Certainly many patients with PDNV may not manifest any PONV in the postanesthesia recovery unit.4Furthermore, some patients may have a genetic predilection. In a study that examined the relationship of patient genome to PONV, at least one single nucleotide polymorphism was shown to predict who is susceptible.10Whether prior knowledge of patient genome would have trumped overt patient characteristics identified in this or other similar prediction models is unclear.Using a multimodal clinical care algorithm consisting of a total intravenous anesthetic (propofol and remifentanil), no nitrous oxide, no neuromuscular blockade, hydration, triple prophylactic antiemetics (ondansetron, droperidol, and dexamethasone), and ketorolac, Scuderi et al. found that 98% of patients studied did not vomit or retch while in the postanesthesia recovery unit.6In those patients described by Scuderi et al. who underwent laparoscopic gyneocologic procedures, only 2% of patients had nausea, and no patient suffered from vomiting. Why do anesthesiologists not implement multimodal therapies, preventing and treating PONV and PDNV as vigorously as preventing and treating pain? What is the hurdle?It is hoped that articles such as this will stimulate debate concerning how to aggressively prevent the nausea and vomiting that patients may experience after surgery. If we are aggressive about using a nonemetogenic anesthetic, and base therapy on Apfel's PONV and PDNV scores, will the model be the same? Will newer drugs be more effective and have longer-term effects than what we currently have available? As anesthesiologists, although we can't do much about the surgery, we can control the anesthetic as well as treatment modalities. This is a call for action: Let's decrease the incidence of PONV and PDNV.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.513
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.263
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations8
Published2012
Admission routes1
Has abstractyes

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