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Record W2126121801 · doi:10.15537/1658-3175.3876

Apnea after reversal of neuromuscular blockade. A case of rare mix-up

2007· article· en· W2126121801 on OpenAlexaboutno aff
Mohammad Ansari, Govardhan K Magaji, Annamma Abraham

Bibliographic record

VenueSaudi Medical Journal · 2007
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAdverse effectLaryngospasmAnesthesiaNear missDiscontinuationConfusionNeuromuscular BlockadeApneaIncidence (geometry)Inguinal herniaMalpracticeIntensive care medicinePediatricsSurgeryHerniaAirwayInternal medicine

Abstract

fetched live from OpenAlex

M error is one of the leading causes of morbidity and mortality in hospitalized patients.1 Considering the potency, types, and frequency of the drugs administered to patients undergoing anesthesia, the potential exists for errors with disastrous consequences.2 Several studies indicate that the incidence of medication error associated with anesthesia practice is common. Analysis of critical incidences by Cooper and colleagues3 showed that drug-related events far exceeded the next most common problem, disconnection of the breathing circuit. The Australian Incident Monitoring Study analyzed adverse events during anesthesia and reported that “The wrong drug” was the most common adverse event.4 Indeed, anesthetic drug errors have been reported for every aspect of anesthetic–related care, most common being the “Syringe swaps” (70.4%) and misidentification of the label (46.8%).5 An analysis of closed malpractice claims showed that medication issues are a leading cause of malpractice litigation against Canadian anesthesiologists, totalling 3.5% of claims against all physicians from 1998 to 2002. The most common cause of malpractice action was a medicationrelated event.6 Berman7 reported that errors due to lookalike or sound-alike medication names are common in the United States. Up to 25% of all medication errors are attributed to name confusion, and 33% to packaging or labeling confusion. Systems and recommendations have been developed that may reduce the occurrence of such errors. In our case, an ASA I, male child of 4 years of age and 15 kg body weight was posted for repair of left inguinal hernia under general anesthesia. His routine complete blood count, and biochemistry including urine analysis were within normal limits. The child was premedicated with 5 ml promethazine hydrochloride oral syrup 1 hour before induction of anesthesia. In the operating room, before initiation of anesthesia, his vitals were recorded, his heart rate was 110/minute with normal sinus rhythm, his blood pressure was 106/70 mm Hg and arterial saturation was 99%. An intra-venous cannulation was performed with 22 G cannula without any difficulty and 5% dextrose with one-quarter normal saline started. Anesthesia was induced with 60 mg thiopentone sodium and relaxed with 20 mg suxamethonium, and tracheal intubation was performed with 4.5 mm uncuffed endotracheal tube. Anesthesia was maintained with 25 μgm fentanyl, 50% oxygen with nitrous oxide, 0.6-0.8% sevoflurane and atracurium besylate 0.5 mg/kg as, and when required. Ayre’s T Piece circuit was used for intermittent positive pressure ventilation. Surgery lasted for 45 minutes, and the whole course of anesthesia was uneventful. At the end of surgery, he gained spontaneous respiration, and was kept on 100% oxygen only. Neuromuscular blockade was reversed with 0.75 mg neostigmine and 0.2 mg atropine. After reversal, the heart rate came down from 102/minute to 55/minute and he gradually developed apnea. Heart rate was corrected with the use of atropine. The cause of this fall in heart rate and apnea could not be detected. This unexpected result of reversal alerted us to consider a medication error. A careful check of the syringes loaded with drugs revealed atracurium besylate mixed with neostigmine methyl sulphate instead of atropine. Two syringes kept sideby-side one loaded with atracurium besylate, 5 mg/ml and marked “Atra” and the other syringe loaded with atropine sulphate, 0.1 mg/ml marked “Atro”. In this case, 0.75 mg of neostigmine was mixed with 10 mg of atracurium besylate instead of 0.2 mg of atropine sulphate. The manner in which labeling of the syringes was carried out, could have happened with anyone involved in the anesthetic care of the patient. In this patient, this “mix-up” did not cause any undesirable side effect except prolong apnea and bradycardia, which were taken care of appropriately. Later, when the effect of the muscle relaxant wore off, an appropriate dose of reversal was used and tracheal extubation carried out. He was observed for one hour in recovery and then shifted to the ward without any problem. Though this medication error did not cause any deleterious effect on the patient’s health, it definitely indicates the need for improved standards for drug labeling. To conclude, the utmost care is essential while giving drugs during anesthesia care. To improve patient safety, each medical and surgical discipline needs to identify the sources of error and develop evidence based preventative strategies. The incidence of medication error during anesthesia is uncertain, but it is astonishingly low given the millions of drugs administered during anesthesia care.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.367
Teacher spread0.334 · 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 designCase report
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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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