The stakes could hardly be higher. Cesarean delivery now accounts for roughly 21 percent of births worldwide, a figure projected to climb toward 30 percent by 2030. Poorly managed postoperative pain is not merely a comfort issue; it delays recovery, interferes with newborn care, raises the risk of thromboembolism, and substantially increases rates of chronic postpartum pain and depression. Yet the cesarean population is fundamentally different from the general surgical populations in which the TAP block first proved itself. Most cesarean patients receive neuraxial anesthesia, typically spinal anesthesia, before the incision is made, and that pre-existing analgesic coverage changes the equation in ways that findings from other surgical settings cannot capture. The new review, registered prospectively in PROSPERO and conducted according to PRISMA 2020 guidelines, set out to quantify the block’s effect on postoperative opioid consumption and to determine which clinical variables drive the variability that has plagued the literature.

The researchers systematically searched PubMed, Embase, and the Cochrane Central Register of Controlled Trials from database inception through March 2024, with no language restrictions. Eligible studies enrolled adult patients undergoing cesarean delivery and compared TAP block, performed by any approach and with any local anesthetic formulation, against placebo, no block, or an active comparator such as wound infiltration or quadratus lumborum block. The primary outcome was total opioid consumption within the first 24 hours after surgery, harmonized across different opioid agents using morphine milligram equivalents where necessary. Secondary outcomes included pain scores at rest and on movement at 2, 6, 12, and 24 hours, time to first analgesic request, postoperative nausea and vomiting, adverse effects, patient satisfaction, and quality of recovery. Eighteen studies spanning 2008 to 2024 and enrolling approximately 1,824 patients across four continents made the cut, fourteen of them randomized controlled trials.

Here is where the story takes a statistically dramatic turn. Only four of the eighteen studies provided sufficiently homogeneous numerical data for quantitative pooling, covering just 193 patients. When those four were combined using random-effects modelling with Hedges’ g correction, the pooled estimate showed a statistically significant reduction in 24-hour opioid consumption favoring TAP block, with a standardized mean difference of minus 2.30 and a 95 percent confidence interval of minus 4.24 to minus 0.36, yielding a p-value of 0.02. But the heterogeneity statistic, I-squared, came in at an extraordinary 97 percent, meaning the studies disagreed with each other to a degree that renders any single summary number unreliable. The authors are refreshingly candid about this: the pooled figure, they write, is better understood as a rough average across very different clinical contexts than as a precise summary estimate. The variation itself, they argue, is the more informative result, and it maps directly onto two clinical variables that were pre-specified as subgroup analyses before any data extraction began: the type of anesthesia used and whether intrathecal morphine was part of the regimen.

The general anesthesia subgroup provides the most consistent evidence for TAP block benefit. With no neuraxial analgesia in place, the block addresses anterior abdominal wall somatic pain without competition, and all four studies conducted under general anesthesia reported clinically meaningful opioid-sparing. The numbers are striking. McDonnell and colleagues found cumulative morphine use of 6 milligrams versus 33 milligrams over the first 12 hours, with the median time to first opioid request extended from 90 to 220 minutes. Eslamian’s team reported tramadol requirements reduced from 250 to 75 milligrams and time to first rescue analgesia delayed by more than three hours. Buluc observed that not a single TAP patient required supplemental analgesia beyond the patient-controlled analgesia protocol, compared with 11 of 15 controls. And Tao, in a propensity-matched retrospective cohort, documented a 10-point improvement in the Quality of Recovery-15 scale at 24 hours, exceeding the instrument’s minimum clinically important difference, along with shorter time to ambulation and earlier return of intestinal function. General anesthesia accounts for roughly 5 to 15 percent of cesarean deliveries at many institutions, and considerably more where preservative-free morphine is unavailable or urgent fetal compromise precludes neuraxial placement, making this subgroup far from a niche concern.

The picture reverses when intrathecal morphine enters the equation. Intrathecal morphine remains the reference standard for post-cesarean pain control, providing sustained spinal-level analgesia covering both somatic and visceral components for 12 to 24 hours, though it comes with well-known drawbacks including pruritus, nausea, urinary retention, and the rare but serious risk of delayed respiratory depression. Across the three dedicated studies that examined TAP block as an add-on to intrathecal morphine-based spinal anesthesia, the incremental contribution of the block was negligible. The pooled estimate in this subgroup was a near-zero standardized mean difference of 0.12 with a confidence interval spanning minus 0.34 to 0.58 and a p-value of 0.61. Lee and colleagues saw a real early advantage at 2 hours, with movement pain scores of 1.9 versus 4.9, but it had disappeared entirely by 24 hours. McKeen found no improvement at any time point in 74 patients receiving intrathecal morphine doses of 0.1 to 0.2 milligrams. Singh, comparing high and low doses of ropivacaine against an intrathecal morphine background, found no difference in the primary endpoint at 24 hours. The pharmacology explains it: once intrathecal morphine generates durable opioid receptor-mediated analgesia, a peripheral fascial plane block has very little additional pain left to address.

Spinal anesthesia without intrathecal morphine, whether because morphine is unavailable, opioids are contraindicated, or the institution follows an opioid-minimization protocol, is the other scenario where TAP block reliably contributes. Six of the eight studies in this subgroup showed statistically significant benefit, with magnitudes varying by background analgesic regimen. Jadon’s results were among the most dramatic: the median time to first analgesic request extended from 4 to 11 hours, and median tramadol use dropped from 2 doses to zero. Srivastava recorded a 50 percent reduction in tramadol over 48 hours, and Mankikar more than doubled the rescue-free window from 4.1 to 9.5 hours. Fusco added an important technical observation: when the block was performed correctly under direct ultrasound visualization, far fewer patients crossed the pain threshold of a visual analog scale score of 4 or higher, underscoring that technique quality matters. The two exceptions are instructive rather than contradictory. Yu tested the block against a rigorous scheduled oral regimen of tramadol, celecoxib, and paracetamol with on-demand oxycodone and found it added nothing, demonstrating what structured multimodal analgesia can achieve on its own. Sripriya found that neither posterior TAP nor transversalis fascia plane block reduced total rescue analgesic doses, yet TAP meaningfully extended the pain-free interval from 4.76 to 6.89 hours.

The active comparator data yield two practical conclusions. TAP block and wound infiltration perform essentially the same when local anesthetic volume and concentration are matched, suggesting that delivery route matters less than the total local anesthetic deposited in the abdominal wall, a finding with real implications when operating room time is short. The quadratus lumborum block appears modestly superior at select time points, plausibly because its posterior spread can reach the paravertebral space and capture visceral afferents that TAP cannot, though that advantage is small and the technique is more demanding. Notably, no trial has yet compared the two techniques in an intrathecal morphine-inclusive setting. Even the extended-duration story is underwhelming: Peebles examined liposomal bupivacaine TAP block against liposomal bupivacaine wound infiltration in a retrospective cohort of 402 patients and found both active arms indistinguishable from each other, with the extended-duration agent not changing which technique came out ahead. Secondary outcomes tracked the primary signal: pain benefit typically attenuated or disappeared by 24 hours, in keeping with the 8 to 16 hour functional duration of conventional bupivacaine and ropivacaine, and reduced nausea and vomiting rates in the general anesthesia subgroup reflected predictable downstream effects of lower systemic opioid exposure. One serious adverse event occurred across the entire dataset, a case of systemic local anesthetic toxicity with convulsions that resolved with intravenous midazolam and left no long-term sequelae.

The authors are careful to frame their conclusions as context-dependent and hypothesis-generating rather than definitive clinical prescriptions. The quantitative evidence rests on only four pooled studies, the two observational cohorts carry the usual risk of unmeasured confounding, background analgesic regimens varied widely, and nearly every study reported only short-term outcomes, with Singh’s 6- and 12-week data the lone exception showing no difference at either time point. Still, the clinical message is neither to abandon the block broadly nor to apply it universally, but to use it where the evidence is strongest. Under general anesthesia, TAP block should be strongly considered as a component of postoperative analgesia. When intrathecal morphine is part of the spinal technique, the available evidence does not support routine use, and resources are better directed toward dose optimization and side-effect management. In patients receiving spinal anesthesia without intrathecal morphine, the block appears to provide clinically meaningful analgesia, with the caveat that benefit is attenuated when structured oral analgesia is already reliably implemented. Future trials, the authors argue, should adopt standardized outcome reporting anchored to the IMMPACT core set, mandate intrathecal morphine use as a pre-specified stratification variable, and finally test continuous catheter-based TAP infusion over single-shot blocks in the general anesthesia setting, where the block’s contribution is clearest and duration matters most. Confirmation in adequately powered prospective trials is required before this framework can serve as the basis for formal clinical guidance, but for now, the era of one-size-fits-all TAP blocking after cesarean delivery may be drawing to a close.

Subject of Research: Medicine

Article Title: Is transversus abdominis plane block universally effective after cesarean delivery? A systematic review and meta-analysis

Article References: Riveros-Perez, E., & Avella-Molano, B. (2026). Is transversus abdominis plane block universally effective after cesarean delivery? A systematic review and meta-analysis. Frontiers in Anesthesiology, 5, Article 1861059. https://doi.org/10.3389/fanes.2026.1861059

Image Credits: AI Generated

DOI: 10.3389/fanes.2026.1861059

Keywords: TAP block, cesarean delivery, intrathecal morphine, meta-analysis, regional anesthesia, postoperative pain, opioid-sparing, obstetric anesthesia, transversus, abdominis, plane, block

Researchers at Weill Cornell Medicine searched PubMed and Embase for studies published between January 2015 and December 2025, combining clinical terms for obstetric anesthesia and delivery with methodological terms for artificial intelligence and machine learning. From 3,135 records identified, two reviewers with consensus adjudication by board-certified anesthesiologists narrowed the field to 172 studies that met inclusion criteria: 154 original research studies, 17 systematic or narrative reviews, and a single case report. Twelve additional records, including nine registered clinical trials and three workforce-focused studies, were analyzed separately. The timing tells its own story. Roughly 69 percent of the included publications appeared after 2022, and more than half were published in 2024 or 2025 alone, a pace that mirrors the public release of large language models and the broader AI boom in medicine.

The geographic spread was equally revealing. The United States contributed 40 studies and China 35, followed by Israel, Italy, India, Singapore, and Spain, with eighteen multinational collaborations rounding out the picture. When the researchers classified the studies by machine learning approach, classification tasks dominated, followed by regression, neural networks, and large language models. Unsupervised learning, reinforcement learning, and dedicated radiomics pipelines appeared only rarely. The work clustered into distinct domains: maternal risk and complications prediction led with 61 studies, delivery mode prediction followed with 43, patient education and conversational AI claimed 15, fetal heart rate tracing analysis 12, imaging and radiomics 8, and provider education and simulation just 2.

The single largest domain, maternal risk and complications prediction, targets some of the most feared events in obstetrics. Postpartum hemorrhage accounts for 11 percent of U.S. maternal mortality and remains a leading preventable cause of maternal death, making accurate risk assessment a matter of life and death. Machine learning models predicting hemorrhage and transfusion have reported widely varying performance, with areas under the curve ranging from 0.67 to 0.99. Large language models have even been used to extract risk factors from prenatal notes and electronic health records, identifying features like multiple gestation and prior cesarean delivery. But the review uncovered a sobering technical problem: differing hemorrhage definitions across health systems can dramatically degrade model performance. One model’s C-statistic fell from 0.93 to 0.57 when applied to a contemporary cohort rather than an early-2000s cohort, a collapse that underscores how fragile these tools can be outside their training environment.

Placenta accreta spectrum, a life-threatening condition in which the placenta invades the uterine wall, illustrates both the power and the limits of current approaches. Although its prevalence is low at roughly 0.17 percent, it drives severe peripartum morbidity, with pooled incidences of 52.2 percent for hysterectomy and 46.9 percent for transfusion among affected women. Deep learning and MRI-based radiomics have shown genuine promise for earlier recognition, with one 2025 study using 15 radiomic features reaching an area under the curve of 0.95 for predicting the condition. Yet the same study found that random forest and k-nearest neighbor models using identical variables achieved AUCs of only 0.704 to 0.863, a reminder that algorithm choice matters enormously and that headline numbers can mask substantial intra-study variation.

Hypertensive disorders of pregnancy represent another major target. Pre-eclampsia affects 555 per 10,000 deliveries, and hypertensive disorders account for 6.8 percent of pregnancy-related deaths. A 2024 pilot study used routine biomarkers and clinical characteristics to predict severe pre-eclampsia requiring intensive care, achieving an AUC of 0.91 with an XGBoost model in an 81-patient cohort. Aspartate aminotransferase, uric acid, and body mass index emerged as the strongest indicators of severe disease. Meanwhile, peripartum cardiomyopathy, which complicates roughly 1 in 2,000 pregnancies worldwide and carries 76-fold higher odds of cardiogenic shock, has become the focus of one of the field’s most compelling real-world tests: a recent trial found that an AI-guided digital stethoscope doubled the diagnosis of pregnancy-related cardiomyopathy compared with usual care, with a number needed to screen of 47 to identify one new case of perinatal left ventricular systolic dysfunction.

Beyond risk prediction, AI is being applied to the mechanics of birth itself. Approximately 30 percent of the reviewed articles addressed prediction of delivery mode and timing, spanning emergency cesarean, successful trial of labor after cesarean, and vaginal versus cesarean delivery. Because about one in three U.S. births occurs by cesarean and most of those are unplanned, carrying higher complication rates than planned surgery, accurate forecasting could transform labor ward planning. Machine learning models for intrapartum delivery mode prediction showed variable performance, with AUCs from 0.69 to 0.932, and one study found a k-nearest neighbor model predicting vaginal delivery four hours after admission with an AUC of 0.812, outperforming traditional logistic regression. For trial of labor after cesarean, three machine learning models significantly outperformed the established Maternal Fetal Medicine Unit calculator, though the margins were narrow and external validation remained limited. The Artificial Intelligence Dystocia Algorithm, designed to assess transverse fetal head position and cesarean risk, reached 95.5 percent accuracy on just 135 cases, a tantalizing but preliminary result.

Fetal heart rate tracing analysis, the backbone of intrapartum monitoring and the primary indication behind 27 percent of cesarean deliveries in the United States, has attracted its own wave of machine learning. Deep learning and neural network models for cardiotocography analysis have reported strong performance, with AUCs between 0.87 and 0.987, and one model categorized delivery mode from fetal heart rate signals with an AUC of 0.967. Imaging and radiomics studies clustered around two themes: MRI and ultrasound models for placenta accreta, and procedural ultrasound for anesthesia itself, including software for lumbar level identification and a neural network for real-time cricothyrotomy landmark identification using wireless handheld ultrasound, relevant to failed-airway preparation on labor and delivery. Notably, fusion models combining radiomic features with clinical and laboratory data consistently outperformed either data type alone, suggesting the most useful clinical applications will not rely on imaging in isolation.

The most rapidly emerging domain is patient education and conversational AI, with 15 of 16 studies published in 2024 or 2025. Multiple evaluations of ChatGPT and other chatbots found that responses to common questions about labor epidural analgesia were generally accurate and appropriately framed but often exceeded the recommended sixth-to-eighth grade reading level, and occasionally included factual errors or omitted clinically important caveats. A 2025 evaluation of ChatGPT-5 in obstetric and gynecologic emergencies highlighted reliability gaps that persist even in the newest models. Innovative tools like the Mothers’ Assistant for Labor analgesia, an interactive avatar-based education platform, point toward more sophisticated applications, but no included study prospectively evaluated whether large language model-supported education actually changed patient knowledge, anxiety, or satisfaction compared with standard counseling. On the provider side, a 2025 study comparing four large language models on complex anesthesia decision-making across 30 high-risk scenarios found that all four generated structured plans, with DeepSeek-R1 performing best in the obstetric subgroup, though the study was limited by small sample size and no outcome-based validation.

Perhaps the most important finding of the entire review is what is missing. Of the 154 original research studies, only 22, or 14 percent, reported external validation in an independent dataset. Prospective evaluations were rare, and almost none described integration into clinical workflow, meaning that even the most accurate models have rarely been tested in the hands of actual anesthesiologists caring for actual patients. The nine registered clinical trials identified cover narrow topics such as labor analgesia sequelae, lung ultrasound interpretation, and automated spinal landmark identification, a pipeline that looks thin relative to the sheer volume of model development activity. The authors also flag serious ethical concerns: algorithmic biases arising from unbalanced training datasets, historical health inequities, race-based clinical adjustments, and opaque black-box methodology could exacerbate the very racial and ethnic disparities in maternal outcomes that persist in the United States, where maternal mortality reached 32.6 deaths per 100,000 live births in 2022. The path forward, the researchers argue, requires a deliberate shift from building models to validating them externally, testing them prospectively, and embedding them responsibly into clinical workflows, with obstetric anesthesiologists serving as designers, evaluators, and stewards of the tools that will increasingly shape their practice. Until then, the extraordinary numbers on paper remain exactly that: numbers on paper.

Subject of Research: Applications of artificial intelligence and machine learning in obstetric anesthesia, including maternal risk prediction, delivery mode forecasting, fetal monitoring, and patient education

Article Title: Artificial intelligence and obstetric anesthesia: a scoping review

Article References: Givens, M. F., Rodriguez Caceres, E., Jotwani, R., Rubin, J. E., Goldstein, P. A., & White, R. S. (2026). Artificial intelligence and obstetric anesthesia: a scoping review. Frontiers in Anesthesiology, 5, Article 1896595. https://doi.org/10.3389/fanes.2026.1896595

Image Credits: AI Generated

DOI: 10.3389/fanes.2026.1896595

Keywords: artificial intelligence, machine learning, obstetric anesthesia, maternal mortality, postpartum hemorrhage, placenta accreta, pre-eclampsia, fetal heart rate monitoring, large language models, external validation, clinical decision support, scoping review

Sickle cell disease begins with a single amino acid substitution in hemoglobin, producing hemoglobin S, which polymerizes when oxygen tension falls. The result is the characteristic sickle shape: red blood cells become rigid, lose their deformability, and lodge in capillary beds, causing the ischemic pain known as vaso-occlusive crisis. In pregnancy, this biology collides with profound physiologic change. Plasma volume expands, the coagulation system shifts toward hypercoagulability, and inflammatory mediators rise, all of which can heighten the risk of crises, acute chest syndrome, and venous thrombosis. According to the source report, anemia and episodic pain affect more than half of pregnant individuals with sickle cell disease, preterm delivery occurs in 9 to 45 percent of such pregnancies, and fetal growth restriction appears in roughly 8 to 21 percent of cases.

The statistical backdrop is sobering. In a large United States cross-sectional study cited in the report, preeclampsia occurred in 10.9 percent of deliveries among patients with sickle cell disease, compared with 4.5 percent in controls. Preeclampsia itself is defined by the American College of Obstetricians and Gynecologists as new-onset hypertension after 20 weeks of gestation with proteinuria, or severe features even without proteinuria. Those severe features include systolic blood pressures of at least 160 mmHg or diastolic pressures of at least 110 mmHg, thrombocytopenia, impaired liver function, renal insufficiency, pulmonary edema, or new cerebral or visual symptoms. For a patient whose red cells already struggle to perfuse her tissues, the added vascular insult of preeclampsia creates a dangerous physiological double bind.

The patient in this case arrived at 33 weeks and 2 days of gestation in severe pain from a vaso-occlusive crisis. Her history included type 2 diabetes, obesity, and avascular necrosis of the right knee, a classic sickle cell complication in which bone tissue dies from interrupted blood supply. Her outpatient regimen already included buprenorphine, a partial opioid agonist, along with acetaminophen. Two days later she returned with left thigh pain rated 8 out of 10 despite her medications, and her blood pressure measured 143/90 mmHg. Intravenous hydromorphone provided minimal relief, prompting admission for inpatient pain control. Laboratory evaluation revealed a hemoglobin of 9.6 g/dL and a hematocrit of 26.2 percent, while a venous duplex ultrasound ruled out deep vein thrombosis as the cause of her leg pain.

One of the most technically interesting aspects of the case involved blood banking. The patient’s antibody screen was positive with a complex antibody profile, meaning her immune system carried antibodies that could react against common red cell antigens. Finding compatible packed red blood cells became genuinely difficult, a problem compounded by the fact that transfusion in sickle cell disease carries risks of alloimmunization, in which further antibodies develop, along with transfusion-related infection and iron overload. Rather than waiting for an emergency, the team transfused 4 units of crossmatched blood while the patient was clinically stable, raising her hemoglobin ahead of anticipated delivery-related blood loss. Intraoperative cell salvage, a technique that recovers blood lost during surgery for reinfusion, was planned as a backup but ultimately was not needed.

Then came the preeclampsia. During the admission, the patient developed repeated severe-range systolic blood pressures, documented between 165/86 and 167/90 mmHg. Notably, no proteinuria assessment was documented, but severe-range pressures alone satisfied diagnostic criteria. Her kidney function remained intact, with a creatinine of 0.59 mg/dL, indicating that end-organ damage had not yet taken hold. The team initiated oral nifedipine at 60 mg every 12 hours, a calcium channel blocker that relaxes vascular smooth muscle, and planned intrapartum magnesium sulfate for seizure prophylaxis, the standard safeguard against eclamptic convulsions. Serial fetal growth surveillance continued because both sickle cell disease and diabetes elevate the risk of fetal growth abnormalities, with an estimated fetal weight tracking at the 60th percentile.

The delivery decision arrived at 35 weeks when a biophysical profile score of 4 out of 8 signaled fetal compromise. Induction of labor was attempted, but after 7 hours of oxytocin augmentation, the cervix remained dilated at only 4 centimeters. The patient requested a primary cesarean section. Labor analgesia had been established through an epidural catheter, which the team redosed for surgical anesthesia, the preferred approach because neuraxial techniques avoid the airway manipulation and hemodynamic swings of general anesthesia. However, immediately after delivery the patient reported intense intraoperative pressure, and after discussion, the anesthesiologists converted to general anesthesia using fentanyl, propofol, succinylcholine, and ketamine, with midazolam, morphine, and ketorolac added for maintenance and analgesia. Hemodynamics remained stable through induction and emergence, a critical detail given the fragility of a preeclamptic, recently transfused patient.

The pharmacology threaded through this case reflects the delicate calculus of analgesia in pregnancy. Acetaminophen remains first-line for vaso-occlusive pain, though recent studies have raised questions about possible associations with childhood asthma or neurodevelopmental outcomes. Nonsteroidal anti-inflammatory drugs are avoided late in gestation because they can prematurely close the fetal ductus arteriosus and reduce amniotic fluid. Patients maintained on buprenorphine should continue their therapy through labor to prevent withdrawal, with full opioid agonists such as hydromorphone added for breakthrough pain and neonates observed for withdrawal if exposure is prolonged. A systematic review cited in the report found no definitive regimen for treating sickle cell pain crises in pregnancy, which means care rests on early recognition of triggers, timely analgesia, judicious fluids, and close maternal-fetal monitoring rather than any standardized protocol.

The postpartum course underscored that delivery resolves neither disease. Magnesium sulfate continued for 24 hours, nifedipine continued for blood pressure control, and the patient received 6 weeks of enoxaparin for venous thromboembolism prophylaxis, an important measure because preeclampsia and sickle cell disease both amplify clotting risk. Hematology recommended maintaining hemoglobin above 10 g/dL with transfusion support and continuing high-dose folic acid to support red cell production. Endocrinology discontinued insulin in favor of metformin for the diabetes. The neonate, weighing 2.565 kg, thrived. The authors emphasize that the lesson of this case is coordination: hematology, obstetrics, anesthesiology, palliative care, and endocrinology each held one thread of a clinical picture in which a single misstep, an incompatible transfusion, an uncontrolled pressure, an abrupt withdrawal, could have unraveled everything. As more individuals with sickle cell disease reach childbearing age, cases like this one map the terrain that multidisciplinary teams must navigate.

Subject of Research: Peripartum anesthetic management of pregnancy complicated by sickle cell disease and preeclampsia

Article Title: Peripartum Anesthetic Management of a Patient With Sickle Cell Disease and Preeclampsia

Article References: Dow, M., Srinivasan, A., & Ayad, S. (2026). Peripartum Anesthetic Management of a Patient With Sickle Cell Disease and Preeclampsia. Clinical Case Reports, 14(10), Article e73662. https://doi.org/10.1002/ccr3.73662

Image Credits: AI Generated

DOI: 10.1002/ccr3.73662

Keywords: sickle cell disease, preeclampsia, vaso-occlusive crisis, obstetric anesthesia, cesarean delivery, blood transfusion, magnesium sulfate, buprenorphine, pregnancy complications, epidural analgesia, fetal surveillance, multidisciplinary care